id	sid	tid	token	lemma	pos
cana-2991	1	1	communications	communication	NOUN
cana-2991	1	2	on	on	ADP
cana-2991	1	3	applied	apply	VERB
cana-2991	1	4	nonlinear	nonlinear	ADJ
cana-2991	1	5	analysis	analysis	NOUN
cana-2991	1	6	issn	issn	NOUN
cana-2991	1	7	:	:	PUNCT
cana-2991	1	8	1074	1074	NUM
cana-2991	1	9	-	-	PUNCT
cana-2991	1	10	133x	133x	NUM
cana-2991	1	11	vol	vol	NOUN
cana-2991	1	12	32	32	NUM
cana-2991	1	13	no	no	NOUN
cana-2991	1	14	.	.	PUNCT
cana-2991	2	1	5s	5s	NUM
cana-2991	2	2	(	(	PUNCT
cana-2991	2	3	2025	2025	NUM
cana-2991	2	4	)	)	PUNCT
cana-2991	2	5	151	151	NUM
cana-2991	2	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-2991	2	7	scalable	scalable	ADJ
cana-2991	2	8	fake	fake	ADJ
cana-2991	2	9	news	news	NOUN
cana-2991	2	10	detection	detection	NOUN
cana-2991	2	11	:	:	PUNCT
cana-2991	2	12	implementing	implement	VERB
cana-2991	2	13	nlp	nlp	NOUN
cana-2991	2	14	and	and	CCONJ
cana-2991	2	15	embedding	embed	VERB
cana-2991	2	16	models	model	NOUN
cana-2991	2	17	for	for	ADP
cana-2991	2	18	large	large	ADJ
cana-2991	2	19	-	-	PUNCT
cana-2991	2	20	scale	scale	NOUN
cana-2991	2	21	data	datum	NOUN
cana-2991	2	22	dr	dr	PROPN
cana-2991	2	23	.	.	PROPN
cana-2991	2	24	surjeet1	surjeet1	PROPN
cana-2991	2	25	,	,	PUNCT
cana-2991	2	26	dr.b.vasavi2	dr.b.vasavi2	PROPN
cana-2991	2	27	,	,	PUNCT
cana-2991	2	28	dr	dr	PROPN
cana-2991	2	29	padmesh	padmesh	PROPN
cana-2991	2	30	tripathi3	tripathi3	PROPN
cana-2991	2	31	,	,	PUNCT
cana-2991	2	32	vakaimalar	vakaimalar	ADJ
cana-2991	2	33	elamaran4	elamaran4	PROPN
cana-2991	2	34	,	,	PUNCT
cana-2991	2	35	ramya	ramya	PROPN
cana-2991	2	36	r5	r5	PROPN
cana-2991	2	37	,	,	PUNCT
cana-2991	2	38	anandh	anandh	NOUN
cana-2991	2	39	a6	a6	NOUN
cana-2991	2	40	1associate	1associate	NUM
cana-2991	2	41	professor	professor	NOUN
cana-2991	2	42	,	,	PUNCT
cana-2991	2	43	bharati	bharati	PROPN
cana-2991	2	44	vidyapeeth	vidyapeeth	PROPN
cana-2991	2	45	's	's	PART
cana-2991	2	46	college	college	NOUN
cana-2991	2	47	of	of	ADP
cana-2991	2	48	engineering	engineering	PROPN
cana-2991	2	49	,	,	PUNCT
cana-2991	2	50	new	new	ADJ
cana-2991	2	51	delhi	delhi	PROPN
cana-2991	2	52	.	.	PUNCT
cana-2991	3	1	surjeet.balhara@bharatividyapeeth.edu	surjeet.balhara@bharatividyapeeth.edu	PROPN
cana-2991	3	2	2associate	2associate	NUM
cana-2991	3	3	professor	professor	NOUN
cana-2991	3	4	,	,	PUNCT
cana-2991	3	5	maturi	maturi	PROPN
cana-2991	3	6	venkata	venkata	PROPN
cana-2991	3	7	subbarao(mvsr	subbarao(mvsr	PROPN
cana-2991	3	8	)	)	PUNCT
cana-2991	3	9	engineering	engineering	NOUN
cana-2991	3	10	college	college	NOUN
cana-2991	3	11	,	,	PUNCT
cana-2991	3	12	department	department	NOUN
cana-2991	3	13	of	of	ADP
cana-2991	3	14	information	information	NOUN
cana-2991	3	15	technology	technology	PROPN
cana-2991	3	16	,	,	PUNCT
cana-2991	3	17	hyderabad	hyderabad	PROPN
cana-2991	3	18	,	,	PUNCT
cana-2991	3	19	vasavi.bande@gmail.com	vasavi.bande@gmail.com	PROPN
cana-2991	3	20	3professor	3professor	NUM
cana-2991	3	21	,	,	PUNCT
cana-2991	3	22	department	department	NOUN
cana-2991	3	23	of	of	ADP
cana-2991	3	24	mathematics	mathematics	PROPN
cana-2991	3	25	,	,	PUNCT
cana-2991	3	26	delhi	delhi	PROPN
cana-2991	3	27	technical	technical	PROPN
cana-2991	3	28	campus	campus	PROPN
cana-2991	3	29	,	,	PUNCT
cana-2991	3	30	greater	great	ADJ
cana-2991	3	31	noida	noida	PROPN
cana-2991	3	32	,	,	PUNCT
cana-2991	3	33	up	up	ADP
cana-2991	3	34	,	,	PUNCT
cana-2991	3	35	india	india	PROPN
cana-2991	3	36	.	.	PUNCT
cana-2991	4	1	padmesh01@rediffmail.com	padmesh01@rediffmail.com	PROPN
cana-2991	4	2	4associate	4associate	PROPN
cana-2991	4	3	professor	professor	NOUN
cana-2991	4	4	,	,	PUNCT
cana-2991	4	5	dept	dept	NOUN
cana-2991	4	6	of	of	ADP
cana-2991	4	7	it	it	PRON
cana-2991	4	8	,	,	PUNCT
cana-2991	4	9	kamaraj	kamaraj	ADJ
cana-2991	4	10	college	college	NOUN
cana-2991	4	11	of	of	ADP
cana-2991	4	12	engineering	engineering	NOUN
cana-2991	4	13	and	and	CCONJ
cana-2991	4	14	technology	technology	NOUN
cana-2991	4	15	,	,	PUNCT
cana-2991	4	16	virudhunagar	virudhunagar	ADJ
cana-2991	4	17	,	,	PUNCT
cana-2991	4	18	tamilnadu	tamilnadu	ADJ
cana-2991	4	19	,	,	PUNCT
cana-2991	4	20	india	india	PROPN
cana-2991	4	21	,	,	PUNCT
cana-2991	4	22	vakaimalarit@kamarajengg.edu.in	vakaimalarit@kamarajengg.edu.in	VERB
cana-2991	4	23	5associate	5associate	PROPN
cana-2991	4	24	professor	professor	NOUN
cana-2991	4	25	,	,	PUNCT
cana-2991	4	26	dept	dept	NOUN
cana-2991	4	27	of	of	ADP
cana-2991	4	28	cse	cse	PROPN
cana-2991	4	29	,	,	PUNCT
cana-2991	4	30	kamaraj	kamaraj	ADJ
cana-2991	4	31	college	college	NOUN
cana-2991	4	32	of	of	ADP
cana-2991	4	33	engineering	engineering	NOUN
cana-2991	4	34	and	and	CCONJ
cana-2991	4	35	technology	technology	NOUN
cana-2991	4	36	,	,	PUNCT
cana-2991	4	37	virudhunagar	virudhunagar	ADJ
cana-2991	4	38	,	,	PUNCT
cana-2991	4	39	tamilnadu	tamilnadu	ADJ
cana-2991	4	40	,	,	PUNCT
cana-2991	4	41	india	india	PROPN
cana-2991	4	42	,	,	PUNCT
cana-2991	4	43	ramyacse@kamarajengg.edu.in	ramyacse@kamarajengg.edu.in	VERB
cana-2991	4	44	6associate	6associate	NUM
cana-2991	4	45	professor	professor	NOUN
cana-2991	4	46	,	,	PUNCT
cana-2991	4	47	dept	dept	NOUN
cana-2991	4	48	of	of	ADP
cana-2991	4	49	cse	cse	PROPN
cana-2991	4	50	,	,	PUNCT
cana-2991	4	51	kamaraj	kamaraj	ADJ
cana-2991	4	52	college	college	NOUN
cana-2991	4	53	of	of	ADP
cana-2991	4	54	engineering	engineering	NOUN
cana-2991	4	55	and	and	CCONJ
cana-2991	4	56	technology	technology	NOUN
cana-2991	4	57	,	,	PUNCT
cana-2991	4	58	virudhunagar	virudhunagar	ADJ
cana-2991	4	59	,	,	PUNCT
cana-2991	4	60	tamilnadu	tamilnadu	ADJ
cana-2991	4	61	,	,	PUNCT
cana-2991	4	62	india	india	PROPN
cana-2991	4	63	,	,	PUNCT
cana-2991	4	64	anandhcse@kamarajengg.edu.in	anandhcse@kamarajengg.edu.in	NOUN
cana-2991	4	65	corresponding	corresponding	ADJ
cana-2991	4	66	author	author	NOUN
cana-2991	4	67	mail	mail	NOUN
cana-2991	4	68	:	:	PUNCT
cana-2991	4	69	vasavi.bande@gmail.com	vasavi.bande@gmail.com	X
cana-2991	4	70	article	article	NOUN
cana-2991	4	71	history	history	NOUN
cana-2991	4	72	:	:	PUNCT
cana-2991	4	73	received	receive	VERB
cana-2991	4	74	:	:	PUNCT
cana-2991	4	75	06	06	NUM
cana-2991	4	76	-	-	SYM
cana-2991	4	77	10	10	NUM
cana-2991	4	78	-	-	PUNCT
cana-2991	4	79	2024	2024	NUM
cana-2991	4	80	revised	revise	VERB
cana-2991	4	81	:	:	PUNCT
cana-2991	4	82	27	27	NUM
cana-2991	4	83	-	-	SYM
cana-2991	4	84	11	11	NUM
cana-2991	4	85	-	-	PUNCT
cana-2991	4	86	2024	2024	NUM
cana-2991	4	87	accepted	accept	VERB
cana-2991	4	88	:	:	PUNCT
cana-2991	4	89	04	04	NUM
cana-2991	4	90	-	-	SYM
cana-2991	4	91	12	12	NUM
cana-2991	4	92	-	-	PUNCT
cana-2991	4	93	2024	2024	NUM
cana-2991	4	94	abstract	abstract	NOUN
cana-2991	4	95	:	:	PUNCT
cana-2991	4	96	this	this	DET
cana-2991	4	97	paper	paper	NOUN
cana-2991	4	98	describes	describe	VERB
cana-2991	4	99	a	a	DET
cana-2991	4	100	scalable	scalable	ADJ
cana-2991	4	101	approach	approach	NOUN
cana-2991	4	102	to	to	ADP
cana-2991	4	103	fake	fake	ADJ
cana-2991	4	104	news	news	NOUN
cana-2991	4	105	detection	detection	NOUN
cana-2991	4	106	by	by	ADP
cana-2991	4	107	employing	employ	VERB
cana-2991	4	108	natural	natural	ADJ
cana-2991	4	109	language	language	NOUN
cana-2991	4	110	processing	processing	NOUN
cana-2991	4	111	and	and	CCONJ
cana-2991	4	112	word	word	NOUN
cana-2991	4	113	embedding	embed	VERB
cana-2991	4	114	models	model	NOUN
cana-2991	4	115	for	for	ADP
cana-2991	4	116	huge	huge	ADJ
cana-2991	4	117	datasets	dataset	NOUN
cana-2991	4	118	.	.	PUNCT
cana-2991	5	1	the	the	DET
cana-2991	5	2	collective	collective	ADJ
cana-2991	5	3	work	work	NOUN
cana-2991	5	4	with	with	ADP
cana-2991	5	5	different	different	ADJ
cana-2991	5	6	embeddings	embedding	NOUN
cana-2991	5	7	(	(	PUNCT
cana-2991	5	8	bag	bag	NOUN
cana-2991	5	9	of	of	ADP
cana-2991	5	10	words	word	NOUN
cana-2991	5	11	,	,	PUNCT
cana-2991	5	12	tf	tf	PROPN
cana-2991	5	13	-	-	PUNCT
cana-2991	5	14	idf	idf	PROPN
cana-2991	5	15	,	,	PUNCT
cana-2991	5	16	word2vec	word2vec	X
cana-2991	5	17	,	,	PUNCT
cana-2991	5	18	and	and	CCONJ
cana-2991	5	19	bidirectional	bidirectional	ADJ
cana-2991	5	20	encoder	encoder	NOUN
cana-2991	5	21	representations	representation	VERB
cana-2991	5	22	from	from	ADP
cana-2991	5	23	transformers	transformer	NOUN
cana-2991	5	24	bert	bert	PROPN
cana-2991	5	25	)	)	PUNCT
cana-2991	5	26	,	,	PUNCT
cana-2991	5	27	extracting	extract	VERB
cana-2991	5	28	not	not	PART
cana-2991	5	29	only	only	ADJ
cana-2991	5	30	word	word	NOUN
cana-2991	5	31	frequency	frequency	NOUN
cana-2991	5	32	but	but	CCONJ
cana-2991	5	33	also	also	ADV
cana-2991	5	34	content	content	NOUN
cana-2991	5	35	relation	relation	NOUN
cana-2991	5	36	in	in	ADP
cana-2991	5	37	news	news	NOUN
cana-2991	5	38	articles	article	NOUN
cana-2991	5	39	.	.	PUNCT
cana-2991	6	1	these	these	DET
cana-2991	6	2	embeddings	embedding	NOUN
cana-2991	6	3	are	be	AUX
cana-2991	6	4	then	then	ADV
cana-2991	6	5	combined	combine	VERB
cana-2991	6	6	with	with	ADP
cana-2991	6	7	machine	machine	NOUN
cana-2991	6	8	learning	learn	VERB
cana-2991	6	9	classifiers	classifier	NOUN
cana-2991	6	10	including	include	VERB
cana-2991	6	11	logistic	logistic	ADJ
cana-2991	6	12	regression	regression	NOUN
cana-2991	6	13	,	,	PUNCT
cana-2991	6	14	random	random	ADJ
cana-2991	6	15	forests	forest	NOUN
cana-2991	6	16	and	and	CCONJ
cana-2991	6	17	neural	neural	ADJ
cana-2991	6	18	networks	network	NOUN
cana-2991	6	19	to	to	PART
cana-2991	6	20	evaluate	evaluate	VERB
cana-2991	6	21	how	how	SCONJ
cana-2991	6	22	different	different	ADJ
cana-2991	6	23	models	model	NOUN
cana-2991	6	24	perform	perform	VERB
cana-2991	6	25	.	.	PUNCT
cana-2991	7	1	it	it	PRON
cana-2991	7	2	is	be	AUX
cana-2991	7	3	a	a	DET
cana-2991	7	4	scalable	scalable	ADJ
cana-2991	7	5	system	system	NOUN
cana-2991	7	6	using	use	VERB
cana-2991	7	7	distributed	distribute	VERB
cana-2991	7	8	processing	processing	NOUN
cana-2991	7	9	frameworks	framework	NOUN
cana-2991	7	10	to	to	PART
cana-2991	7	11	process	process	VERB
cana-2991	7	12	large	large	ADJ
cana-2991	7	13	amounts	amount	NOUN
cana-2991	7	14	of	of	ADP
cana-2991	7	15	data	datum	NOUN
cana-2991	7	16	and	and	CCONJ
cana-2991	7	17	to	to	PART
cana-2991	7	18	enable	enable	VERB
cana-2991	7	19	large	large	ADJ
cana-2991	7	20	scale	scale	NOUN
cana-2991	7	21	model	model	NOUN
cana-2991	7	22	training	training	NOUN
cana-2991	7	23	.	.	PUNCT
cana-2991	8	1	our	our	PRON
cana-2991	8	2	methodology	methodology	NOUN
cana-2991	8	3	with	with	ADP
cana-2991	8	4	widely	widely	ADV
cana-2991	8	5	adopted	adopt	VERB
cana-2991	8	6	fake	fake	ADJ
cana-2991	8	7	news	news	NOUN
cana-2991	8	8	datasets	dataset	NOUN
cana-2991	8	9	including	include	VERB
cana-2991	8	10	politifact	politifact	PROPN
cana-2991	8	11	and	and	CCONJ
cana-2991	8	12	the	the	DET
cana-2991	8	13	liar	liar	NOUN
cana-2991	8	14	dataset	dataset	NOUN
cana-2991	8	15	show	show	VERB
cana-2991	8	16	superior	superior	ADJ
cana-2991	8	17	classification	classification	NOUN
cana-2991	8	18	results	result	NOUN
cana-2991	8	19	,	,	PUNCT
cana-2991	8	20	in	in	ADP
cana-2991	8	21	particular	particular	ADJ
cana-2991	8	22	when	when	SCONJ
cana-2991	8	23	employing	employ	VERB
cana-2991	8	24	deep	deep	ADJ
cana-2991	8	25	learning	learning	NOUN
cana-2991	8	26	-	-	PUNCT
cana-2991	8	27	based	base	VERB
cana-2991	8	28	embeddings	embedding	NOUN
cana-2991	8	29	such	such	ADJ
cana-2991	8	30	as	as	ADP
cana-2991	8	31	bert	bert	PROPN
cana-2991	8	32	which	which	PRON
cana-2991	8	33	outperforms	outperform	VERB
cana-2991	8	34	traditional	traditional	ADJ
cana-2991	8	35	methods	method	NOUN
cana-2991	8	36	by	by	ADP
cana-2991	8	37	accuracy	accuracy	NOUN
cana-2991	8	38	and	and	CCONJ
cana-2991	8	39	recall	recall	NOUN
cana-2991	8	40	.	.	PUNCT
cana-2991	9	1	the	the	DET
cana-2991	9	2	authors	author	NOUN
cana-2991	9	3	investigate	investigate	VERB
cana-2991	9	4	the	the	DET
cana-2991	9	5	effect	effect	NOUN
cana-2991	9	6	of	of	ADP
cana-2991	9	7	text	text	NOUN
cana-2991	9	8	preprocessing	preprocessing	NOUN
cana-2991	9	9	methods	method	NOUN
cana-2991	9	10	(	(	PUNCT
cana-2991	9	11	e.g.	e.g.	ADV
cana-2991	9	12	stop	stop	VERB
cana-2991	9	13	-	-	PUNCT
cana-2991	9	14	word	word	NOUN
cana-2991	9	15	removal	removal	NOUN
cana-2991	9	16	,	,	PUNCT
cana-2991	9	17	tokenization	tokenization	NOUN
cana-2991	9	18	)	)	PUNCT
cana-2991	9	19	on	on	ADP
cana-2991	9	20	classification	classification	NOUN
cana-2991	9	21	results	result	NOUN
cana-2991	9	22	.	.	PUNCT
cana-2991	10	1	our	our	PRON
cana-2991	10	2	findings	finding	NOUN
cana-2991	10	3	call	call	VERB
cana-2991	10	4	attention	attention	NOUN
cana-2991	10	5	to	to	ADP
cana-2991	10	6	the	the	DET
cana-2991	10	7	trade	trade	NOUN
cana-2991	10	8	-	-	PUNCT
cana-2991	10	9	offs	off	NOUN
cana-2991	10	10	required	require	VERB
cana-2991	10	11	for	for	ADP
cana-2991	10	12	launching	launch	VERB
cana-2991	10	13	large	large	ADJ
cana-2991	10	14	-	-	PUNCT
cana-2991	10	15	scale	scale	NOUN
cana-2991	10	16	fake	fake	ADJ
cana-2991	10	17	news	news	NOUN
cana-2991	10	18	detection	detection	NOUN
cana-2991	10	19	systems	system	NOUN
cana-2991	10	20	given	give	VERB
cana-2991	10	21	a	a	DET
cana-2991	10	22	balance	balance	NOUN
cana-2991	10	23	between	between	ADP
cana-2991	10	24	model	model	NOUN
cana-2991	10	25	complexity	complexity	NOUN
cana-2991	10	26	and	and	CCONJ
cana-2991	10	27	computational	computational	ADJ
cana-2991	10	28	efficiency	efficiency	NOUN
cana-2991	10	29	.	.	PUNCT
cana-2991	11	1	keywords	keyword	NOUN
cana-2991	11	2	:	:	PUNCT
cana-2991	11	3	news	news	NOUN
cana-2991	11	4	,	,	PUNCT
cana-2991	11	5	detection	detection	NOUN
cana-2991	11	6	,	,	PUNCT
cana-2991	11	7	system	system	NOUN
cana-2991	11	8	,	,	PUNCT
cana-2991	11	9	embeddings	embedding	NOUN
cana-2991	11	10	,	,	PUNCT
cana-2991	11	11	word	word	NOUN
cana-2991	11	12	,	,	PUNCT
cana-2991	11	13	backdrop	backdrop	ADJ
cana-2991	11	14	,	,	PUNCT
cana-2991	11	15	combination	combination	NOUN
cana-2991	11	16	,	,	PUNCT
cana-2991	11	17	nlp	nlp	NOUN
cana-2991	11	18	,	,	PUNCT
cana-2991	11	19	bert	bert	PROPN
cana-2991	11	20	,	,	PUNCT
cana-2991	11	21	automated	automate	VERB
cana-2991	11	22	,	,	PUNCT
cana-2991	11	23	tokenization	tokenization	NOUN
cana-2991	11	24	,	,	PUNCT
cana-2991	11	25	classification	classification	NOUN
cana-2991	11	26	.	.	PUNCT
cana-2991	12	1	introduction	introduction	NOUN
cana-2991	12	2	the	the	DET
cana-2991	12	3	way	way	NOUN
cana-2991	12	4	people	people	NOUN
cana-2991	12	5	interact	interact	VERB
cana-2991	12	6	with	with	ADP
cana-2991	12	7	news	news	NOUN
cana-2991	12	8	and	and	CCONJ
cana-2991	12	9	media	medium	NOUN
cana-2991	12	10	is	be	AUX
cana-2991	12	11	seriously	seriously	ADV
cana-2991	12	12	altered	alter	VERB
cana-2991	12	13	by	by	ADP
cana-2991	12	14	the	the	DET
cana-2991	12	15	global	global	ADJ
cana-2991	12	16	circulation	circulation	NOUN
cana-2991	12	17	of	of	ADP
cana-2991	12	18	content	content	NOUN
cana-2991	12	19	in	in	ADP
cana-2991	12	20	the	the	DET
cana-2991	12	21	digital	digital	ADJ
cana-2991	12	22	age	age	NOUN
cana-2991	12	23	.	.	PUNCT
cana-2991	13	1	this	this	PRON
cana-2991	13	2	has	have	AUX
cana-2991	13	3	enabled	enable	VERB
cana-2991	13	4	information	information	NOUN
cana-2991	13	5	to	to	PART
cana-2991	13	6	be	be	AUX
cana-2991	13	7	circulated	circulate	VERB
cana-2991	13	8	faster	fast	ADV
cana-2991	13	9	than	than	ADP
cana-2991	13	10	ever	ever	ADV
cana-2991	13	11	,	,	PUNCT
cana-2991	13	12	however	however	ADV
cana-2991	13	13	it	it	PRON
cana-2991	13	14	has	have	AUX
cana-2991	13	15	also	also	ADV
cana-2991	13	16	brought	bring	VERB
cana-2991	13	17	a	a	DET
cana-2991	13	18	new	new	ADJ
cana-2991	13	19	set	set	NOUN
cana-2991	13	20	of	of	ADP
cana-2991	13	21	hurdles	hurdle	NOUN
cana-2991	13	22	in	in	ADP
cana-2991	13	23	the	the	DET
cana-2991	13	24	form	form	NOUN
cana-2991	13	25	of	of	ADP
cana-2991	13	26	fake	fake	ADJ
cana-2991	13	27	news	news	NOUN
cana-2991	13	28	:	:	PUNCT
cana-2991	13	29	misinformation	misinformation	NOUN
cana-2991	13	30	or	or	CCONJ
cana-2991	13	31	disinformation	disinformation	NOUN
cana-2991	13	32	.	.	PUNCT
cana-2991	14	1	fake	fake	ADJ
cana-2991	14	2	news	news	NOUN
cana-2991	14	3	that	that	PRON
cana-2991	14	4	is	be	AUX
cana-2991	14	5	often	often	ADV
cana-2991	14	6	presented	present	VERB
cana-2991	14	7	as	as	SCONJ
cana-2991	14	8	if	if	SCONJ
cana-2991	14	9	it	it	PRON
cana-2991	14	10	were	be	AUX
cana-2991	14	11	true	true	ADJ
cana-2991	14	12	and	and	CCONJ
cana-2991	14	13	verified	verify	VERB
cana-2991	14	14	information	information	NOUN
cana-2991	14	15	intentionally	intentionally	ADV
cana-2991	14	16	spread	spread	VERB
cana-2991	14	17	to	to	PART
cana-2991	14	18	deceive	deceive	VERB
cana-2991	14	19	society	society	NOUN
cana-2991	14	20	has	have	AUX
cana-2991	14	21	become	become	VERB
cana-2991	14	22	a	a	DET
cana-2991	14	23	global	global	ADJ
cana-2991	14	24	corrupting	corrupting	ADJ
cana-2991	14	25	force	force	NOUN
cana-2991	14	26	,	,	PUNCT
cana-2991	14	27	mobilizing	mobilize	VERB
cana-2991	14	28	public	public	ADJ
cana-2991	14	29	opinion	opinion	NOUN
cana-2991	14	30	during	during	ADP
cana-2991	14	31	elections	election	NOUN
cana-2991	14	32	and	and	CCONJ
cana-2991	14	33	obscuring	obscure	VERB
cana-2991	14	34	the	the	DET
cana-2991	14	35	truth	truth	NOUN
cana-2991	14	36	related	relate	VERB
cana-2991	14	37	to	to	ADP
cana-2991	14	38	fundamental	fundamental	ADJ
cana-2991	14	39	matters	matter	NOUN
cana-2991	14	40	of	of	ADP
cana-2991	14	41	the	the	DET
cana-2991	14	42	international	international	ADJ
cana-2991	14	43	community	community	NOUN
cana-2991	14	44	.	.	PUNCT
cana-2991	15	1	when	when	SCONJ
cana-2991	15	2	such	such	ADJ
cana-2991	15	3	content	content	NOUN
cana-2991	15	4	goes	go	VERB
cana-2991	15	5	viral	viral	ADJ
cana-2991	15	6	,	,	PUNCT
cana-2991	15	7	the	the	DET
cana-2991	15	8	mailto:surjeet.balhara@bharatividyapeeth.edu	mailto:surjeet.balhara@bharatividyapeeth.edu	VERB
cana-2991	15	9	mailto:vasavi.bande@gmail.com	mailto:vasavi.bande@gmail.com	X
cana-2991	15	10	mailto:padmesh01@rediffmail.com	mailto:padmesh01@rediffmail.com	PROPN
cana-2991	15	11	mailto:vakaimalarit@kamarajengg.edu.in	mailto:vakaimalarit@kamarajengg.edu.in	PROPN
cana-2991	15	12	mailto:anandhcse@kamarajengg.edu.in	mailto:anandhcse@kamarajengg.edu.in	PROPN
cana-2991	15	13	mailto:vasavi.bande@gmail.com	mailto:vasavi.bande@gmail.com	NOUN
cana-2991	15	14	communications	communication	NOUN
cana-2991	15	15	on	on	ADP
cana-2991	15	16	applied	apply	VERB
cana-2991	15	17	nonlinear	nonlinear	ADJ
cana-2991	15	18	analysis	analysis	NOUN
cana-2991	15	19	issn	issn	NOUN
cana-2991	15	20	:	:	PUNCT
cana-2991	15	21	1074	1074	NUM
cana-2991	15	22	-	-	PUNCT
cana-2991	15	23	133x	133x	NUM
cana-2991	15	24	vol	vol	NOUN
cana-2991	15	25	32	32	NUM
cana-2991	15	26	no	no	NOUN
cana-2991	15	27	.	.	PUNCT
cana-2991	16	1	5s	5s	NUM
cana-2991	16	2	(	(	PUNCT
cana-2991	16	3	2025	2025	NUM
cana-2991	16	4	)	)	PUNCT
cana-2991	16	5	152	152	NUM
cana-2991	16	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	16	7	consequences	consequence	NOUN
cana-2991	16	8	can	can	AUX
cana-2991	16	9	be	be	AUX
cana-2991	16	10	serious	serious	ADJ
cana-2991	16	11	:	:	PUNCT
cana-2991	16	12	propagandists	propagandist	NOUN
cana-2991	16	13	are	be	AUX
cana-2991	16	14	able	able	ADJ
cana-2991	16	15	to	to	PART
cana-2991	16	16	break	break	VERB
cana-2991	16	17	public	public	ADJ
cana-2991	16	18	trust	trust	NOUN
cana-2991	16	19	in	in	ADP
cana-2991	16	20	current	current	ADJ
cana-2991	16	21	journalism	journalism	NOUN
cana-2991	16	22	,	,	PUNCT
cana-2991	16	23	tear	tear	ADJ
cana-2991	16	24	societies	society	NOUN
cana-2991	16	25	even	even	ADV
cana-2991	16	26	further	far	ADV
cana-2991	16	27	apart	apart	ADV
cana-2991	16	28	or	or	CCONJ
cana-2991	16	29	even	even	ADV
cana-2991	16	30	organize	organize	VERB
cana-2991	16	31	violence	violence	NOUN
cana-2991	16	32	and	and	CCONJ
cana-2991	16	33	riots	riot	NOUN
cana-2991	16	34	.	.	PUNCT
cana-2991	17	1	that	that	PRON
cana-2991	17	2	is	be	AUX
cana-2991	17	3	why	why	SCONJ
cana-2991	17	4	some	some	DET
cana-2991	17	5	applied	applied	ADJ
cana-2991	17	6	areas	area	NOUN
cana-2991	17	7	(	(	PUNCT
cana-2991	17	8	e.g.	e.g.	ADV
cana-2991	17	9	,	,	PUNCT
cana-2991	17	10	artificial	artificial	ADJ
cana-2991	17	11	intelligence	intelligence	NOUN
cana-2991	17	12	,	,	PUNCT
cana-2991	17	13	natural	natural	ADJ
cana-2991	17	14	language	language	NOUN
cana-2991	17	15	processing	processing	NOUN
cana-2991	17	16	and	and	CCONJ
cana-2991	17	17	media	medium	NOUN
cana-2991	17	18	studies	study	NOUN
cana-2991	17	19	)	)	PUNCT
cana-2991	17	20	have	have	AUX
cana-2991	17	21	been	be	AUX
cana-2991	17	22	working	work	VERB
cana-2991	17	23	hard	hard	ADV
cana-2991	17	24	towards	towards	ADP
cana-2991	17	25	the	the	DET
cana-2991	17	26	detection	detection	NOUN
cana-2991	17	27	of	of	ADP
cana-2991	17	28	fake	fake	ADJ
cana-2991	17	29	news	news	NOUN
cana-2991	17	30	and	and	CCONJ
cana-2991	17	31	extending	extend	VERB
cana-2991	17	32	effort	effort	NOUN
cana-2991	17	33	in	in	ADP
cana-2991	17	34	studying	study	VERB
cana-2991	17	35	its	its	PRON
cana-2991	17	36	propagation[1	propagation[1	NOUN
cana-2991	17	37	]	]	X
cana-2991	17	38	.	.	PUNCT
cana-2991	18	1	this	this	PRON
cana-2991	18	2	is	be	AUX
cana-2991	18	3	very	very	ADV
cana-2991	18	4	challenging	challenging	ADJ
cana-2991	18	5	to	to	PART
cana-2991	18	6	identify	identify	VERB
cana-2991	18	7	fake	fake	ADJ
cana-2991	18	8	news	news	NOUN
cana-2991	18	9	,	,	PUNCT
cana-2991	18	10	as	as	SCONJ
cana-2991	18	11	we	we	PRON
cana-2991	18	12	know	know	VERB
cana-2991	18	13	these	these	DET
cana-2991	18	14	days	day	NOUN
cana-2991	18	15	digital	digital	ADJ
cana-2991	18	16	platforms	platform	NOUN
cana-2991	18	17	are	be	AUX
cana-2991	18	18	rapidly	rapidly	ADV
cana-2991	18	19	growing	grow	VERB
cana-2991	18	20	and	and	CCONJ
cana-2991	18	21	especially	especially	ADV
cana-2991	18	22	social	social	ADJ
cana-2991	18	23	media	medium	NOUN
cana-2991	18	24	.	.	PUNCT
cana-2991	19	1	social	social	ADJ
cana-2991	19	2	media	medium	NOUN
cana-2991	19	3	algorithms	algorithm	NOUN
cana-2991	19	4	reward	reward	NOUN
cana-2991	19	5	engagement	engagement	NOUN
cana-2991	19	6	,	,	PUNCT
cana-2991	19	7	sharing	share	VERB
cana-2991	19	8	the	the	DET
cana-2991	19	9	content	content	NOUN
cana-2991	19	10	that	that	PRON
cana-2991	19	11	gets	get	VERB
cana-2991	19	12	people	people	NOUN
cana-2991	19	13	to	to	PART
cana-2991	19	14	click	click	VERB
cana-2991	19	15	on	on	ADP
cana-2991	19	16	it	it	PRON
cana-2991	19	17	,	,	PUNCT
cana-2991	19	18	like	like	ADP
cana-2991	19	19	it	it	PRON
cana-2991	19	20	,	,	PUNCT
cana-2991	19	21	and	and	CCONJ
cana-2991	19	22	share	share	NOUN
cana-2991	19	23	,	,	PUNCT
cana-2991	19	24	whether	whether	SCONJ
cana-2991	19	25	or	or	CCONJ
cana-2991	19	26	not	not	PART
cana-2991	19	27	those	those	DET
cana-2991	19	28	posts	post	NOUN
cana-2991	19	29	are	be	AUX
cana-2991	19	30	accurate	accurate	ADJ
cana-2991	19	31	.	.	PUNCT
cana-2991	20	1	here	here	ADV
cana-2991	20	2	,	,	PUNCT
cana-2991	20	3	fake	fake	ADJ
cana-2991	20	4	news	news	NOUN
cana-2991	20	5	spreads	spread	VERB
cana-2991	20	6	faster	fast	ADV
cana-2991	20	7	and	and	CCONJ
cana-2991	20	8	reaches	reach	VERB
cana-2991	20	9	more	more	ADJ
cana-2991	20	10	people	people	NOUN
cana-2991	20	11	compared	compare	VERB
cana-2991	20	12	to	to	ADP
cana-2991	20	13	accurate	accurate	ADJ
cana-2991	20	14	information	information	NOUN
cana-2991	20	15	.	.	PUNCT
cana-2991	21	1	it	it	PRON
cana-2991	21	2	was	be	AUX
cana-2991	21	3	especially	especially	ADV
cana-2991	21	4	prominent	prominent	ADJ
cana-2991	21	5	for	for	ADP
cana-2991	21	6	things	thing	NOUN
cana-2991	21	7	like	like	ADP
cana-2991	21	8	the	the	DET
cana-2991	21	9	2016	2016	NUM
cana-2991	21	10	u.s	u.s	PROPN
cana-2991	21	11	.	.	PROPN
cana-2991	21	12	presidential	presidential	ADJ
cana-2991	21	13	election	election	NOUN
cana-2991	21	14	and	and	CCONJ
cana-2991	21	15	the	the	DET
cana-2991	21	16	brexit	brexit	NOUN
cana-2991	21	17	vote	vote	NOUN
cana-2991	21	18	,	,	PUNCT
cana-2991	21	19	with	with	ADP
cana-2991	21	20	people	people	NOUN
cana-2991	21	21	lapping	lap	VERB
cana-2991	21	22	up	up	ADP
cana-2991	21	23	fake	fake	ADJ
cana-2991	21	24	news	news	NOUN
cana-2991	21	25	stories	story	NOUN
cana-2991	21	26	,	,	PUNCT
cana-2991	21	27	of	of	ADP
cana-2991	21	28	which	which	PRON
cana-2991	21	29	there	there	PRON
cana-2991	21	30	were	be	VERB
cana-2991	21	31	many	many	ADJ
cana-2991	21	32	.	.	PUNCT
cana-2991	22	1	given	give	VERB
cana-2991	22	2	the	the	DET
cana-2991	22	3	growing	grow	VERB
cana-2991	22	4	sophistication	sophistication	NOUN
cana-2991	22	5	of	of	ADP
cana-2991	22	6	fake	fake	ADJ
cana-2991	22	7	news	news	NOUN
cana-2991	22	8	,	,	PUNCT
cana-2991	22	9	more	more	ADV
cana-2991	22	10	sophisticated	sophisticated	ADJ
cana-2991	22	11	tools	tool	NOUN
cana-2991	22	12	are	be	AUX
cana-2991	22	13	needed	need	VERB
cana-2991	22	14	for	for	SCONJ
cana-2991	22	15	these	these	DET
cana-2991	22	16	tools	tool	NOUN
cana-2991	22	17	to	to	PART
cana-2991	22	18	detect	detect	VERB
cana-2991	22	19	and	and	CCONJ
cana-2991	22	20	flag	flag	VERB
cana-2991	22	21	such	such	ADJ
cana-2991	22	22	content	content	NOUN
cana-2991	22	23	in	in	ADP
cana-2991	22	24	advance	advance	NOUN
cana-2991	22	25	so	so	SCONJ
cana-2991	22	26	that	that	SCONJ
cana-2991	22	27	it	it	PRON
cana-2991	22	28	can	can	AUX
cana-2991	22	29	not	not	PART
cana-2991	22	30	happen	happen	VERB
cana-2991	22	31	and	and	CCONJ
cana-2991	22	32	cause	cause	VERB
cana-2991	22	33	societal	societal	ADJ
cana-2991	22	34	damage	damage	NOUN
cana-2991	22	35	.	.	PUNCT
cana-2991	23	1	given	give	VERB
cana-2991	23	2	the	the	DET
cana-2991	23	3	sheer	sheer	ADJ
cana-2991	23	4	scale	scale	NOUN
cana-2991	23	5	of	of	ADP
cana-2991	23	6	content	content	NOUN
cana-2991	23	7	that	that	PRON
cana-2991	23	8	is	be	AUX
cana-2991	23	9	created	create	VERB
cana-2991	23	10	daily	daily	ADV
cana-2991	23	11	,	,	PUNCT
cana-2991	23	12	traditional	traditional	ADJ
cana-2991	23	13	means	mean	NOUN
cana-2991	23	14	such	such	ADJ
cana-2991	23	15	as	as	ADP
cana-2991	23	16	human	human	ADJ
cana-2991	23	17	fact	fact	NOUN
cana-2991	23	18	-	-	PUNCT
cana-2991	23	19	checking	checking	NOUN
cana-2991	23	20	have	have	AUX
cana-2991	23	21	definitely	definitely	ADV
cana-2991	23	22	encountered	encounter	VERB
cana-2991	23	23	limitations	limitation	NOUN
cana-2991	23	24	in	in	ADP
cana-2991	23	25	this	this	DET
cana-2991	23	26	age	age	NOUN
cana-2991	23	27	.	.	PUNCT
cana-2991	24	1	this	this	PRON
cana-2991	24	2	is	be	AUX
cana-2991	24	3	why	why	SCONJ
cana-2991	24	4	automated	automated	ADJ
cana-2991	24	5	detection	detection	NOUN
cana-2991	24	6	systems	system	NOUN
cana-2991	24	7	for	for	ADP
cana-2991	24	8	fake	fake	ADJ
cana-2991	24	9	news	news	NOUN
cana-2991	24	10	are	be	AUX
cana-2991	24	11	crucial	crucial	ADJ
cana-2991	24	12	;	;	PUNCT
cana-2991	24	13	they	they	PRON
cana-2991	24	14	can	can	AUX
cana-2991	24	15	prevent	prevent	VERB
cana-2991	24	16	the	the	DET
cana-2991	24	17	problem	problem	NOUN
cana-2991	24	18	from	from	ADP
cana-2991	24	19	continuing	continue	VERB
cana-2991	24	20	to	to	PART
cana-2991	24	21	spiral	spiral	VERB
cana-2991	24	22	out	out	ADP
cana-2991	24	23	of	of	ADP
cana-2991	24	24	control	control	NOUN
cana-2991	24	25	.	.	PUNCT
cana-2991	25	1	the	the	DET
cana-2991	25	2	automated	automate	VERB
cana-2991	25	3	detection	detection	NOUN
cana-2991	25	4	of	of	ADP
cana-2991	25	5	fake	fake	ADJ
cana-2991	25	6	news	news	NOUN
cana-2991	25	7	faces	face	VERB
cana-2991	25	8	exciting	exciting	ADJ
cana-2991	25	9	challenges	challenge	NOUN
cana-2991	25	10	which	which	PRON
cana-2991	25	11	can	can	AUX
cana-2991	25	12	be	be	AUX
cana-2991	25	13	addressed	address	VERB
cana-2991	25	14	by	by	ADP
cana-2991	25	15	natural	natural	ADJ
cana-2991	25	16	language	language	NOUN
cana-2991	25	17	processing	processing	NOUN
cana-2991	25	18	.	.	PUNCT
cana-2991	26	1	performing	perform	VERB
cana-2991	26	2	classification	classification	NOUN
cana-2991	26	3	on	on	ADP
cana-2991	26	4	the	the	DET
cana-2991	26	5	textual	textual	ADJ
cana-2991	26	6	content	content	NOUN
cana-2991	26	7	nlp	nlp	NOUN
cana-2991	26	8	techniques	technique	NOUN
cana-2991	26	9	can	can	AUX
cana-2991	26	10	be	be	AUX
cana-2991	26	11	applied	apply	VERB
cana-2991	26	12	,	,	PUNCT
cana-2991	26	13	i.e.	i.e.	X
cana-2991	26	14	,	,	PUNCT
cana-2991	26	15	to	to	PART
cana-2991	26	16	classify	classify	VERB
cana-2991	26	17	the	the	DET
cana-2991	26	18	articles	article	NOUN
cana-2991	26	19	as	as	ADP
cana-2991	26	20	real	real	ADJ
cana-2991	26	21	or	or	CCONJ
cana-2991	26	22	fake	fake	ADJ
cana-2991	26	23	based	base	VERB
cana-2991	26	24	on	on	ADP
cana-2991	26	25	the	the	DET
cana-2991	26	26	language	language	NOUN
cana-2991	26	27	of	of	ADP
cana-2991	26	28	particular	particular	ADJ
cana-2991	26	29	patterns	pattern	NOUN
cana-2991	26	30	and	and	CCONJ
cana-2991	26	31	features	feature	NOUN
cana-2991	26	32	.	.	PUNCT
cana-2991	27	1	a	a	DET
cana-2991	27	2	key	key	ADJ
cana-2991	27	3	part	part	NOUN
cana-2991	27	4	of	of	ADP
cana-2991	27	5	this	this	DET
cana-2991	27	6	process	process	NOUN
cana-2991	27	7	is	be	AUX
cana-2991	27	8	word	word	NOUN
cana-2991	27	9	embeddings	embedding	NOUN
cana-2991	27	10	,	,	PUNCT
cana-2991	27	11	which	which	PRON
cana-2991	27	12	are	be	AUX
cana-2991	27	13	numerical	numerical	ADJ
cana-2991	27	14	vectors	vector	NOUN
cana-2991	27	15	that	that	PRON
cana-2991	27	16	represent	represent	VERB
cana-2991	27	17	words	word	NOUN
cana-2991	27	18	and	and	CCONJ
cana-2991	27	19	take	take	VERB
cana-2991	27	20	into	into	ADP
cana-2991	27	21	account	account	NOUN
cana-2991	27	22	the	the	DET
cana-2991	27	23	frequency	frequency	NOUN
cana-2991	27	24	of	of	ADP
cana-2991	27	25	words	word	NOUN
cana-2991	27	26	and	and	CCONJ
cana-2991	27	27	how	how	SCONJ
cana-2991	27	28	they	they	PRON
cana-2991	27	29	are	be	AUX
cana-2991	27	30	related	relate	VERB
cana-2991	27	31	.	.	PUNCT
cana-2991	28	1	in	in	ADP
cana-2991	28	2	the	the	DET
cana-2991	28	3	course	course	NOUN
cana-2991	28	4	of	of	ADP
cana-2991	28	5	recent	recent	ADJ
cana-2991	28	6	years	year	NOUN
cana-2991	28	7	various	various	ADJ
cana-2991	28	8	word	word	NOUN
cana-2991	28	9	embedding	embed	VERB
cana-2991	28	10	techniques	technique	NOUN
cana-2991	28	11	like	like	ADP
cana-2991	28	12	bow	bow	NOUN
cana-2991	28	13	,	,	PUNCT
cana-2991	28	14	tf	tf	PROPN
cana-2991	28	15	-	-	PUNCT
cana-2991	28	16	idf	idf	PROPN
cana-2991	28	17	,	,	PUNCT
cana-2991	28	18	word2vec	word2vec	X
cana-2991	28	19	,	,	PUNCT
cana-2991	28	20	glove	glove	NOUN
cana-2991	28	21	and	and	CCONJ
cana-2991	28	22	bert	bert	PROPN
cana-2991	28	23	are	be	AUX
cana-2991	28	24	created	create	VERB
cana-2991	28	25	for	for	ADP
cana-2991	28	26	improving	improve	VERB
cana-2991	28	27	the	the	DET
cana-2991	28	28	accuracy	accuracy	NOUN
cana-2991	28	29	of	of	ADP
cana-2991	28	30	text	text	NOUN
cana-2991	28	31	classification	classification	NOUN
cana-2991	28	32	tasks	task	NOUN
cana-2991	28	33	.	.	PUNCT
cana-2991	29	1	these	these	DET
cana-2991	29	2	embeddings	embedding	NOUN
cana-2991	29	3	can	can	AUX
cana-2991	29	4	then	then	ADV
cana-2991	29	5	be	be	AUX
cana-2991	29	6	used	use	VERB
cana-2991	29	7	in	in	ADP
cana-2991	29	8	combination	combination	NOUN
cana-2991	29	9	with	with	ADP
cana-2991	29	10	several	several	ADJ
cana-2991	29	11	machine	machine	NOUN
cana-2991	29	12	learning	learn	VERB
cana-2991	29	13	algorithms	algorithm	NOUN
cana-2991	29	14	like	like	ADP
cana-2991	29	15	logistic	logistic	ADJ
cana-2991	29	16	regression	regression	NOUN
cana-2991	29	17	,	,	PUNCT
cana-2991	29	18	random	random	ADJ
cana-2991	29	19	forests	forest	NOUN
cana-2991	29	20	,	,	PUNCT
cana-2991	29	21	neural	neural	ADJ
cana-2991	29	22	networks	network	NOUN
cana-2991	29	23	to	to	PART
cana-2991	29	24	build	build	VERB
cana-2991	29	25	informative	informative	ADJ
cana-2991	29	26	models	model	NOUN
cana-2991	29	27	to	to	PART
cana-2991	29	28	find	find	VERB
cana-2991	29	29	fake	fake	ADJ
cana-2991	29	30	news[2	news[2	NOUN
cana-2991	29	31	-	-	PUNCT
cana-2991	29	32	5	5	NUM
cana-2991	29	33	]	]	PUNCT
cana-2991	29	34	.	.	PUNCT
cana-2991	30	1	one	one	NUM
cana-2991	30	2	of	of	ADP
cana-2991	30	3	the	the	DET
cana-2991	30	4	significant	significant	ADJ
cana-2991	30	5	hurdles	hurdle	NOUN
cana-2991	30	6	faced	face	VERB
cana-2991	30	7	when	when	SCONJ
cana-2991	30	8	researching	research	VERB
cana-2991	30	9	on	on	ADP
cana-2991	30	10	developing	develop	VERB
cana-2991	30	11	automated	automate	VERB
cana-2991	30	12	fake	fake	ADJ
cana-2991	30	13	news	news	NOUN
cana-2991	30	14	detection	detection	NOUN
cana-2991	30	15	systems	system	NOUN
cana-2991	30	16	is	be	AUX
cana-2991	30	17	scalability	scalability	NOUN
cana-2991	30	18	.	.	PUNCT
cana-2991	31	1	because	because	SCONJ
cana-2991	31	2	of	of	ADP
cana-2991	31	3	the	the	DET
cana-2991	31	4	increasing	increase	VERB
cana-2991	31	5	volume	volume	NOUN
cana-2991	31	6	of	of	ADP
cana-2991	31	7	online	online	ADJ
cana-2991	31	8	content	content	NOUN
cana-2991	31	9	that	that	PRON
cana-2991	31	10	we	we	PRON
cana-2991	31	11	are	be	AUX
cana-2991	31	12	facing	face	VERB
cana-2991	31	13	,	,	PUNCT
cana-2991	31	14	fake	fake	ADJ
cana-2991	31	15	news	news	NOUN
cana-2991	31	16	detection	detection	NOUN
cana-2991	31	17	systems	system	NOUN
cana-2991	31	18	have	have	VERB
cana-2991	31	19	to	to	PART
cana-2991	31	20	scale	scale	VERB
cana-2991	31	21	efficiently	efficiently	ADV
cana-2991	31	22	for	for	ADP
cana-2991	31	23	large	large	ADJ
cana-2991	31	24	-	-	PUNCT
cana-2991	31	25	scale	scale	NOUN
cana-2991	31	26	datasets	dataset	NOUN
cana-2991	31	27	.	.	PUNCT
cana-2991	32	1	it	it	PRON
cana-2991	32	2	needs	need	VERB
cana-2991	32	3	powerful	powerful	ADJ
cana-2991	32	4	algorithms	algorithm	NOUN
cana-2991	32	5	in	in	ADP
cana-2991	32	6	place	place	NOUN
cana-2991	32	7	to	to	PART
cana-2991	32	8	make	make	VERB
cana-2991	32	9	this	this	PRON
cana-2991	32	10	a	a	DET
cana-2991	32	11	possibility	possibility	NOUN
cana-2991	32	12	,	,	PUNCT
cana-2991	32	13	and	and	CCONJ
cana-2991	32	14	systems	system	NOUN
cana-2991	32	15	that	that	PRON
cana-2991	32	16	can	can	AUX
cana-2991	32	17	rise	rise	VERB
cana-2991	32	18	up	up	ADP
cana-2991	32	19	to	to	ADP
cana-2991	32	20	the	the	DET
cana-2991	32	21	challenge	challenge	NOUN
cana-2991	32	22	of	of	ADP
cana-2991	32	23	processing	process	VERB
cana-2991	32	24	huge	huge	ADJ
cana-2991	32	25	sums	sum	NOUN
cana-2991	32	26	of	of	ADP
cana-2991	32	27	textual	textual	ADJ
cana-2991	32	28	data	datum	NOUN
cana-2991	32	29	on	on	ADP
cana-2991	32	30	the	the	DET
cana-2991	32	31	fly	fly	NOUN
cana-2991	32	32	.	.	PUNCT
cana-2991	33	1	to	to	PART
cana-2991	33	2	cater	cater	VERB
cana-2991	33	3	for	for	ADP
cana-2991	33	4	such	such	ADJ
cana-2991	33	5	demands	demand	NOUN
cana-2991	33	6	,	,	PUNCT
cana-2991	33	7	distributed	distribute	VERB
cana-2991	33	8	computing	computing	NOUN
cana-2991	33	9	frameworks	framework	NOUN
cana-2991	33	10	like	like	ADP
cana-2991	33	11	apache	apache	NOUN
cana-2991	33	12	spark	spark	NOUN
cana-2991	33	13	and	and	CCONJ
cana-2991	33	14	hadoop	hadoop	NOUN
cana-2991	33	15	are	be	AUX
cana-2991	33	16	widely	widely	ADV
cana-2991	33	17	used	use	VERB
cana-2991	33	18	that	that	PRON
cana-2991	33	19	can	can	AUX
cana-2991	33	20	distribute	distribute	VERB
cana-2991	33	21	the	the	DET
cana-2991	33	22	processing	processing	NOUN
cana-2991	33	23	of	of	ADP
cana-2991	33	24	large	large	ADJ
cana-2991	33	25	datasets	dataset	NOUN
cana-2991	33	26	across	across	ADP
cana-2991	33	27	different	different	ADJ
cana-2991	33	28	machines	machine	NOUN
cana-2991	33	29	.	.	PUNCT
cana-2991	34	1	also	also	ADV
cana-2991	34	2	necessary	necessary	ADJ
cana-2991	34	3	to	to	PART
cana-2991	34	4	be	be	AUX
cana-2991	34	5	scalable	scalable	ADJ
cana-2991	34	6	on	on	ADP
cana-2991	34	7	a	a	DET
cana-2991	34	8	larger	large	ADJ
cana-2991	34	9	dataset	dataset	NOUN
cana-2991	34	10	are	be	AUX
cana-2991	34	11	practices	practice	NOUN
cana-2991	34	12	such	such	ADJ
cana-2991	34	13	as	as	ADP
cana-2991	34	14	batch	batch	NOUN
cana-2991	34	15	processing	processing	NOUN
cana-2991	34	16	and	and	CCONJ
cana-2991	34	17	using	use	VERB
cana-2991	34	18	optimization	optimization	NOUN
cana-2991	34	19	algorithms	algorithm	NOUN
cana-2991	34	20	so	so	SCONJ
cana-2991	34	21	that	that	SCONJ
cana-2991	34	22	the	the	DET
cana-2991	34	23	system	system	NOUN
cana-2991	34	24	is	be	AUX
cana-2991	34	25	effective	effective	ADJ
cana-2991	34	26	just	just	ADV
cana-2991	34	27	with	with	ADP
cana-2991	34	28	its	its	PRON
cana-2991	34	29	fundamental	fundamental	ADJ
cana-2991	34	30	operations[14	operations[14	PROPN
cana-2991	34	31	]	]	PUNCT
cana-2991	34	32	.	.	PUNCT
cana-2991	35	1	language	language	NOUN
cana-2991	35	2	itself	itself	PRON
cana-2991	35	3	is	be	AUX
cana-2991	35	4	abstract	abstract	ADJ
cana-2991	35	5	and	and	CCONJ
cana-2991	35	6	its	its	PRON
cana-2991	35	7	meaning	meaning	NOUN
cana-2991	35	8	differs	differ	VERB
cana-2991	35	9	from	from	ADP
cana-2991	35	10	one	one	NUM
cana-2991	35	11	language	language	NOUN
cana-2991	35	12	to	to	ADP
cana-2991	35	13	another	another	PRON
cana-2991	35	14	.	.	PUNCT
cana-2991	36	1	fake	fake	ADJ
cana-2991	36	2	news	news	NOUN
cana-2991	36	3	articles	article	NOUN
cana-2991	36	4	are	be	AUX
cana-2991	36	5	designed	design	VERB
cana-2991	36	6	to	to	PART
cana-2991	36	7	look	look	VERB
cana-2991	36	8	similar	similar	ADJ
cana-2991	36	9	in	in	ADP
cana-2991	36	10	style	style	NOUN
cana-2991	36	11	and	and	CCONJ
cana-2991	36	12	format	format	NOUN
cana-2991	36	13	as	as	ADP
cana-2991	36	14	real	real	ADJ
cana-2991	36	15	or	or	CCONJ
cana-2991	36	16	truthful	truthful	ADJ
cana-2991	36	17	content	content	NOUN
cana-2991	36	18	,	,	PUNCT
cana-2991	36	19	hence	hence	ADV
cana-2991	36	20	a	a	DET
cana-2991	36	21	user	user	NOUN
cana-2991	36	22	can	can	AUX
cana-2991	36	23	be	be	AUX
cana-2991	36	24	forced	force	VERB
cana-2991	36	25	to	to	PART
cana-2991	36	26	easily	easily	ADV
cana-2991	36	27	fall	fall	VERB
cana-2991	36	28	into	into	ADP
cana-2991	36	29	their	their	PRON
cana-2991	36	30	trap	trap	NOUN
cana-2991	36	31	.	.	PUNCT
cana-2991	37	1	these	these	DET
cana-2991	37	2	events	event	NOUN
cana-2991	37	3	are	be	AUX
cana-2991	37	4	likely	likely	ADJ
cana-2991	37	5	to	to	PART
cana-2991	37	6	include	include	VERB
cana-2991	37	7	some	some	DET
cana-2991	37	8	accurate	accurate	ADJ
cana-2991	37	9	information	information	NOUN
cana-2991	37	10	but	but	CCONJ
cana-2991	37	11	largely	largely	ADV
cana-2991	37	12	they	they	PRON
cana-2991	37	13	may	may	AUX
cana-2991	37	14	be	be	AUX
cana-2991	37	15	inaccurate	inaccurate	ADJ
cana-2991	37	16	by	by	ADP
cana-2991	37	17	the	the	DET
cana-2991	37	18	changing	changing	NOUN
cana-2991	37	19	of	of	ADP
cana-2991	37	20	scene	scene	NOUN
cana-2991	37	21	and	and	CCONJ
cana-2991	37	22	or	or	CCONJ
cana-2991	37	23	a	a	DET
cana-2991	37	24	removal	removal	NOUN
cana-2991	37	25	of	of	ADP
cana-2991	37	26	vital	vital	ADJ
cana-2991	37	27	hints	hint	NOUN
cana-2991	37	28	.	.	PUNCT
cana-2991	38	1	to	to	PART
cana-2991	38	2	establish	establish	VERB
cana-2991	38	3	whether	whether	SCONJ
cana-2991	38	4	something	something	PRON
cana-2991	38	5	is	be	AUX
cana-2991	38	6	fake	fake	ADJ
cana-2991	38	7	news	news	NOUN
cana-2991	38	8	or	or	CCONJ
cana-2991	38	9	not	not	PART
cana-2991	38	10	,	,	PUNCT
cana-2991	38	11	systems	system	NOUN
cana-2991	38	12	for	for	ADP
cana-2991	38	13	identifying	identify	VERB
cana-2991	38	14	fake	fake	ADJ
cana-2991	38	15	news	news	NOUN
cana-2991	38	16	have	have	VERB
cana-2991	38	17	to	to	PART
cana-2991	38	18	go	go	VERB
cana-2991	38	19	beyond	beyond	ADP
cana-2991	38	20	word	word	NOUN
cana-2991	38	21	frequency	frequency	NOUN
cana-2991	38	22	and	and	CCONJ
cana-2991	38	23	take	take	VERB
cana-2991	38	24	into	into	ADP
cana-2991	38	25	account	account	NOUN
cana-2991	38	26	some	some	DET
cana-2991	38	27	more	more	ADV
cana-2991	38	28	subtle	subtle	ADJ
cana-2991	38	29	laws	law	NOUN
cana-2991	38	30	of	of	ADP
cana-2991	38	31	language	language	NOUN
cana-2991	38	32	like	like	ADP
cana-2991	38	33	sentiment	sentiment	NOUN
cana-2991	38	34	,	,	PUNCT
cana-2991	38	35	coherence	coherence	NOUN
cana-2991	38	36	,	,	PUNCT
cana-2991	38	37	relations	relation	NOUN
cana-2991	38	38	between	between	ADP
cana-2991	38	39	words	word	NOUN
cana-2991	38	40	.	.	PUNCT
cana-2991	39	1	this	this	PRON
cana-2991	39	2	is	be	AUX
cana-2991	39	3	where	where	SCONJ
cana-2991	39	4	advanced	advanced	ADJ
cana-2991	39	5	word	word	NOUN
cana-2991	39	6	embedding	embed	VERB
cana-2991	39	7	techniques	technique	NOUN
cana-2991	39	8	such	such	ADJ
cana-2991	39	9	as	as	SCONJ
cana-2991	39	10	bert	bert	PROPN
cana-2991	39	11	become	become	VERB
cana-2991	39	12	important	important	ADJ
cana-2991	39	13	,	,	PUNCT
cana-2991	39	14	since	since	SCONJ
cana-2991	39	15	bert	bert	PROPN
cana-2991	39	16	can	can	AUX
cana-2991	39	17	imbue	imbue	VERB
cana-2991	39	18	the	the	DET
cana-2991	39	19	context	context	NOUN
cana-2991	39	20	with	with	ADP
cana-2991	39	21	meaning	meaning	NOUN
cana-2991	39	22	using	use	VERB
cana-2991	39	23	the	the	DET
cana-2991	39	24	trends	trend	NOUN
cana-2991	39	25	of	of	ADP
cana-2991	39	26	surrounding	surround	VERB
cana-2991	39	27	words	word	NOUN
cana-2991	39	28	in	in	ADP
cana-2991	39	29	a	a	DET
cana-2991	39	30	sentence	sentence	NOUN
cana-2991	39	31	.	.	PUNCT
cana-2991	40	1	communications	communication	NOUN
cana-2991	40	2	on	on	ADP
cana-2991	40	3	applied	apply	VERB
cana-2991	40	4	nonlinear	nonlinear	ADJ
cana-2991	40	5	analysis	analysis	NOUN
cana-2991	40	6	issn	issn	NOUN
cana-2991	40	7	:	:	PUNCT
cana-2991	40	8	1074	1074	NUM
cana-2991	40	9	-	-	PUNCT
cana-2991	40	10	133x	133x	NUM
cana-2991	40	11	vol	vol	NOUN
cana-2991	40	12	32	32	NUM
cana-2991	40	13	no	no	NOUN
cana-2991	40	14	.	.	PUNCT
cana-2991	41	1	5s	5s	NUM
cana-2991	41	2	(	(	PUNCT
cana-2991	41	3	2025	2025	NUM
cana-2991	41	4	)	)	PUNCT
cana-2991	41	5	153	153	NUM
cana-2991	41	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	41	7	figure	figure	NOUN
cana-2991	41	8	1	1	NUM
cana-2991	41	9	.	.	PUNCT
cana-2991	41	10	fake	fake	ADJ
cana-2991	41	11	news	news	NOUN
cana-2991	41	12	on	on	ADP
cana-2991	41	13	social	social	ADJ
cana-2991	41	14	media	medium	NOUN
cana-2991	41	15	:	:	PUNCT
cana-2991	41	16	from	from	ADP
cana-2991	41	17	characterization	characterization	NOUN
cana-2991	41	18	to	to	ADP
cana-2991	41	19	detection[3	detection[3	ADP
cana-2991	41	20	]	]	PUNCT
cana-2991	41	21	using	use	VERB
cana-2991	41	22	figure	figure	NOUN
cana-2991	41	23	1	1	NUM
cana-2991	41	24	,	,	PUNCT
cana-2991	41	25	deep	deep	ADJ
cana-2991	41	26	learning	learning	NOUN
cana-2991	41	27	and	and	CCONJ
cana-2991	41	28	advances	advance	NOUN
cana-2991	41	29	in	in	ADP
cana-2991	41	30	neural	neural	ADJ
cana-2991	41	31	networks	network	NOUN
cana-2991	41	32	have	have	AUX
cana-2991	41	33	strengthened	strengthen	VERB
cana-2991	41	34	nlp	nlp	NOUN
cana-2991	41	35	models	model	NOUN
cana-2991	41	36	to	to	PART
cana-2991	41	37	detect	detect	VERB
cana-2991	41	38	fake	fake	ADJ
cana-2991	41	39	news	news	NOUN
cana-2991	41	40	even	even	ADV
cana-2991	41	41	better	well	ADV
cana-2991	41	42	.	.	PUNCT
cana-2991	42	1	they	they	PRON
cana-2991	42	2	tend	tend	VERB
cana-2991	42	3	to	to	PART
cana-2991	42	4	be	be	AUX
cana-2991	42	5	very	very	ADV
cana-2991	42	6	effective	effective	ADJ
cana-2991	42	7	for	for	ADP
cana-2991	42	8	text	text	NOUN
cana-2991	42	9	classification	classification	NOUN
cana-2991	42	10	when	when	SCONJ
cana-2991	42	11	applied	apply	VERB
cana-2991	42	12	in	in	ADP
cana-2991	42	13	combinations	combination	NOUN
cana-2991	42	14	with	with	ADP
cana-2991	42	15	types	type	NOUN
cana-2991	42	16	of	of	ADP
cana-2991	42	17	models	model	NOUN
cana-2991	42	18	similar	similar	ADJ
cana-2991	42	19	to	to	ADP
cana-2991	42	20	convolutional	convolutional	ADJ
cana-2991	42	21	neural	neural	ADJ
cana-2991	42	22	networks	network	NOUN
cana-2991	42	23	and	and	CCONJ
cana-2991	42	24	long	long	ADJ
cana-2991	42	25	short	short	ADJ
cana-2991	42	26	-	-	PUNCT
cana-2991	42	27	term	term	NOUN
cana-2991	42	28	memory	memory	NOUN
cana-2991	42	29	networks	network	NOUN
cana-2991	42	30	,	,	PUNCT
cana-2991	42	31	like	like	ADP
cana-2991	42	32	both	both	PRON
cana-2991	42	33	cnns	cnns	PROPN
cana-2991	42	34	-	-	PUNCT
cana-2991	42	35	lstm	lstm	PROPN
cana-2991	42	36	and	and	CCONJ
cana-2991	42	37	lstm	lstm	PROPN
cana-2991	42	38	-	-	PUNCT
cana-2991	42	39	cnn	cnn	PROPN
cana-2991	42	40	.	.	PUNCT
cana-2991	43	1	models	model	NOUN
cana-2991	43	2	like	like	ADP
cana-2991	43	3	this	this	PRON
cana-2991	43	4	can	can	AUX
cana-2991	43	5	learn	learn	VERB
cana-2991	43	6	to	to	PART
cana-2991	43	7	recognize	recognize	VERB
cana-2991	43	8	intricate	intricate	ADJ
cana-2991	43	9	patterns	pattern	NOUN
cana-2991	43	10	in	in	ADP
cana-2991	43	11	data	datum	NOUN
cana-2991	43	12	,	,	PUNCT
cana-2991	43	13	even	even	ADV
cana-2991	43	14	those	those	PRON
cana-2991	43	15	spanning	span	VERB
cana-2991	43	16	far	far	ADV
cana-2991	43	17	across	across	ADP
cana-2991	43	18	entire	entire	ADJ
cana-2991	43	19	text	text	NOUN
cana-2991	43	20	examples	example	NOUN
cana-2991	43	21	,	,	PUNCT
cana-2991	43	22	and	and	CCONJ
cana-2991	43	23	are	be	AUX
cana-2991	43	24	thus	thus	ADV
cana-2991	43	25	effective	effective	ADJ
cana-2991	43	26	at	at	ADP
cana-2991	43	27	contextually	contextually	ADV
cana-2991	43	28	-	-	PUNCT
cana-2991	43	29	based	base	VERB
cana-2991	43	30	tasks	task	NOUN
cana-2991	43	31	.	.	PUNCT
cana-2991	44	1	given	give	VERB
cana-2991	44	2	that	that	SCONJ
cana-2991	44	3	it	it	PRON
cana-2991	44	4	is	be	AUX
cana-2991	44	5	based	base	VERB
cana-2991	44	6	on	on	ADP
cana-2991	44	7	a	a	DET
cana-2991	44	8	transformer	transformer	NOUN
cana-2991	44	9	architecture	architecture	NOUN
cana-2991	44	10	,	,	PUNCT
cana-2991	44	11	bert	bert	NOUN
cana-2991	44	12	leverages	leverage	VERB
cana-2991	44	13	its	its	PRON
cana-2991	44	14	huge	huge	ADJ
cana-2991	44	15	popularity	popularity	NOUN
cana-2991	44	16	within	within	ADP
cana-2991	44	17	the	the	DET
cana-2991	44	18	fake	fake	ADJ
cana-2991	44	19	news	news	NOUN
cana-2991	44	20	detection	detection	NOUN
cana-2991	44	21	paradigm	paradigm	NOUN
cana-2991	44	22	by	by	ADP
cana-2991	44	23	being	be	AUX
cana-2991	44	24	capable	capable	ADJ
cana-2991	44	25	of	of	ADP
cana-2991	44	26	dealing	deal	VERB
cana-2991	44	27	with	with	ADP
cana-2991	44	28	sentence	sentence	NOUN
cana-2991	44	29	-	-	PUNCT
cana-2991	44	30	level	level	NOUN
cana-2991	44	31	processing	processing	NOUN
cana-2991	44	32	rather	rather	ADV
cana-2991	44	33	than	than	ADP
cana-2991	44	34	word	word	NOUN
cana-2991	44	35	-	-	PUNCT
cana-2991	44	36	by	by	ADP
cana-2991	44	37	-	-	PUNCT
cana-2991	44	38	word	word	NOUN
cana-2991	44	39	.	.	PUNCT
cana-2991	45	1	response	response	NOUN
cana-2991	45	2	entity	entity	NOUN
cana-2991	45	3	bert	bert	PROPN
cana-2991	45	4	can	can	AUX
cana-2991	45	5	then	then	ADV
cana-2991	45	6	capture	capture	VERB
cana-2991	45	7	bidirectional	bidirectional	ADJ
cana-2991	45	8	context	context	NOUN
cana-2991	45	9	,	,	PUNCT
cana-2991	45	10	which	which	PRON
cana-2991	45	11	essentially	essentially	ADV
cana-2991	45	12	has	have	VERB
cana-2991	45	13	access	access	NOUN
cana-2991	45	14	to	to	ADP
cana-2991	45	15	the	the	DET
cana-2991	45	16	words	word	NOUN
cana-2991	45	17	before	before	ADP
cana-2991	45	18	and	and	CCONJ
cana-2991	45	19	after	after	ADP
cana-2991	45	20	a	a	DET
cana-2991	45	21	target	target	NOUN
cana-2991	45	22	word	word	NOUN
cana-2991	45	23	within	within	ADP
cana-2991	45	24	a	a	DET
cana-2991	45	25	sentence	sentence	NOUN
cana-2991	45	26	.	.	PUNCT
cana-2991	46	1	recent	recent	ADJ
cana-2991	46	2	works	work	NOUN
cana-2991	46	3	employing	employ	VERB
cana-2991	46	4	deep	deep	ADJ
cana-2991	46	5	learning	learning	NOUN
cana-2991	46	6	models	model	NOUN
cana-2991	46	7	enhanced	enhance	VERB
cana-2991	46	8	with	with	ADP
cana-2991	46	9	sophisticated	sophisticated	ADJ
cana-2991	46	10	word	word	NOUN
cana-2991	46	11	embeddings	embedding	NOUN
cana-2991	46	12	have	have	AUX
cana-2991	46	13	boosted	boost	VERB
cana-2991	46	14	the	the	DET
cana-2991	46	15	accuracy	accuracy	NOUN
cana-2991	46	16	in	in	ADP
cana-2991	46	17	identifying	identify	VERB
cana-2991	46	18	fake	fake	ADJ
cana-2991	46	19	news	news	NOUN
cana-2991	46	20	dramatically[15	dramatically[15	NOUN
cana-2991	46	21	-	-	PUNCT
cana-2991	46	22	18	18	NUM
cana-2991	46	23	]	]	PUNCT
cana-2991	46	24	.	.	PUNCT
cana-2991	47	1	finally	finally	ADV
cana-2991	47	2	,	,	PUNCT
cana-2991	47	3	even	even	ADV
cana-2991	47	4	with	with	ADP
cana-2991	47	5	the	the	DET
cana-2991	47	6	strides	stride	NOUN
cana-2991	47	7	made	make	VERB
cana-2991	47	8	in	in	ADP
cana-2991	47	9	this	this	DET
cana-2991	47	10	field	field	NOUN
cana-2991	47	11	,	,	PUNCT
cana-2991	47	12	there	there	PRON
cana-2991	47	13	are	be	VERB
cana-2991	47	14	still	still	ADV
cana-2991	47	15	several	several	ADJ
cana-2991	47	16	open	open	ADJ
cana-2991	47	17	problems	problem	NOUN
cana-2991	47	18	for	for	ADP
cana-2991	47	19	detecting	detect	VERB
cana-2991	47	20	fake	fake	ADJ
cana-2991	47	21	news	news	NOUN
cana-2991	47	22	.	.	PUNCT
cana-2991	48	1	the	the	DET
cana-2991	48	2	most	most	ADV
cana-2991	48	3	imminent	imminent	ADJ
cana-2991	48	4	stress	stress	NOUN
cana-2991	48	5	point	point	NOUN
cana-2991	48	6	,	,	PUNCT
cana-2991	48	7	as	as	SCONJ
cana-2991	48	8	discussed	discuss	VERB
cana-2991	48	9	before	before	ADV
cana-2991	48	10	,	,	PUNCT
cana-2991	48	11	is	be	AUX
cana-2991	48	12	the	the	DET
cana-2991	48	13	trade	trade	NOUN
cana-2991	48	14	off	off	ADP
cana-2991	48	15	between	between	ADP
cana-2991	48	16	model	model	NOUN
cana-2991	48	17	complexity	complexity	NOUN
cana-2991	48	18	and	and	CCONJ
cana-2991	48	19	computational	computational	ADJ
cana-2991	48	20	efficiency	efficiency	NOUN
cana-2991	48	21	.	.	PUNCT
cana-2991	49	1	however	however	ADV
cana-2991	49	2	,	,	PUNCT
cana-2991	49	3	one	one	PRON
cana-2991	49	4	can	can	AUX
cana-2991	49	5	only	only	ADV
cana-2991	49	6	run	run	VERB
cana-2991	49	7	models	model	NOUN
cana-2991	49	8	that	that	PRON
cana-2991	49	9	are	be	AUX
cana-2991	49	10	computationally	computationally	ADV
cana-2991	49	11	expensive	expensive	ADJ
cana-2991	49	12	like	like	ADP
cana-2991	49	13	bert	bert	PROPN
cana-2991	49	14	so	so	ADV
cana-2991	49	15	many	many	ADJ
cana-2991	49	16	times	time	NOUN
cana-2991	49	17	before	before	ADP
cana-2991	49	18	scale	scale	NOUN
cana-2991	49	19	just	just	ADV
cana-2991	49	20	becomes	become	VERB
cana-2991	49	21	an	an	DET
cana-2991	49	22	issue	issue	NOUN
cana-2991	49	23	.	.	PUNCT
cana-2991	50	1	less	less	ADJ
cana-2991	50	2	complex	complex	ADJ
cana-2991	50	3	models	model	NOUN
cana-2991	50	4	like	like	ADP
cana-2991	50	5	logistic	logistic	ADJ
cana-2991	50	6	regression	regression	NOUN
cana-2991	50	7	or	or	CCONJ
cana-2991	50	8	random	random	ADJ
cana-2991	50	9	forests	forest	NOUN
cana-2991	50	10	are	be	AUX
cana-2991	50	11	faster	fast	ADJ
cana-2991	50	12	,	,	PUNCT
cana-2991	50	13	but	but	CCONJ
cana-2991	50	14	their	their	PRON
cana-2991	50	15	performance	performance	NOUN
cana-2991	50	16	on	on	ADP
cana-2991	50	17	the	the	DET
cana-2991	50	18	fake	fake	ADJ
cana-2991	50	19	news	news	NOUN
cana-2991	50	20	task	task	NOUN
cana-2991	50	21	is	be	AUX
cana-2991	50	22	weaker	weak	ADJ
cana-2991	50	23	.	.	PUNCT
cana-2991	51	1	thus	thus	ADV
cana-2991	51	2	,	,	PUNCT
cana-2991	51	3	for	for	ADP
cana-2991	51	4	the	the	DET
cana-2991	51	5	real	real	ADJ
cana-2991	51	6	-	-	PUNCT
cana-2991	51	7	world	world	NOUN
cana-2991	51	8	large	large	ADJ
cana-2991	51	9	-	-	PUNCT
cana-2991	51	10	scale	scale	NOUN
cana-2991	51	11	applications	application	NOUN
cana-2991	51	12	,	,	PUNCT
cana-2991	51	13	it	it	PRON
cana-2991	51	14	is	be	AUX
cana-2991	51	15	crucial	crucial	ADJ
cana-2991	51	16	to	to	PART
cana-2991	51	17	consider	consider	VERB
cana-2991	51	18	these	these	DET
cana-2991	51	19	wise	wise	ADJ
cana-2991	51	20	trade	trade	NOUN
cana-2991	51	21	-	-	PUNCT
cana-2991	51	22	offs	off	NOUN
cana-2991	51	23	while	while	SCONJ
cana-2991	51	24	designing	design	VERB
cana-2991	51	25	the	the	DET
cana-2991	51	26	fake	fake	ADJ
cana-2991	51	27	news	news	NOUN
cana-2991	51	28	detection	detection	NOUN
cana-2991	51	29	systems	system	NOUN
cana-2991	51	30	.	.	PUNCT
cana-2991	52	1	the	the	DET
cana-2991	52	2	performance	performance	NOUN
cana-2991	52	3	of	of	ADP
cana-2991	52	4	fake	fake	ADJ
cana-2991	52	5	news	news	NOUN
cana-2991	52	6	detection	detection	NOUN
cana-2991	52	7	systems	system	NOUN
cana-2991	52	8	is	be	AUX
cana-2991	52	9	highly	highly	ADV
cana-2991	52	10	dependent	dependent	ADJ
cana-2991	52	11	on	on	ADP
cana-2991	52	12	the	the	DET
cana-2991	52	13	quality	quality	NOUN
cana-2991	52	14	and	and	CCONJ
cana-2991	52	15	diversity	diversity	NOUN
cana-2991	52	16	of	of	ADP
cana-2991	52	17	training	training	NOUN
cana-2991	52	18	data	datum	NOUN
cana-2991	52	19	employed	employ	VERB
cana-2991	52	20	for	for	ADP
cana-2991	52	21	their	their	PRON
cana-2991	52	22	design	design	NOUN
cana-2991	52	23	,	,	PUNCT
cana-2991	52	24	besides	besides	SCONJ
cana-2991	52	25	scalability	scalability	NOUN
cana-2991	52	26	and	and	CCONJ
cana-2991	52	27	computational	computational	ADJ
cana-2991	52	28	efficiency	efficiency	NOUN
cana-2991	52	29	.	.	PUNCT
cana-2991	53	1	contextdependent	contextdependent	ADJ
cana-2991	53	2	fake	fake	ADJ
cana-2991	53	3	news	news	NOUN
cana-2991	53	4	:	:	PUNCT
cana-2991	53	5	it	it	PRON
cana-2991	53	6	is	be	AUX
cana-2991	53	7	a	a	DET
cana-2991	53	8	type	type	NOUN
cana-2991	53	9	of	of	ADP
cana-2991	53	10	fake	fake	ADJ
cana-2991	53	11	news	news	NOUN
cana-2991	53	12	specific	specific	ADJ
cana-2991	53	13	to	to	ADP
cana-2991	53	14	the	the	DET
cana-2991	53	15	context	context	NOUN
cana-2991	53	16	,	,	PUNCT
cana-2991	53	17	which	which	PRON
cana-2991	53	18	might	might	AUX
cana-2991	53	19	not	not	PART
cana-2991	53	20	transfer	transfer	VERB
cana-2991	53	21	well	well	ADV
cana-2991	53	22	trained	train	VERB
cana-2991	53	23	on	on	ADP
cana-2991	53	24	one	one	NUM
cana-2991	53	25	dataset	dataset	NOUN
cana-2991	53	26	or	or	CCONJ
cana-2991	53	27	domain	domain	NOUN
cana-2991	53	28	to	to	ADP
cana-2991	53	29	another	another	PRON
cana-2991	53	30	.	.	PUNCT
cana-2991	54	1	e.g.	e.g.	ADV
cana-2991	54	2	,	,	PUNCT
cana-2991	54	3	a	a	DET
cana-2991	54	4	model	model	NOUN
cana-2991	54	5	trained	train	VERB
cana-2991	54	6	on	on	ADP
cana-2991	54	7	political	political	ADJ
cana-2991	54	8	news	news	NOUN
cana-2991	54	9	could	could	AUX
cana-2991	54	10	fail	fail	VERB
cana-2991	54	11	to	to	PART
cana-2991	54	12	classify	classify	VERB
cana-2991	54	13	fake	fake	ADJ
cana-2991	54	14	news	news	NOUN
cana-2991	54	15	in	in	ADP
cana-2991	54	16	other	other	ADJ
cana-2991	54	17	domains	domain	NOUN
cana-2991	54	18	,	,	PUNCT
cana-2991	54	19	e.g.	e.g.	ADV
cana-2991	54	20	,	,	PUNCT
cana-2991	54	21	health	health	NOUN
cana-2991	54	22	or	or	CCONJ
cana-2991	54	23	science	science	NOUN
cana-2991	54	24	.	.	PUNCT
cana-2991	55	1	in	in	ADP
cana-2991	55	2	that	that	DET
cana-2991	55	3	regard	regard	NOUN
cana-2991	55	4	,	,	PUNCT
cana-2991	55	5	it	it	PRON
cana-2991	55	6	is	be	AUX
cana-2991	55	7	necessary	necessary	ADJ
cana-2991	55	8	for	for	SCONJ
cana-2991	55	9	researchers	researcher	NOUN
cana-2991	55	10	to	to	PART
cana-2991	55	11	train	train	VERB
cana-2991	55	12	their	their	PRON
cana-2991	55	13	models	model	NOUN
cana-2991	55	14	on	on	ADP
cana-2991	55	15	different	different	ADJ
cana-2991	55	16	datasets	dataset	NOUN
cana-2991	55	17	covering	cover	VERB
cana-2991	55	18	various	various	ADJ
cana-2991	55	19	topics	topic	NOUN
cana-2991	55	20	and	and	CCONJ
cana-2991	55	21	styles	style	NOUN
cana-2991	55	22	.	.	PUNCT
cana-2991	56	1	secondly	secondly	ADV
cana-2991	56	2	,	,	PUNCT
cana-2991	56	3	the	the	DET
cana-2991	56	4	training	training	NOUN
cana-2991	56	5	data	datum	NOUN
cana-2991	56	6	should	should	AUX
cana-2991	56	7	be	be	AUX
cana-2991	56	8	bias	bias	NOUN
cana-2991	56	9	-	-	PUNCT
cana-2991	56	10	free	free	ADJ
cana-2991	56	11	because	because	SCONJ
cana-2991	56	12	biased	biased	ADJ
cana-2991	56	13	training	training	NOUN
cana-2991	56	14	data	datum	NOUN
cana-2991	56	15	led	lead	VERB
cana-2991	56	16	to	to	ADP
cana-2991	56	17	biased	biased	ADJ
cana-2991	56	18	predictions	prediction	NOUN
cana-2991	56	19	and	and	CCONJ
cana-2991	56	20	consequently	consequently	ADV
cana-2991	56	21	further	far	ADV
cana-2991	56	22	increased	increase	VERB
cana-2991	56	23	the	the	DET
cana-2991	56	24	spread	spread	NOUN
cana-2991	56	25	of	of	ADP
cana-2991	56	26	misinformation[19	misinformation[19	NOUN
cana-2991	56	27	]	]	PUNCT
cana-2991	56	28	.	.	PUNCT
cana-2991	57	1	preprocessing	preprocessing	NOUN
cana-2991	57	2	is	be	AUX
cana-2991	57	3	another	another	DET
cana-2991	57	4	important	important	ADJ
cana-2991	57	5	phase	phase	NOUN
cana-2991	57	6	in	in	ADP
cana-2991	57	7	the	the	DET
cana-2991	57	8	building	building	NOUN
cana-2991	57	9	of	of	ADP
cana-2991	57	10	bogus	bogus	ADJ
cana-2991	57	11	news	news	NOUN
cana-2991	57	12	discovery	discovery	NOUN
cana-2991	57	13	systems	system	NOUN
cana-2991	57	14	.	.	PUNCT
cana-2991	58	1	to	to	PART
cana-2991	58	2	perform	perform	VERB
cana-2991	58	3	natural	natural	ADJ
cana-2991	58	4	language	language	NOUN
cana-2991	58	5	processing	processing	NOUN
cana-2991	58	6	on	on	ADP
cana-2991	58	7	a	a	DET
cana-2991	58	8	dataset	dataset	NOUN
cana-2991	58	9	,	,	PUNCT
cana-2991	58	10	we	we	PRON
cana-2991	58	11	need	need	VERB
cana-2991	58	12	to	to	PART
cana-2991	58	13	first	first	ADV
cana-2991	58	14	clean	clean	VERB
cana-2991	58	15	and	and	CCONJ
cana-2991	58	16	preprocess	preprocess	VERB
cana-2991	58	17	the	the	DET
cana-2991	58	18	raw	raw	ADJ
cana-2991	58	19	text	text	NOUN
cana-2991	58	20	of	of	ADP
cana-2991	58	21	the	the	DET
cana-2991	58	22	text	text	NOUN
cana-2991	58	23	data	datum	NOUN
cana-2991	58	24	as	as	SCONJ
cana-2991	58	25	text	text	NOUN
cana-2991	58	26	can	can	AUX
cana-2991	58	27	not	not	PART
cana-2991	58	28	be	be	AUX
cana-2991	58	29	used	use	VERB
cana-2991	58	30	in	in	ADP
cana-2991	58	31	its	its	PRON
cana-2991	58	32	raw	raw	ADJ
cana-2991	58	33	form	form	NOUN
cana-2991	58	34	by	by	ADP
cana-2991	58	35	any	any	DET
cana-2991	58	36	machine	machine	NOUN
cana-2991	58	37	learning	learn	VERB
cana-2991	58	38	algorithm	algorithm	NOUN
cana-2991	58	39	.	.	PUNCT
cana-2991	59	1	these	these	PRON
cana-2991	59	2	are	be	AUX
cana-2991	59	3	mainly	mainly	ADV
cana-2991	59	4	used	use	VERB
cana-2991	59	5	for	for	ADP
cana-2991	59	6	natural	natural	ADJ
cana-2991	59	7	language	language	NOUN
cana-2991	59	8	processing	processing	NOUN
cana-2991	59	9	tasks	task	NOUN
cana-2991	59	10	like	like	ADP
cana-2991	59	11	tokenization	tokenization	NOUN
cana-2991	59	12	,	,	PUNCT
cana-2991	59	13	stop	stop	VERB
cana-2991	59	14	-	-	PUNCT
cana-2991	59	15	word	word	NOUN
cana-2991	59	16	removal	removal	NOUN
cana-2991	59	17	and	and	CCONJ
cana-2991	59	18	stemming	stemming	NOUN
cana-2991	59	19	or	or	CCONJ
cana-2991	59	20	lemmatization	lemmatization	NOUN
cana-2991	59	21	.	.	PUNCT
cana-2991	60	1	tokenization	tokenization	NOUN
cana-2991	60	2	is	be	AUX
cana-2991	60	3	a	a	DET
cana-2991	60	4	step	step	NOUN
cana-2991	60	5	of	of	ADP
cana-2991	60	6	transforming	transform	VERB
cana-2991	60	7	text	text	NOUN
cana-2991	60	8	into	into	ADP
cana-2991	60	9	words	word	NOUN
cana-2991	60	10	or	or	CCONJ
cana-2991	60	11	tokens	token	NOUN
cana-2991	60	12	where	where	SCONJ
cana-2991	60	13	stop	stop	VERB
cana-2991	60	14	-	-	PUNCT
cana-2991	60	15	word	word	NOUN
cana-2991	60	16	punctuation	punctuation	NOUN
cana-2991	60	17	comes	come	VERB
cana-2991	60	18	such	such	ADJ
cana-2991	60	19	as	as	ADP
cana-2991	60	20	“	"	PUNCT
cana-2991	60	21	the	the	PRON
cana-2991	60	22	”	"	PUNCT
cana-2991	60	23	or	or	CCONJ
cana-2991	60	24	“	"	PUNCT
cana-2991	60	25	and	and	CCONJ
cana-2991	60	26	”	"	PUNCT
cana-2991	60	27	that	that	PRON
cana-2991	60	28	are	be	AUX
cana-2991	60	29	frequently	frequently	ADV
cana-2991	60	30	existing	exist	VERB
cana-2991	60	31	but	but	CCONJ
cana-2991	60	32	do	do	AUX
cana-2991	60	33	not	not	PART
cana-2991	60	34	deliver	deliver	VERB
cana-2991	60	35	any	any	DET
cana-2991	60	36	end	end	NOUN
cana-2991	60	37	purpose	purpose	NOUN
cana-2991	60	38	.	.	PUNCT
cana-2991	61	1	it	it	PRON
cana-2991	61	2	is	be	AUX
cana-2991	61	3	a	a	DET
cana-2991	61	4	method	method	NOUN
cana-2991	61	5	that	that	PRON
cana-2991	61	6	reduces	reduce	VERB
cana-2991	61	7	to	to	ADP
cana-2991	61	8	the	the	DET
cana-2991	61	9	root	root	NOUN
cana-2991	61	10	word	word	NOUN
cana-2991	61	11	,	,	PUNCT
cana-2991	61	12	so	so	SCONJ
cana-2991	61	13	we	we	PRON
cana-2991	61	14	can	can	AUX
cana-2991	61	15	capture	capture	VERB
cana-2991	61	16	the	the	DET
cana-2991	61	17	meaning	meaning	NOUN
cana-2991	61	18	of	of	ADP
cana-2991	61	19	a	a	DET
cana-2991	61	20	text	text	NOUN
cana-2991	61	21	data	datum	NOUN
cana-2991	61	22	.	.	PUNCT
cana-2991	62	1	however	however	ADV
cana-2991	62	2	,	,	PUNCT
cana-2991	62	3	even	even	ADV
cana-2991	62	4	though	though	SCONJ
cana-2991	62	5	preprocessing	preprocessing	NOUN
cana-2991	62	6	is	be	AUX
cana-2991	62	7	necessary	necessary	ADJ
cana-2991	62	8	in	in	ADP
cana-2991	62	9	the	the	DET
cana-2991	62	10	pipeline	pipeline	NOUN
cana-2991	62	11	,	,	PUNCT
cana-2991	62	12	we	we	PRON
cana-2991	62	13	need	need	VERB
cana-2991	62	14	to	to	PART
cana-2991	62	15	face	face	VERB
cana-2991	62	16	some	some	DET
cana-2991	62	17	problems	problem	NOUN
cana-2991	62	18	from	from	ADP
cana-2991	62	19	communications	communication	NOUN
cana-2991	62	20	on	on	ADP
cana-2991	62	21	applied	apply	VERB
cana-2991	62	22	nonlinear	nonlinear	ADJ
cana-2991	62	23	analysis	analysis	NOUN
cana-2991	62	24	issn	issn	NOUN
cana-2991	62	25	:	:	PUNCT
cana-2991	62	26	1074	1074	NUM
cana-2991	62	27	-	-	PUNCT
cana-2991	62	28	133x	133x	NUM
cana-2991	62	29	vol	vol	NOUN
cana-2991	62	30	32	32	NUM
cana-2991	62	31	no	no	NOUN
cana-2991	62	32	.	.	PUNCT
cana-2991	63	1	5s	5s	NUM
cana-2991	63	2	(	(	PUNCT
cana-2991	63	3	2025	2025	NUM
cana-2991	63	4	)	)	PUNCT
cana-2991	63	5	154	154	NUM
cana-2991	63	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	63	7	it	it	PRON
cana-2991	63	8	as	as	ADV
cana-2991	63	9	well	well	ADV
cana-2991	63	10	.	.	PUNCT
cana-2991	64	1	this	this	DET
cana-2991	64	2	inadvertent	inadvertent	ADJ
cana-2991	64	3	removal	removal	NOUN
cana-2991	64	4	of	of	ADP
cana-2991	64	5	useful	useful	ADJ
cana-2991	64	6	phrases	phrase	NOUN
cana-2991	64	7	is	be	AUX
cana-2991	64	8	particularly	particularly	ADV
cana-2991	64	9	salient	salient	ADJ
cana-2991	64	10	when	when	SCONJ
cana-2991	64	11	"	"	PUNCT
cana-2991	64	12	stop	stop	VERB
cana-2991	64	13	-	-	PUNCT
cana-2991	64	14	words	word	NOUN
cana-2991	64	15	"	"	PUNCT
cana-2991	64	16	are	be	AUX
cana-2991	64	17	knocked	knock	VERB
cana-2991	64	18	out	out	ADP
cana-2991	64	19	of	of	ADP
cana-2991	64	20	an	an	DET
cana-2991	64	21	input	input	NOUN
cana-2991	64	22	example	example	NOUN
cana-2991	64	23	(	(	PUNCT
cana-2991	64	24	this	this	PRON
cana-2991	64	25	happens	happen	VERB
cana-2991	64	26	by	by	ADP
cana-2991	64	27	pruning	prune	VERB
cana-2991	64	28	the	the	DET
cana-2991	64	29	vocabulary	vocabulary	NOUN
cana-2991	64	30	,	,	PUNCT
cana-2991	64	31	a	a	DET
cana-2991	64	32	process	process	NOUN
cana-2991	64	33	which	which	PRON
cana-2991	64	34	only	only	ADV
cana-2991	64	35	takes	take	VERB
cana-2991	64	36	into	into	ADP
cana-2991	64	37	account	account	NOUN
cana-2991	64	38	words	word	NOUN
cana-2991	64	39	separate	separate	ADJ
cana-2991	64	40	from	from	ADP
cana-2991	64	41	their	their	PRON
cana-2991	64	42	function	function	NOUN
cana-2991	64	43	words	word	NOUN
cana-2991	64	44	;	;	PUNCT
cana-2991	64	45	these	these	DET
cana-2991	64	46	functional	functional	ADJ
cana-2991	64	47	words	word	NOUN
cana-2991	64	48	are	be	AUX
cana-2991	64	49	often	often	ADV
cana-2991	64	50	cherry	cherry	NOUN
cana-2991	64	51	-	-	PUNCT
cana-2991	64	52	picked	pick	VERB
cana-2991	64	53	to	to	PART
cana-2991	64	54	be	be	AUX
cana-2991	64	55	authoritative	authoritative	ADJ
cana-2991	64	56	markers	marker	NOUN
cana-2991	64	57	of	of	ADP
cana-2991	64	58	whether	whether	SCONJ
cana-2991	64	59	or	or	CCONJ
cana-2991	64	60	not	not	PART
cana-2991	64	61	news	news	NOUN
cana-2991	64	62	articles	article	NOUN
cana-2991	64	63	are	be	AUX
cana-2991	64	64	fake	fake	ADJ
cana-2991	64	65	)	)	PUNCT
cana-2991	64	66	and	and	CCONJ
cana-2991	64	67	mean	mean	VERB
cana-2991	64	68	disabling	disable	VERB
cana-2991	64	69	rows[20	rows[20	NOUN
cana-2991	64	70	]	]	PUNCT
cana-2991	64	71	.	.	PUNCT
cana-2991	65	1	figure	figure	NOUN
cana-2991	65	2	2	2	NUM
cana-2991	65	3	.	.	PUNCT
cana-2991	65	4	estimated	estimate	VERB
cana-2991	65	5	trend	trend	NOUN
cana-2991	65	6	of	of	ADP
cana-2991	65	7	publications	publication	NOUN
cana-2991	65	8	from	from	ADP
cana-2991	65	9	2000	2000	NUM
cana-2991	65	10	to	to	ADP
cana-2991	65	11	2023	2023	NUM
cana-2991	65	12	in	in	ADP
cana-2991	65	13	fake	fake	ADJ
cana-2991	65	14	news	news	NOUN
cana-2991	65	15	detection	detection	NOUN
cana-2991	65	16	and	and	CCONJ
cana-2991	65	17	nlp	nlp	NOUN
cana-2991	65	18	one	one	PRON
cana-2991	65	19	can	can	AUX
cana-2991	65	20	not	not	PART
cana-2991	65	21	deny	deny	VERB
cana-2991	65	22	the	the	DET
cana-2991	65	23	importance	importance	NOUN
cana-2991	65	24	of	of	ADP
cana-2991	65	25	feature	feature	NOUN
cana-2991	65	26	engineering	engineering	NOUN
cana-2991	65	27	in	in	ADP
cana-2991	65	28	fake	fake	ADJ
cana-2991	65	29	news	news	NOUN
cana-2991	65	30	detection	detection	NOUN
cana-2991	65	31	.	.	PUNCT
cana-2991	66	1	feature	feature	NOUN
cana-2991	66	2	engineering	engineering	NOUN
cana-2991	66	3	is	be	AUX
cana-2991	66	4	the	the	DET
cana-2991	66	5	process	process	NOUN
cana-2991	66	6	of	of	ADP
cana-2991	66	7	taking	take	VERB
cana-2991	66	8	raw	raw	ADJ
cana-2991	66	9	data	datum	NOUN
cana-2991	66	10	and	and	CCONJ
cana-2991	66	11	making	make	VERB
cana-2991	66	12	useful	useful	ADJ
cana-2991	66	13	features	feature	NOUN
cana-2991	66	14	out	out	ADP
cana-2991	66	15	of	of	ADP
cana-2991	66	16	them	they	PRON
cana-2991	66	17	,	,	PUNCT
cana-2991	66	18	which	which	PRON
cana-2991	66	19	provides	provide	VERB
cana-2991	66	20	better	well	ADJ
cana-2991	66	21	power	power	NOUN
cana-2991	66	22	to	to	ADP
cana-2991	66	23	machine	machine	NOUN
cana-2991	66	24	learning	learning	NOUN
cana-2991	66	25	models	model	NOUN
cana-2991	66	26	.	.	PUNCT
cana-2991	67	1	using	use	VERB
cana-2991	67	2	figure	figure	NOUN
cana-2991	67	3	2	2	NUM
cana-2991	67	4	,	,	PUNCT
cana-2991	67	5	it	it	PRON
cana-2991	67	6	shows	show	VERB
cana-2991	67	7	that	that	SCONJ
cana-2991	67	8	from	from	ADP
cana-2991	67	9	the	the	DET
cana-2991	67	10	past	past	ADJ
cana-2991	67	11	5	5	NUM
cana-2991	67	12	years	year	NOUN
cana-2991	67	13	the	the	DET
cana-2991	67	14	research	research	NOUN
cana-2991	67	15	on	on	ADP
cana-2991	67	16	this	this	DET
cana-2991	67	17	topic	topic	NOUN
cana-2991	67	18	is	be	AUX
cana-2991	67	19	rapidly	rapidly	ADV
cana-2991	67	20	increasing	increase	VERB
cana-2991	67	21	so	so	ADV
cana-2991	67	22	far	far	ADV
cana-2991	67	23	.	.	PUNCT
cana-2991	68	1	in	in	ADP
cana-2991	68	2	the	the	DET
cana-2991	68	3	case	case	NOUN
cana-2991	68	4	of	of	ADP
cana-2991	68	5	detecting	detect	VERB
cana-2991	68	6	fake	fake	ADJ
cana-2991	68	7	news	news	NOUN
cana-2991	68	8	some	some	DET
cana-2991	68	9	features	feature	NOUN
cana-2991	68	10	could	could	AUX
cana-2991	68	11	be	be	AUX
cana-2991	68	12	how	how	SCONJ
cana-2991	68	13	many	many	ADJ
cana-2991	68	14	times	time	NOUN
cana-2991	68	15	a	a	DET
cana-2991	68	16	word	word	NOUN
cana-2991	68	17	or	or	CCONJ
cana-2991	68	18	phrase	phrase	NOUN
cana-2991	68	19	is	be	AUX
cana-2991	68	20	mentioned	mention	VERB
cana-2991	68	21	,	,	PUNCT
cana-2991	68	22	if	if	SCONJ
cana-2991	68	23	there	there	PRON
cana-2991	68	24	are	be	VERB
cana-2991	68	25	stylistic	stylistic	ADJ
cana-2991	68	26	elements	element	NOUN
cana-2991	68	27	such	such	ADJ
cana-2991	68	28	as	as	ADP
cana-2991	68	29	punctuation	punctuation	NOUN
cana-2991	68	30	or	or	CCONJ
cana-2991	68	31	capitalization	capitalization	NOUN
cana-2991	68	32	and	and	CCONJ
cana-2991	68	33	the	the	DET
cana-2991	68	34	sentiment	sentiment	NOUN
cana-2991	68	35	of	of	ADP
cana-2991	68	36	text	text	NOUN
cana-2991	68	37	.	.	PUNCT
cana-2991	69	1	research	research	NOUN
cana-2991	69	2	in	in	ADP
cana-2991	69	3	recent	recent	ADJ
cana-2991	69	4	years	year	NOUN
cana-2991	69	5	showed	show	VERB
cana-2991	69	6	that	that	SCONJ
cana-2991	69	7	we	we	PRON
cana-2991	69	8	can	can	AUX
cana-2991	69	9	really	really	ADV
cana-2991	69	10	improve	improve	VERB
cana-2991	69	11	fake	fake	ADJ
cana-2991	69	12	news	news	NOUN
cana-2991	69	13	detection	detection	NOUN
cana-2991	69	14	systems	system	NOUN
cana-2991	69	15	accuracy	accuracy	NOUN
cana-2991	69	16	by	by	ADP
cana-2991	69	17	using	use	VERB
cana-2991	69	18	stylistic	stylistic	ADJ
cana-2991	69	19	features	feature	NOUN
cana-2991	69	20	,	,	PUNCT
cana-2991	69	21	which	which	DET
cana-2991	69	22	word	word	NOUN
cana-2991	69	23	embeddings	embedding	VERB
cana-2991	69	24	learn	learn	VERB
cana-2991	69	25	but	but	CCONJ
cana-2991	69	26	probably	probably	ADV
cana-2991	69	27	no	no	ADV
cana-2991	69	28	more	more	ADJ
cana-2991	69	29	(	(	PUNCT
cana-2991	69	30	this	this	PRON
cana-2991	69	31	does	do	AUX
cana-2991	69	32	n't	not	PART
cana-2991	69	33	mean	mean	VERB
cana-2991	69	34	i	i	PRON
cana-2991	69	35	am	be	AUX
cana-2991	69	36	saying	say	VERB
cana-2991	69	37	this	this	PRON
cana-2991	69	38	is	be	AUX
cana-2991	69	39	sufficient	sufficient	ADJ
cana-2991	69	40	,	,	PUNCT
cana-2991	69	41	but	but	CCONJ
cana-2991	69	42	whatever	whatever	PRON
cana-2991	69	43	)	)	PUNCT
cana-2991	69	44	.	.	PUNCT
cana-2991	70	1	a	a	DET
cana-2991	70	2	good	good	ADJ
cana-2991	70	3	example	example	NOUN
cana-2991	70	4	of	of	ADP
cana-2991	70	5	this	this	PRON
cana-2991	70	6	is	be	AUX
cana-2991	70	7	that	that	SCONJ
cana-2991	70	8	many	many	ADJ
cana-2991	70	9	fake	fake	ADJ
cana-2991	70	10	news	news	NOUN
cana-2991	70	11	articles	article	NOUN
cana-2991	70	12	attempt	attempt	VERB
cana-2991	70	13	to	to	PART
cana-2991	70	14	elicit	elicit	VERB
cana-2991	70	15	a	a	DET
cana-2991	70	16	strong	strong	ADJ
cana-2991	70	17	emotion	emotion	NOUN
cana-2991	70	18	from	from	ADP
cana-2991	70	19	their	their	PRON
cana-2991	70	20	readers	reader	NOUN
cana-2991	70	21	by	by	ADP
cana-2991	70	22	using	use	VERB
cana-2991	70	23	overly	overly	ADV
cana-2991	70	24	sensationalized	sensationalize	VERB
cana-2991	70	25	terms	term	NOUN
cana-2991	70	26	or	or	CCONJ
cana-2991	70	27	language	language	NOUN
cana-2991	70	28	.	.	PUNCT
cana-2991	71	1	when	when	SCONJ
cana-2991	71	2	these	these	DET
cana-2991	71	3	stylistic	stylistic	ADJ
cana-2991	71	4	attributes	attribute	NOUN
cana-2991	71	5	are	be	AUX
cana-2991	71	6	combined	combine	VERB
cana-2991	71	7	with	with	ADP
cana-2991	71	8	the	the	DET
cana-2991	71	9	model	model	NOUN
cana-2991	71	10	,	,	PUNCT
cana-2991	71	11	it	it	PRON
cana-2991	71	12	can	can	AUX
cana-2991	71	13	enable	enable	VERB
cana-2991	71	14	researchers	researcher	NOUN
cana-2991	71	15	to	to	PART
cana-2991	71	16	discern	discern	VERB
cana-2991	71	17	more	more	ADV
cana-2991	71	18	effectively	effectively	ADV
cana-2991	71	19	fake	fake	ADJ
cana-2991	71	20	news	news	NOUN
cana-2991	71	21	from	from	ADP
cana-2991	71	22	any	any	DET
cana-2991	71	23	actual	actual	ADJ
cana-2991	71	24	one	one	NUM
cana-2991	71	25	.	.	PUNCT
cana-2991	72	1	evaluation	evaluation	NOUN
cana-2991	72	2	is	be	AUX
cana-2991	72	3	n't	not	PART
cana-2991	72	4	an	an	DET
cana-2991	72	5	afterthought	afterthought	NOUN
cana-2991	72	6	,	,	PUNCT
cana-2991	72	7	though	though	ADV
cana-2991	72	8	;	;	PUNCT
cana-2991	72	9	no	no	DET
cana-2991	72	10	fake	fake	ADJ
cana-2991	72	11	news	news	NOUN
cana-2991	72	12	detection	detection	NOUN
cana-2991	72	13	system	system	NOUN
cana-2991	72	14	can	can	AUX
cana-2991	72	15	fly	fly	VERB
cana-2991	72	16	without	without	ADP
cana-2991	72	17	frequent	frequent	ADJ
cana-2991	72	18	testing	testing	NOUN
cana-2991	72	19	.	.	PUNCT
cana-2991	73	1	when	when	SCONJ
cana-2991	73	2	a	a	DET
cana-2991	73	3	model	model	NOUN
cana-2991	73	4	is	be	AUX
cana-2991	73	5	trained	train	VERB
cana-2991	73	6	,	,	PUNCT
cana-2991	73	7	it	it	PRON
cana-2991	73	8	must	must	AUX
cana-2991	73	9	be	be	AUX
cana-2991	73	10	assessed	assess	VERB
cana-2991	73	11	so	so	SCONJ
cana-2991	73	12	that	that	SCONJ
cana-2991	73	13	an	an	DET
cana-2991	73	14	estimate	estimate	NOUN
cana-2991	73	15	of	of	ADP
cana-2991	73	16	its	its	PRON
cana-2991	73	17	performance	performance	NOUN
cana-2991	73	18	on	on	ADP
cana-2991	73	19	unseen	unseen	ADJ
cana-2991	73	20	data	datum	NOUN
cana-2991	73	21	can	can	AUX
cana-2991	73	22	be	be	AUX
cana-2991	73	23	made	make	VERB
cana-2991	73	24	.	.	PUNCT
cana-2991	74	1	main	main	ADJ
cana-2991	74	2	evaluation	evaluation	NOUN
cana-2991	74	3	metrics	metric	NOUN
cana-2991	74	4	are	be	AUX
cana-2991	74	5	accuracy	accuracy	NOUN
cana-2991	74	6	,	,	PUNCT
cana-2991	74	7	precision	precision	NOUN
cana-2991	74	8	,	,	PUNCT
cana-2991	74	9	recall	recall	NOUN
cana-2991	74	10	,	,	PUNCT
cana-2991	74	11	f1	f1	NOUN
cana-2991	74	12	-	-	PUNCT
cana-2991	74	13	score	score	NOUN
cana-2991	74	14	.	.	PUNCT
cana-2991	75	1	a	a	DET
cana-2991	75	2	way	way	NOUN
cana-2991	75	3	to	to	PART
cana-2991	75	4	quantify	quantify	VERB
cana-2991	75	5	accuracy	accuracy	NOUN
cana-2991	75	6	,	,	PUNCT
cana-2991	75	7	precision	precision	NOUN
cana-2991	75	8	and	and	CCONJ
cana-2991	75	9	recall	recall	NOUN
cana-2991	75	10	seeks	seek	VERB
cana-2991	75	11	to	to	PART
cana-2991	75	12	highlight	highlight	VERB
cana-2991	75	13	how	how	SCONJ
cana-2991	75	14	well	well	ADV
cana-2991	75	15	the	the	DET
cana-2991	75	16	model	model	NOUN
cana-2991	75	17	performs	perform	VERB
cana-2991	75	18	in	in	ADP
cana-2991	75	19	identifying	identify	VERB
cana-2991	75	20	real	real	ADJ
cana-2991	75	21	news	news	NOUN
cana-2991	75	22	versus	versus	ADP
cana-2991	75	23	fake	fake	ADJ
cana-2991	75	24	news	news	NOUN
cana-2991	75	25	.	.	PUNCT
cana-2991	76	1	the	the	DET
cana-2991	76	2	f1	f1	NOUN
cana-2991	76	3	-	-	PUNCT
cana-2991	76	4	score	score	NOUN
cana-2991	76	5	is	be	AUX
cana-2991	76	6	a	a	DET
cana-2991	76	7	combination	combination	NOUN
cana-2991	76	8	of	of	ADP
cana-2991	76	9	precision	precision	NOUN
cana-2991	76	10	and	and	CCONJ
cana-2991	76	11	recall	recall	NOUN
cana-2991	76	12	,	,	PUNCT
cana-2991	76	13	which	which	PRON
cana-2991	76	14	gives	give	VERB
cana-2991	76	15	us	we	PRON
cana-2991	76	16	a	a	DET
cana-2991	76	17	balanced	balanced	ADJ
cana-2991	76	18	model	model	NOUN
cana-2991	76	19	on	on	ADP
cana-2991	76	20	the	the	DET
cana-2991	76	21	basis	basis	NOUN
cana-2991	76	22	of	of	ADP
cana-2991	76	23	its	its	PRON
cana-2991	76	24	performance	performance	NOUN
cana-2991	76	25	.	.	PUNCT
cana-2991	77	1	also	also	ADV
cana-2991	77	2	,	,	PUNCT
cana-2991	77	3	these	these	DET
cana-2991	77	4	measures	measure	NOUN
cana-2991	77	5	of	of	ADP
cana-2991	77	6	success	success	NOUN
cana-2991	77	7	are	be	AUX
cana-2991	77	8	just	just	ADV
cana-2991	77	9	a	a	DET
cana-2991	77	10	few	few	ADJ
cana-2991	77	11	of	of	ADP
cana-2991	77	12	the	the	DET
cana-2991	77	13	standard	standard	ADJ
cana-2991	77	14	ones	one	NOUN
cana-2991	77	15	the	the	DET
cana-2991	77	16	system	system	NOUN
cana-2991	77	17	has	have	VERB
cana-2991	77	18	to	to	PART
cana-2991	77	19	be	be	AUX
cana-2991	77	20	reliable	reliable	ADJ
cana-2991	77	21	and	and	CCONJ
cana-2991	77	22	generalizable	generalizable	ADJ
cana-2991	77	23	as	as	ADV
cana-2991	77	24	well	well	ADV
cana-2991	77	25	.	.	PUNCT
cana-2991	78	1	a	a	DET
cana-2991	78	2	well	well	ADV
cana-2991	78	3	-	-	PUNCT
cana-2991	78	4	performing	perform	VERB
cana-2991	78	5	model	model	NOUN
cana-2991	78	6	in	in	ADP
cana-2991	78	7	one	one	NUM
cana-2991	78	8	specific	specific	ADJ
cana-2991	78	9	dataset	dataset	NOUN
cana-2991	78	10	might	might	AUX
cana-2991	78	11	not	not	PART
cana-2991	78	12	be	be	AUX
cana-2991	78	13	sufficient	sufficient	ADJ
cana-2991	78	14	to	to	PART
cana-2991	78	15	perform	perform	VERB
cana-2991	78	16	as	as	ADV
cana-2991	78	17	well	well	ADV
cana-2991	78	18	in	in	ADP
cana-2991	78	19	many	many	ADJ
cana-2991	78	20	other	other	ADJ
cana-2991	78	21	contexts	contexts	NOUN
cana-2991	78	22	,	,	PUNCT
cana-2991	78	23	so	so	ADV
cana-2991	78	24	evaluating	evaluate	VERB
cana-2991	78	25	the	the	DET
cana-2991	78	26	model	model	NOUN
cana-2991	78	27	on	on	ADP
cana-2991	78	28	multiple	multiple	ADJ
cana-2991	78	29	datasets	dataset	NOUN
cana-2991	78	30	is	be	AUX
cana-2991	78	31	critical	critical	ADJ
cana-2991	78	32	to	to	PART
cana-2991	78	33	warrant	warrant	VERB
cana-2991	78	34	reliability	reliability	NOUN
cana-2991	78	35	.	.	PUNCT
cana-2991	79	1	in	in	ADP
cana-2991	79	2	this	this	DET
cana-2991	79	3	paper	paper	NOUN
cana-2991	79	4	,	,	PUNCT
cana-2991	79	5	we	we	PRON
cana-2991	79	6	target	target	VERB
cana-2991	79	7	scalable	scalable	ADJ
cana-2991	79	8	fake	fake	ADJ
cana-2991	79	9	news	news	NOUN
cana-2991	79	10	detection	detection	NOUN
cana-2991	79	11	systems	system	NOUN
cana-2991	79	12	by	by	ADP
cana-2991	79	13	using	use	VERB
cana-2991	79	14	nlp	nlp	ADJ
cana-2991	79	15	tools	tool	NOUN
cana-2991	79	16	with	with	ADP
cana-2991	79	17	advanced	advanced	ADJ
cana-2991	79	18	word	word	NOUN
cana-2991	79	19	embedding	embed	VERB
cana-2991	79	20	models	model	NOUN
cana-2991	79	21	for	for	ADP
cana-2991	79	22	large	large	ADJ
cana-2991	79	23	volumes	volume	NOUN
cana-2991	79	24	of	of	ADP
cana-2991	79	25	data	data	PROPN
cana-2991	79	26	.	.	PUNCT
cana-2991	80	1	the	the	DET
cana-2991	80	2	embedding	embed	VERB
cana-2991	80	3	techniques	technique	NOUN
cana-2991	80	4	we	we	PRON
cana-2991	80	5	will	will	AUX
cana-2991	80	6	discuss	discuss	VERB
cana-2991	80	7	are	be	AUX
cana-2991	80	8	bag	bag	NOUN
cana-2991	80	9	of	of	ADP
cana-2991	80	10	words	word	NOUN
cana-2991	80	11	,	,	PUNCT
cana-2991	80	12	tf	tf	PROPN
cana-2991	80	13	-	-	PUNCT
cana-2991	80	14	idf	idf	PROPN
cana-2991	80	15	,	,	PUNCT
cana-2991	80	16	word2vec	word2vec	X
cana-2991	80	17	,	,	PUNCT
cana-2991	80	18	glove	glove	NOUN
cana-2991	80	19	and	and	CCONJ
cana-2991	80	20	bert	bert	NOUN
cana-2991	80	21	which	which	PRON
cana-2991	80	22	can	can	AUX
cana-2991	80	23	be	be	AUX
cana-2991	80	24	attached	attach	VERB
cana-2991	80	25	to	to	ADP
cana-2991	80	26	machine	machine	NOUN
cana-2991	80	27	learning	learn	VERB
cana-2991	80	28	classifiers	classifier	NOUN
cana-2991	80	29	like	like	ADP
cana-2991	80	30	logistic	logistic	ADJ
cana-2991	80	31	regression	regression	NOUN
cana-2991	80	32	,	,	PUNCT
cana-2991	80	33	random	random	ADJ
cana-2991	80	34	forests	forest	NOUN
cana-2991	80	35	or	or	CCONJ
cana-2991	80	36	neural	neural	ADJ
cana-2991	80	37	networks	network	NOUN
cana-2991	80	38	.	.	PUNCT
cana-2991	81	1	this	this	DET
cana-2991	81	2	system	system	NOUN
cana-2991	81	3	has	have	AUX
cana-2991	81	4	been	be	AUX
cana-2991	81	5	designed	design	VERB
cana-2991	81	6	to	to	PART
cana-2991	81	7	scale	scale	VERB
cana-2991	81	8	thanks	thank	NOUN
cana-2991	81	9	to	to	ADP
cana-2991	81	10	the	the	DET
cana-2991	81	11	use	use	NOUN
cana-2991	81	12	of	of	ADP
cana-2991	81	13	distributed	distributed	ADJ
cana-2991	81	14	computing	computing	NOUN
cana-2991	81	15	,	,	PUNCT
cana-2991	81	16	and	and	CCONJ
cana-2991	81	17	optimization	optimization	NOUN
cana-2991	81	18	techniques	technique	NOUN
cana-2991	81	19	in	in	ADP
cana-2991	81	20	order	order	NOUN
cana-2991	81	21	to	to	PART
cana-2991	81	22	process	process	VERB
cana-2991	81	23	massive	massive	ADJ
cana-2991	81	24	amounts	amount	NOUN
cana-2991	81	25	of	of	ADP
cana-2991	81	26	data	datum	NOUN
cana-2991	81	27	.	.	PUNCT
cana-2991	82	1	the	the	DET
cana-2991	82	2	performance	performance	NOUN
cana-2991	82	3	of	of	ADP
cana-2991	82	4	the	the	DET
cana-2991	82	5	system	system	NOUN
cana-2991	82	6	is	be	AUX
cana-2991	82	7	evaluated	evaluate	VERB
cana-2991	82	8	using	use	VERB
cana-2991	82	9	benchmark	benchmark	NOUN
cana-2991	82	10	fake	fake	ADJ
cana-2991	82	11	news	news	NOUN
cana-2991	82	12	datasets	dataset	NOUN
cana-2991	82	13	communications	communication	NOUN
cana-2991	82	14	on	on	ADP
cana-2991	82	15	applied	apply	VERB
cana-2991	82	16	nonlinear	nonlinear	ADJ
cana-2991	82	17	analysis	analysis	NOUN
cana-2991	82	18	issn	issn	NOUN
cana-2991	82	19	:	:	PUNCT
cana-2991	82	20	1074	1074	NUM
cana-2991	82	21	-	-	PUNCT
cana-2991	82	22	133x	133x	NUM
cana-2991	82	23	vol	vol	NOUN
cana-2991	82	24	32	32	NUM
cana-2991	82	25	no	no	NOUN
cana-2991	82	26	.	.	PUNCT
cana-2991	83	1	5s	5s	NUM
cana-2991	83	2	(	(	PUNCT
cana-2991	83	3	2025	2025	NUM
cana-2991	83	4	)	)	PUNCT
cana-2991	83	5	155	155	NUM
cana-2991	83	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	83	7	(	(	PUNCT
cana-2991	83	8	politifact	politifact	NOUN
cana-2991	83	9	and	and	CCONJ
cana-2991	83	10	liar	liar	NOUN
cana-2991	83	11	)	)	PUNCT
cana-2991	83	12	on	on	ADP
cana-2991	83	13	metrics	metric	NOUN
cana-2991	83	14	like	like	ADP
cana-2991	83	15	embedding	embed	VERB
cana-2991	83	16	category	category	NOUN
cana-2991	83	17	,	,	PUNCT
cana-2991	83	18	factorization	factorization	NOUN
cana-2991	83	19	method	method	NOUN
cana-2991	83	20	used	use	VERB
cana-2991	83	21	for	for	ADP
cana-2991	83	22	cardinality	cardinality	NOUN
cana-2991	83	23	reduction	reduction	NOUN
cana-2991	83	24	and	and	CCONJ
cana-2991	83	25	gates	gate	VERB
cana-2991	83	26	classification	classification	NOUN
cana-2991	83	27	accuracy	accuracy	NOUN
cana-2991	83	28	.	.	PUNCT
cana-2991	84	1	the	the	DET
cana-2991	84	2	results	result	NOUN
cana-2991	84	3	show	show	VERB
cana-2991	84	4	that	that	SCONJ
cana-2991	84	5	learnable	learnable	ADJ
cana-2991	84	6	embeddings	embedding	NOUN
cana-2991	84	7	such	such	ADJ
cana-2991	84	8	as	as	ADP
cana-2991	84	9	bert	bert	PROPN
cana-2991	84	10	are	be	AUX
cana-2991	84	11	more	more	ADV
cana-2991	84	12	accurate	accurate	ADJ
cana-2991	84	13	compared	compare	VERB
cana-2991	84	14	to	to	ADP
cana-2991	84	15	static	static	ADJ
cana-2991	84	16	embeddings	embedding	NOUN
cana-2991	84	17	in	in	ADP
cana-2991	84	18	classifying	classify	VERB
cana-2991	84	19	fake	fake	ADJ
cana-2991	84	20	news	news	NOUN
cana-2991	84	21	,	,	PUNCT
cana-2991	84	22	and	and	CCONJ
cana-2991	84	23	at	at	ADP
cana-2991	84	24	the	the	DET
cana-2991	84	25	same	same	ADJ
cana-2991	84	26	time	time	NOUN
cana-2991	84	27	suggest	suggest	VERB
cana-2991	84	28	the	the	DET
cana-2991	84	29	need	need	NOUN
cana-2991	84	30	for	for	ADP
cana-2991	84	31	a	a	DET
cana-2991	84	32	balance	balance	NOUN
cana-2991	84	33	between	between	ADP
cana-2991	84	34	model	model	NOUN
cana-2991	84	35	complexity	complexity	NOUN
cana-2991	84	36	and	and	CCONJ
cana-2991	84	37	computational	computational	ADJ
cana-2991	84	38	efficiency	efficiency	NOUN
cana-2991	84	39	in	in	ADP
cana-2991	84	40	practical	practical	ADJ
cana-2991	84	41	applications[21	applications[21	NOUN
cana-2991	84	42	-	-	SYM
cana-2991	84	43	28	28	NUM
cana-2991	84	44	]	]	PUNCT
cana-2991	84	45	.	.	PUNCT
cana-2991	85	1	overall	overall	ADV
cana-2991	85	2	,	,	PUNCT
cana-2991	85	3	the	the	DET
cana-2991	85	4	task	task	NOUN
cana-2991	85	5	of	of	ADP
cana-2991	85	6	detecting	detect	VERB
cana-2991	85	7	fake	fake	ADJ
cana-2991	85	8	news	news	NOUN
cana-2991	85	9	is	be	AUX
cana-2991	85	10	intricate	intricate	ADJ
cana-2991	85	11	and	and	CCONJ
cana-2991	85	12	multifaceted	multifaceted	ADJ
cana-2991	85	13	and	and	CCONJ
cana-2991	85	14	undoubtedly	undoubtedly	ADV
cana-2991	85	15	falls	fall	VERB
cana-2991	85	16	into	into	ADP
cana-2991	85	17	the	the	DET
cana-2991	85	18	domain	domain	NOUN
cana-2991	85	19	of	of	ADP
cana-2991	85	20	sophisticated	sophisticated	ADJ
cana-2991	85	21	tools	tool	NOUN
cana-2991	85	22	originating	originate	VERB
cana-2991	85	23	in	in	ADP
cana-2991	85	24	nlp	nlp	NOUN
cana-2991	85	25	,	,	PUNCT
cana-2991	85	26	machine	machine	NOUN
cana-2991	85	27	learning	learning	NOUN
cana-2991	85	28	,	,	PUNCT
cana-2991	85	29	and	and	CCONJ
cana-2991	85	30	data	datum	NOUN
cana-2991	85	31	science	science	NOUN
cana-2991	85	32	.	.	PUNCT
cana-2991	86	1	building	build	VERB
cana-2991	86	2	scalable	scalable	ADJ
cana-2991	86	3	systems	system	NOUN
cana-2991	86	4	for	for	ADP
cana-2991	86	5	fake	fake	ADJ
cana-2991	86	6	news	news	NOUN
cana-2991	86	7	classification	classification	NOUN
cana-2991	86	8	that	that	PRON
cana-2991	86	9	can	can	AUX
cana-2991	86	10	work	work	VERB
cana-2991	86	11	with	with	ADP
cana-2991	86	12	growing	grow	VERB
cana-2991	86	13	data	datum	NOUN
cana-2991	86	14	volumes	volume	NOUN
cana-2991	86	15	will	will	AUX
cana-2991	86	16	help	help	VERB
cana-2991	86	17	to	to	PART
cana-2991	86	18	identify	identify	VERB
cana-2991	86	19	and	and	CCONJ
cana-2991	86	20	address	address	VERB
cana-2991	86	21	the	the	DET
cana-2991	86	22	problem	problem	NOUN
cana-2991	86	23	of	of	ADP
cana-2991	86	24	misinformation	misinformation	NOUN
cana-2991	86	25	born	bear	VERB
cana-2991	86	26	in	in	ADP
cana-2991	86	27	the	the	DET
cana-2991	86	28	modern	modern	ADJ
cana-2991	86	29	age	age	NOUN
cana-2991	86	30	of	of	ADP
cana-2991	86	31	the	the	DET
cana-2991	86	32	internet	internet	NOUN
cana-2991	86	33	.	.	PUNCT
cana-2991	87	1	however	however	ADV
cana-2991	87	2	,	,	PUNCT
cana-2991	87	3	the	the	DET
cana-2991	87	4	current	current	ADJ
cana-2991	87	5	paper	paper	NOUN
cana-2991	87	6	aims	aim	VERB
cana-2991	87	7	to	to	PART
cana-2991	87	8	provide	provide	VERB
cana-2991	87	9	a	a	DET
cana-2991	87	10	practical	practical	ADJ
cana-2991	87	11	and	and	CCONJ
cana-2991	87	12	high	high	ADJ
cana-2991	87	13	-	-	PUNCT
cana-2991	87	14	performance	performance	NOUN
cana-2991	87	15	solution	solution	NOUN
cana-2991	87	16	for	for	ADP
cana-2991	87	17	this	this	DET
cana-2991	87	18	task	task	NOUN
cana-2991	87	19	,	,	PUNCT
cana-2991	87	20	which	which	PRON
cana-2991	87	21	fits	fit	VERB
cana-2991	87	22	the	the	DET
cana-2991	87	23	current	current	ADJ
cana-2991	87	24	environment	environment	NOUN
cana-2991	87	25	.	.	PUNCT
cana-2991	88	1	thus	thus	ADV
cana-2991	88	2	,	,	PUNCT
cana-2991	88	3	it	it	PRON
cana-2991	88	4	can	can	AUX
cana-2991	88	5	be	be	AUX
cana-2991	88	6	said	say	VERB
cana-2991	88	7	that	that	SCONJ
cana-2991	88	8	the	the	DET
cana-2991	88	9	work	work	NOUN
cana-2991	88	10	in	in	ADP
cana-2991	88	11	this	this	DET
cana-2991	88	12	document	document	NOUN
cana-2991	88	13	is	be	AUX
cana-2991	88	14	relevant	relevant	ADJ
cana-2991	88	15	to	to	ADP
cana-2991	88	16	the	the	DET
cana-2991	88	17	current	current	ADJ
cana-2991	88	18	research	research	NOUN
cana-2991	88	19	in	in	ADP
cana-2991	88	20	the	the	DET
cana-2991	88	21	field	field	NOUN
cana-2991	88	22	since	since	SCONJ
cana-2991	88	23	it	it	PRON
cana-2991	88	24	provides	provide	VERB
cana-2991	88	25	a	a	DET
cana-2991	88	26	crucial	crucial	ADJ
cana-2991	88	27	tool	tool	NOUN
cana-2991	88	28	to	to	PART
cana-2991	88	29	counteract	counteract	VERB
cana-2991	88	30	the	the	DET
cana-2991	88	31	fake	fake	ADJ
cana-2991	88	32	news	news	NOUN
cana-2991	88	33	.	.	PUNCT
cana-2991	89	1	1	1	X
cana-2991	89	2	.	.	X
cana-2991	89	3	related	relate	VERB
cana-2991	89	4	work	work	NOUN
cana-2991	89	5	fake	fake	ADJ
cana-2991	89	6	news	news	NOUN
cana-2991	89	7	,	,	PUNCT
cana-2991	89	8	in	in	ADP
cana-2991	89	9	particular	particular	ADJ
cana-2991	89	10	,	,	PUNCT
cana-2991	89	11	has	have	AUX
cana-2991	89	12	been	be	AUX
cana-2991	89	13	a	a	DET
cana-2991	89	14	focus	focus	NOUN
cana-2991	89	15	of	of	ADP
cana-2991	89	16	much	much	ADJ
cana-2991	89	17	research	research	NOUN
cana-2991	89	18	in	in	ADP
cana-2991	89	19	recent	recent	ADJ
cana-2991	89	20	years	year	NOUN
cana-2991	89	21	;	;	PUNCT
cana-2991	89	22	given	give	VERB
cana-2991	89	23	the	the	DET
cana-2991	89	24	rise	rise	NOUN
cana-2991	89	25	of	of	ADP
cana-2991	89	26	misinformation	misinformation	NOUN
cana-2991	89	27	fuelled	fuel	VERB
cana-2991	89	28	by	by	ADP
cana-2991	89	29	growing	grow	VERB
cana-2991	89	30	social	social	ADJ
cana-2991	89	31	media	medium	NOUN
cana-2991	89	32	platforms	platform	NOUN
cana-2991	89	33	which	which	PRON
cana-2991	89	34	facilitate	facilitate	VERB
cana-2991	89	35	rapid	rapid	ADJ
cana-2991	89	36	information	information	NOUN
cana-2991	89	37	distribution	distribution	NOUN
cana-2991	89	38	.	.	PUNCT
cana-2991	90	1	but	but	CCONJ
cana-2991	90	2	it	it	PRON
cana-2991	90	3	also	also	ADV
cana-2991	90	4	comes	come	VERB
cana-2991	90	5	because	because	SCONJ
cana-2991	90	6	of	of	ADP
cana-2991	90	7	increasing	increase	VERB
cana-2991	90	8	societal	societal	ADJ
cana-2991	90	9	imperatives	imperative	NOUN
cana-2991	90	10	to	to	PART
cana-2991	90	11	solve	solve	VERB
cana-2991	90	12	the	the	DET
cana-2991	90	13	challenge	challenge	NOUN
cana-2991	90	14	of	of	ADP
cana-2991	90	15	fake	fake	ADJ
cana-2991	90	16	news	news	NOUN
cana-2991	90	17	detection	detection	NOUN
cana-2991	90	18	at	at	ADP
cana-2991	90	19	scale	scale	NOUN
cana-2991	90	20	.	.	PUNCT
cana-2991	91	1	in	in	ADP
cana-2991	91	2	that	that	DET
cana-2991	91	3	context	context	NOUN
cana-2991	91	4	,	,	PUNCT
cana-2991	91	5	several	several	ADJ
cana-2991	91	6	research	research	NOUN
cana-2991	91	7	studies	study	NOUN
cana-2991	91	8	have	have	AUX
cana-2991	91	9	tried	try	VERB
cana-2991	91	10	to	to	PART
cana-2991	91	11	use	use	VERB
cana-2991	91	12	nlp	nlp	ADJ
cana-2991	91	13	techniques	technique	NOUN
cana-2991	91	14	and	and	CCONJ
cana-2991	91	15	machine	machine	NOUN
cana-2991	91	16	learning	learn	VERB
cana-2991	91	17	algorithms	algorithm	NOUN
cana-2991	91	18	in	in	ADP
cana-2991	91	19	order	order	NOUN
cana-2991	91	20	to	to	PART
cana-2991	91	21	detect	detect	VERB
cana-2991	91	22	it	it	PRON
cana-2991	91	23	.	.	PUNCT
cana-2991	92	1	the	the	DET
cana-2991	92	2	remainder	remainder	NOUN
cana-2991	92	3	of	of	ADP
cana-2991	92	4	the	the	DET
cana-2991	92	5	introduction	introduction	NOUN
cana-2991	92	6	section	section	NOUN
cana-2991	92	7	will	will	AUX
cana-2991	92	8	include	include	VERB
cana-2991	92	9	previous	previous	ADJ
cana-2991	92	10	studies	study	NOUN
cana-2991	92	11	that	that	PRON
cana-2991	92	12	have	have	AUX
cana-2991	92	13	conducted	conduct	VERB
cana-2991	92	14	research	research	NOUN
cana-2991	92	15	on	on	ADP
cana-2991	92	16	fake	fake	ADJ
cana-2991	92	17	news	news	NOUN
cana-2991	92	18	detection	detection	NOUN
cana-2991	92	19	and	and	CCONJ
cana-2991	92	20	its	its	PRON
cana-2991	92	21	advantages	advantage	NOUN
cana-2991	92	22	and	and	CCONJ
cana-2991	92	23	disadvantages	disadvantage	NOUN
cana-2991	92	24	regarding	regard	VERB
cana-2991	92	25	the	the	DET
cana-2991	92	26	current	current	ADJ
cana-2991	92	27	study	study	NOUN
cana-2991	92	28	.	.	PUNCT
cana-2991	93	1	foundation	foundation	NOUN
cana-2991	93	2	of	of	ADP
cana-2991	93	3	detection	detection	NOUN
cana-2991	93	4	of	of	ADP
cana-2991	93	5	fake	fake	ADJ
cana-2991	93	6	news	news	NOUN
cana-2991	93	7	:	:	PUNCT
cana-2991	93	8	early	early	ADJ
cana-2991	93	9	work	work	NOUN
cana-2991	93	10	project	project	NOUN
cana-2991	93	11	devoted	devote	VERB
cana-2991	93	12	to	to	ADP
cana-2991	93	13	the	the	DET
cana-2991	93	14	detection	detection	NOUN
cana-2991	93	15	of	of	ADP
cana-2991	93	16	fake	fake	ADJ
cana-2991	93	17	news	news	NOUN
cana-2991	93	18	initially	initially	ADV
cana-2991	93	19	relied	rely	VERB
cana-2991	93	20	on	on	ADP
cana-2991	93	21	statistical	statistical	ADJ
cana-2991	93	22	methods	method	NOUN
cana-2991	93	23	and	and	CCONJ
cana-2991	93	24	rule	rule	NOUN
cana-2991	93	25	-	-	PUNCT
cana-2991	93	26	based	base	VERB
cana-2991	93	27	systems	system	NOUN
cana-2991	93	28	that	that	PRON
cana-2991	93	29	leveraged	leveraged	ADJ
cana-2991	93	30	domain	domain	NOUN
cana-2991	93	31	-	-	PUNCT
cana-2991	93	32	specific	specific	ADJ
cana-2991	93	33	stylistic	stylistic	ADJ
cana-2991	93	34	and	and	CCONJ
cana-2991	93	35	syntactic	syntactic	ADJ
cana-2991	93	36	characteristics	characteristic	NOUN
cana-2991	93	37	of	of	ADP
cana-2991	93	38	news	news	NOUN
cana-2991	93	39	articles	article	NOUN
cana-2991	93	40	.	.	PUNCT
cana-2991	94	1	research	research	NOUN
cana-2991	94	2	from	from	ADP
cana-2991	94	3	potthast	potthast	NOUN
cana-2991	94	4	et	et	PROPN
cana-2991	94	5	al	al	PROPN
cana-2991	94	6	.	.	PROPN
cana-2991	95	1	(	(	PUNCT
cana-2991	95	2	2017	2017	NUM
cana-2991	95	3	)	)	PUNCT
cana-2991	95	4	and	and	CCONJ
cana-2991	95	5	ahmed	ahme	VERB
cana-2991	95	6	et	et	PROPN
cana-2991	95	7	al.[29	al.[29	PROPN
cana-2991	95	8	]	]	PUNCT
cana-2991	95	9	in	in	ADP
cana-2991	95	10	(	(	PUNCT
cana-2991	95	11	2018	2018	NUM
cana-2991	95	12	)	)	PUNCT
cana-2991	95	13	,	,	PUNCT
cana-2991	95	14	a	a	DET
cana-2991	95	15	stylistic	stylistic	NOUN
cana-2991	95	16	-	-	PUNCT
cana-2991	95	17	based	base	VERB
cana-2991	95	18	method	method	NOUN
cana-2991	95	19	for	for	ADP
cana-2991	95	20	fake	fake	ADJ
cana-2991	95	21	news	news	NOUN
cana-2991	95	22	detection	detection	NOUN
cana-2991	95	23	which	which	PRON
cana-2991	95	24	it	it	PRON
cana-2991	95	25	identifies	identify	VERB
cana-2991	95	26	according	accord	VERB
cana-2991	95	27	to	to	ADP
cana-2991	95	28	lexical	lexical	ADJ
cana-2991	95	29	features	feature	NOUN
cana-2991	95	30	,	,	PUNCT
cana-2991	95	31	such	such	ADJ
cana-2991	95	32	as	as	ADP
cana-2991	95	33	part	part	NOUN
cana-2991	95	34	-	-	PUNCT
cana-2991	95	35	of	of	ADP
cana-2991	95	36	-	-	PUNCT
cana-2991	95	37	speech	speech	NOUN
cana-2991	95	38	tags	tag	NOUN
cana-2991	95	39	,	,	PUNCT
cana-2991	95	40	sentence	sentence	NOUN
cana-2991	95	41	structure	structure	NOUN
cana-2991	95	42	and	and	CCONJ
cana-2991	95	43	frequency	frequency	NOUN
cana-2991	95	44	of	of	ADP
cana-2991	95	45	certain	certain	ADJ
cana-2991	95	46	words	word	NOUN
cana-2991	95	47	.	.	PUNCT
cana-2991	96	1	early	early	ADJ
cana-2991	96	2	models	model	NOUN
cana-2991	96	3	trained	train	VERB
cana-2991	96	4	on	on	ADP
cana-2991	96	5	these	these	DET
cana-2991	96	6	features	feature	NOUN
cana-2991	96	7	distinguish	distinguish	VERB
cana-2991	96	8	news	news	NOUN
cana-2991	96	9	based	base	VERB
cana-2991	96	10	on	on	ADP
cana-2991	96	11	the	the	DET
cana-2991	96	12	way	way	NOUN
cana-2991	96	13	it	it	PRON
cana-2991	96	14	is	be	AUX
cana-2991	96	15	written	write	VERB
cana-2991	96	16	,	,	PUNCT
cana-2991	96	17	rather	rather	ADV
cana-2991	96	18	than	than	ADP
cana-2991	96	19	its	its	PRON
cana-2991	96	20	content	content	NOUN
cana-2991	96	21	making	make	VERB
cana-2991	96	22	them	they	PRON
cana-2991	96	23	good	good	ADJ
cana-2991	96	24	at	at	ADP
cana-2991	96	25	identifying	identify	VERB
cana-2991	96	26	some	some	DET
cana-2991	96	27	kinds	kind	NOUN
cana-2991	96	28	of	of	ADP
cana-2991	96	29	fake	fake	ADJ
cana-2991	96	30	news	news	NOUN
cana-2991	96	31	,	,	PUNCT
cana-2991	96	32	but	but	CCONJ
cana-2991	96	33	poor	poor	ADJ
cana-2991	96	34	at	at	ADP
cana-2991	96	35	scaled	scale	VERB
cana-2991	96	36	data	data	NOUN
cana-2991	96	37	processing	processing	NOUN
cana-2991	96	38	and	and	CCONJ
cana-2991	96	39	generalization	generalization	NOUN
cana-2991	96	40	to	to	PART
cana-2991	96	41	diverse	diverse	VERB
cana-2991	96	42	news	news	NOUN
cana-2991	96	43	topics	topic	NOUN
cana-2991	96	44	.	.	PUNCT
cana-2991	97	1	moreover	moreover	ADV
cana-2991	97	2	,	,	PUNCT
cana-2991	97	3	we	we	PRON
cana-2991	97	4	detail	detail	VERB
cana-2991	97	5	knowledge	knowledge	NOUN
cana-2991	97	6	-	-	PUNCT
cana-2991	97	7	based	base	VERB
cana-2991	97	8	ones	one	NOUN
cana-2991	97	9	which	which	PRON
cana-2991	97	10	seek	seek	VERB
cana-2991	97	11	to	to	PART
cana-2991	97	12	analyze	analyze	VERB
cana-2991	97	13	third	third	ADJ
cana-2991	97	14	-	-	PUNCT
cana-2991	97	15	party	party	NOUN
cana-2991	97	16	information	information	NOUN
cana-2991	97	17	resources	resource	NOUN
cana-2991	97	18	that	that	PRON
cana-2991	97	19	serve	serve	VERB
cana-2991	97	20	as	as	ADP
cana-2991	97	21	the	the	DET
cana-2991	97	22	ground	ground	NOUN
cana-2991	97	23	with	with	ADP
cana-2991	97	24	which	which	PRON
cana-2991	97	25	new	new	ADJ
cana-2991	97	26	content	content	NOUN
cana-2991	97	27	is	be	AUX
cana-2991	97	28	verified	verify	VERB
cana-2991	97	29	.	.	PUNCT
cana-2991	98	1	shu	shu	PROPN
cana-2991	98	2	et	et	PROPN
cana-2991	98	3	al	al	PROPN
cana-2991	98	4	.	.	PROPN
cana-2991	98	5	crowd	crowd	NOUN
cana-2991	98	6	-	-	PUNCT
cana-2991	98	7	sourcing	sourcing	NOUN
cana-2991	98	8	&	&	CCONJ
cana-2991	98	9	domain	domain	NOUN
cana-2991	98	10	expertise	expertise	NOUN
cana-2991	98	11	-	-	PUNCT
cana-2991	98	12	dependent	dependent	ADJ
cana-2991	98	13	approaches	approach	VERB
cana-2991	98	14	holtz	holtz	PROPN
cana-2991	98	15	et	et	PROPN
cana-2991	98	16	al.[30	al.[30	PROPN
cana-2991	98	17	]	]	X
cana-2991	98	18	(	(	PUNCT
cana-2991	98	19	2017	2017	NUM
cana-2991	98	20	)	)	PUNCT
cana-2991	98	21	conducted	conduct	VERB
cana-2991	98	22	a	a	DET
cana-2991	98	23	systematic	systematic	ADJ
cana-2991	98	24	review	review	NOUN
cana-2991	98	25	of	of	ADP
cana-2991	98	26	methods	method	NOUN
cana-2991	98	27	using	use	VERB
cana-2991	98	28	crowd	crowd	NOUN
cana-2991	98	29	-	-	PUNCT
cana-2991	98	30	sourced	source	VERB
cana-2991	98	31	verification	verification	NOUN
cana-2991	98	32	and	and	CCONJ
cana-2991	98	33	leveraging	leverage	VERB
cana-2991	98	34	domain	domain	NOUN
cana-2991	98	35	expert	expert	NOUN
cana-2991	98	36	familiarity	familiarity	NOUN
cana-2991	98	37	with	with	ADP
cana-2991	98	38	the	the	DET
cana-2991	98	39	issue	issue	NOUN
cana-2991	98	40	.	.	PUNCT
cana-2991	99	1	unfortunately	unfortunately	ADV
cana-2991	99	2	,	,	PUNCT
cana-2991	99	3	manual	manual	ADJ
cana-2991	99	4	approaches	approach	NOUN
cana-2991	99	5	are	be	AUX
cana-2991	99	6	not	not	PART
cana-2991	99	7	scalable	scalable	ADJ
cana-2991	99	8	,	,	PUNCT
cana-2991	99	9	and	and	CCONJ
cana-2991	99	10	large	large	ADJ
cana-2991	99	11	datasets	dataset	NOUN
cana-2991	99	12	requiring	require	VERB
cana-2991	99	13	intervention	intervention	NOUN
cana-2991	99	14	quickly	quickly	ADV
cana-2991	99	15	become	become	VERB
cana-2991	99	16	cumbersome	cumbersome	ADJ
cana-2991	99	17	to	to	PART
cana-2991	99	18	manage	manage	VERB
cana-2991	99	19	.	.	PUNCT
cana-2991	100	1	the	the	DET
cana-2991	100	2	next	next	ADJ
cana-2991	100	3	step	step	NOUN
cana-2991	100	4	of	of	ADP
cana-2991	100	5	these	these	DET
cana-2991	100	6	scalability	scalability	NOUN
cana-2991	100	7	issues	issue	NOUN
cana-2991	100	8	was	be	AUX
cana-2991	100	9	the	the	DET
cana-2991	100	10	move	move	NOUN
cana-2991	100	11	towards	towards	ADP
cana-2991	100	12	machine	machine	NOUN
cana-2991	100	13	learning	learning	NOUN
cana-2991	100	14	models	model	NOUN
cana-2991	100	15	.	.	PUNCT
cana-2991	101	1	word	word	NOUN
cana-2991	101	2	embeddings	embedding	NOUN
cana-2991	101	3	with	with	ADP
cana-2991	101	4	nlp	nlp	NOUN
cana-2991	101	5	approach	approach	NOUN
cana-2991	101	6	a	a	DET
cana-2991	101	7	significant	significant	ADJ
cana-2991	101	8	step	step	NOUN
cana-2991	101	9	towards	towards	ADP
cana-2991	101	10	fake	fake	ADJ
cana-2991	101	11	news	news	NOUN
cana-2991	101	12	recognition	recognition	NOUN
cana-2991	101	13	nowadays	nowadays	ADV
cana-2991	101	14	is	be	AUX
cana-2991	101	15	that	that	PRON
cana-2991	101	16	nlp	nlp	NOUN
cana-2991	101	17	and	and	CCONJ
cana-2991	101	18	word	word	NOUN
cana-2991	101	19	embedding	embed	VERB
cana-2991	101	20	techniques	technique	NOUN
cana-2991	101	21	are	be	AUX
cana-2991	101	22	being	be	AUX
cana-2991	101	23	applied	apply	VERB
cana-2991	101	24	to	to	PART
cana-2991	101	25	turn	turn	VERB
cana-2991	101	26	the	the	DET
cana-2991	101	27	textual	textual	ADJ
cana-2991	101	28	data	datum	NOUN
cana-2991	101	29	into	into	ADP
cana-2991	101	30	a	a	DET
cana-2991	101	31	numeric	numeric	ADJ
cana-2991	101	32	representation	representation	NOUN
cana-2991	101	33	so	so	SCONJ
cana-2991	101	34	that	that	SCONJ
cana-2991	101	35	it	it	PRON
cana-2991	101	36	can	can	AUX
cana-2991	101	37	be	be	AUX
cana-2991	101	38	processed	process	VERB
cana-2991	101	39	by	by	ADP
cana-2991	101	40	machine	machine	NOUN
cana-2991	101	41	learning	learning	NOUN
cana-2991	101	42	models	model	NOUN
cana-2991	101	43	.	.	PUNCT
cana-2991	102	1	in	in	ADP
cana-2991	102	2	the	the	DET
cana-2991	102	3	fake	fake	ADJ
cana-2991	102	4	news	news	NOUN
cana-2991	102	5	detection	detection	NOUN
cana-2991	102	6	tasks	task	NOUN
cana-2991	102	7	,	,	PUNCT
cana-2991	102	8	some	some	DET
cana-2991	102	9	traditional	traditional	ADJ
cana-2991	102	10	embedding	embed	VERB
cana-2991	102	11	communications	communication	NOUN
cana-2991	102	12	on	on	ADP
cana-2991	102	13	applied	apply	VERB
cana-2991	102	14	nonlinear	nonlinear	ADJ
cana-2991	102	15	analysis	analysis	NOUN
cana-2991	102	16	issn	issn	NOUN
cana-2991	102	17	:	:	PUNCT
cana-2991	102	18	1074	1074	NUM
cana-2991	102	19	-	-	PUNCT
cana-2991	102	20	133x	133x	NUM
cana-2991	102	21	vol	vol	NOUN
cana-2991	102	22	32	32	NUM
cana-2991	102	23	no	no	NOUN
cana-2991	102	24	.	.	PUNCT
cana-2991	103	1	5s	5s	NUM
cana-2991	103	2	(	(	PUNCT
cana-2991	103	3	2025	2025	NUM
cana-2991	103	4	)	)	PUNCT
cana-2991	103	5	156	156	NUM
cana-2991	103	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	103	7	methods	method	NOUN
cana-2991	103	8	like	like	ADP
cana-2991	103	9	bag	bag	NOUN
cana-2991	103	10	of	of	ADP
cana-2991	103	11	words	word	NOUN
cana-2991	103	12	and	and	CCONJ
cana-2991	103	13	term	term	NOUN
cana-2991	103	14	frequency	frequency	NOUN
cana-2991	103	15	-	-	PUNCT
cana-2991	103	16	inverse	inverse	NOUN
cana-2991	103	17	document	document	NOUN
cana-2991	103	18	frequency	frequency	NOUN
cana-2991	103	19	have	have	AUX
cana-2991	103	20	been	be	AUX
cana-2991	103	21	frequently	frequently	ADV
cana-2991	103	22	adopted	adopt	VERB
cana-2991	103	23	to	to	PART
cana-2991	103	24	represent	represent	VERB
cana-2991	103	25	textual	textual	ADJ
cana-2991	103	26	information	information	NOUN
cana-2991	103	27	.	.	PUNCT
cana-2991	104	1	for	for	ADP
cana-2991	104	2	example	example	NOUN
cana-2991	104	3	,	,	PUNCT
cana-2991	104	4	hauschild	hauschild	NOUN
cana-2991	104	5	and	and	CCONJ
cana-2991	104	6	eskridge	eskridge	NOUN
cana-2991	104	7	(	(	PUNCT
cana-2991	104	8	2024	2024	NUM
cana-2991	104	9	)	)	PUNCT
cana-2991	104	10	applied	apply	VERB
cana-2991	104	11	the	the	DET
cana-2991	104	12	bow	bow	NOUN
cana-2991	104	13	model	model	NOUN
cana-2991	104	14	as	as	ADV
cana-2991	104	15	well	well	ADV
cana-2991	104	16	as	as	ADP
cana-2991	104	17	the	the	DET
cana-2991	104	18	tf	tf	PROPN
cana-2991	104	19	-	-	PUNCT
cana-2991	104	20	idf	idf	PROPN
cana-2991	104	21	one	one	NOUN
cana-2991	104	22	to	to	PART
cana-2991	104	23	portray	portray	VERB
cana-2991	104	24	fake	fake	ADJ
cana-2991	104	25	news	news	NOUN
cana-2991	104	26	over	over	ADP
cana-2991	104	27	politically	politically	ADV
cana-2991	104	28	fact	fact	NOUN
cana-2991	104	29	checked	check	VERB
cana-2991	104	30	politifact	politifact	PROPN
cana-2991	104	31	and	and	CCONJ
cana-2991	104	32	liar	liar	NOUN
cana-2991	104	33	datasets	dataset	NOUN
cana-2991	104	34	.	.	PUNCT
cana-2991	105	1	bow	bow	NOUN
cana-2991	105	2	assumes	assume	VERB
cana-2991	105	3	words	word	NOUN
cana-2991	105	4	are	be	AUX
cana-2991	105	5	independent	independent	ADJ
cana-2991	105	6	of	of	ADP
cana-2991	105	7	one	one	NUM
cana-2991	105	8	another	another	DET
cana-2991	105	9	,	,	PUNCT
cana-2991	105	10	and	and	CCONJ
cana-2991	105	11	tf	tf	PROPN
cana-2991	105	12	-	-	PUNCT
cana-2991	105	13	idf	idf	PROPN
cana-2991	105	14	weights	weight	VERB
cana-2991	105	15	words	word	NOUN
cana-2991	105	16	based	base	VERB
cana-2991	105	17	on	on	ADP
cana-2991	105	18	their	their	PRON
cana-2991	105	19	frequency	frequency	NOUN
cana-2991	105	20	across	across	ADP
cana-2991	105	21	documents	document	NOUN
cana-2991	105	22	which	which	PRON
cana-2991	105	23	is	be	AUX
cana-2991	105	24	helpful	helpful	ADJ
cana-2991	105	25	to	to	PART
cana-2991	105	26	identify	identify	VERB
cana-2991	105	27	rare	rare	ADJ
cana-2991	105	28	but	but	CCONJ
cana-2991	105	29	meaningful	meaningful	ADJ
cana-2991	105	30	terms	term	NOUN
cana-2991	105	31	in	in	ADP
cana-2991	105	32	fake	fake	ADJ
cana-2991	105	33	news	news	NOUN
cana-2991	105	34	.	.	PUNCT
cana-2991	106	1	although	although	SCONJ
cana-2991	106	2	,	,	PUNCT
cana-2991	106	3	word	word	NOUN
cana-2991	106	4	level	level	NOUN
cana-2991	106	5	models	model	NOUN
cana-2991	106	6	have	have	VERB
cana-2991	106	7	limitations	limitation	NOUN
cana-2991	106	8	in	in	ADP
cana-2991	106	9	terms	term	NOUN
cana-2991	106	10	of	of	ADP
cana-2991	106	11	word	word	NOUN
cana-2991	106	12	independence	independence	NOUN
cana-2991	106	13	and	and	CCONJ
cana-2991	106	14	lack	lack	NOUN
cana-2991	106	15	of	of	ADP
cana-2991	106	16	awareness	awareness	NOUN
cana-2991	106	17	about	about	ADP
cana-2991	106	18	the	the	DET
cana-2991	106	19	context	context	NOUN
cana-2991	106	20	.	.	PUNCT
cana-2991	107	1	to	to	PART
cana-2991	107	2	fix	fix	VERB
cana-2991	107	3	this	this	DET
cana-2991	107	4	,	,	PUNCT
cana-2991	107	5	more	more	ADV
cana-2991	107	6	advanced	advanced	ADJ
cana-2991	107	7	embedding	embed	VERB
cana-2991	107	8	models	model	NOUN
cana-2991	107	9	including	include	VERB
cana-2991	107	10	word2vec	word2vec	X
cana-2991	107	11	and	and	CCONJ
cana-2991	107	12	global	global	ADJ
cana-2991	107	13	vectors	vector	NOUN
cana-2991	107	14	for	for	ADP
cana-2991	107	15	word	word	NOUN
cana-2991	107	16	representation	representation	NOUN
cana-2991	107	17	(	(	PUNCT
cana-2991	107	18	glove	glove	NOUN
cana-2991	107	19	)	)	PUNCT
cana-2991	107	20	were	be	AUX
cana-2991	107	21	developed	develop	VERB
cana-2991	107	22	.	.	PUNCT
cana-2991	108	1	word2vec	word2vec	X
cana-2991	108	2	employs	employ	VERB
cana-2991	108	3	a	a	DET
cana-2991	108	4	dense	dense	ADJ
cana-2991	108	5	,	,	PUNCT
cana-2991	108	6	lowdimensional	lowdimensional	ADJ
cana-2991	108	7	neural	neural	ADJ
cana-2991	108	8	networks	network	NOUN
cana-2991	108	9	that	that	PRON
cana-2991	108	10	captures	capture	VERB
cana-2991	108	11	the	the	DET
cana-2991	108	12	context	context	NOUN
cana-2991	108	13	of	of	ADP
cana-2991	108	14	words	word	NOUN
cana-2991	108	15	,	,	PUNCT
cana-2991	108	16	by	by	ADP
cana-2991	108	17	predicting	predict	VERB
cana-2991	108	18	the	the	DET
cana-2991	108	19	likelihood	likelihood	NOUN
cana-2991	108	20	of	of	ADP
cana-2991	108	21	a	a	DET
cana-2991	108	22	word	word	NOUN
cana-2991	108	23	appearing	appear	VERB
cana-2991	108	24	in	in	ADP
cana-2991	108	25	a	a	DET
cana-2991	108	26	sentence	sentence	NOUN
cana-2991	108	27	given	give	VERB
cana-2991	108	28	its	its	PRON
cana-2991	108	29	surrounding	surround	VERB
cana-2991	108	30	words	word	NOUN
cana-2991	108	31	(	(	PUNCT
cana-2991	108	32	skip	skip	NOUN
cana-2991	108	33	-	-	PUNCT
cana-2991	108	34	gram	gram	NOUN
cana-2991	108	35	)	)	PUNCT
cana-2991	108	36	or	or	CCONJ
cana-2991	108	37	how	how	SCONJ
cana-2991	108	38	likely	likely	ADJ
cana-2991	108	39	similar	similar	ADJ
cana-2991	108	40	words	word	NOUN
cana-2991	108	41	are	be	AUX
cana-2991	108	42	to	to	PART
cana-2991	108	43	appear	appear	VERB
cana-2991	108	44	around	around	ADP
cana-2991	108	45	it	it	PRON
cana-2991	108	46	.	.	PUNCT
cana-2991	109	1	it	it	PRON
cana-2991	109	2	also	also	ADV
cana-2991	109	3	models	model	VERB
cana-2991	109	4	the	the	DET
cana-2991	109	5	local	local	ADJ
cana-2991	109	6	and	and	CCONJ
cana-2991	109	7	global	global	ADJ
cana-2991	109	8	word	word	NOUN
cana-2991	109	9	co	co	NOUN
cana-2991	109	10	-	-	NOUN
cana-2991	109	11	occurrences	occurrence	NOUN
cana-2991	109	12	by	by	ADP
cana-2991	109	13	glove	glove	NOUN
cana-2991	109	14	in	in	ADP
cana-2991	109	15	a	a	DET
cana-2991	109	16	corpus	corpus	NOUN
cana-2991	109	17	,	,	PUNCT
cana-2991	109	18	which	which	PRON
cana-2991	109	19	can	can	AUX
cana-2991	109	20	help	help	VERB
cana-2991	109	21	to	to	PART
cana-2991	109	22	judge	judge	VERB
cana-2991	109	23	whether	whether	SCONJ
cana-2991	109	24	news	news	NOUN
cana-2991	109	25	is	be	AUX
cana-2991	109	26	real	real	ADJ
cana-2991	109	27	or	or	CCONJ
cana-2991	109	28	false	false	ADJ
cana-2991	109	29	through	through	ADP
cana-2991	109	30	its	its	PRON
cana-2991	109	31	context[31	context[31	NOUN
cana-2991	109	32	-	-	PUNCT
cana-2991	109	33	37	37	NUM
cana-2991	109	34	]	]	PUNCT
cana-2991	109	35	.	.	PUNCT
cana-2991	110	1	truică	truică	NOUN
cana-2991	110	2	and	and	CCONJ
cana-2991	110	3	apostol	apostol	NOUN
cana-2991	110	4	(	(	PUNCT
cana-2991	110	5	2023	2023	NUM
cana-2991	110	6	)	)	PUNCT
cana-2991	110	7	have	have	AUX
cana-2991	110	8	used	use	VERB
cana-2991	110	9	document	document	NOUN
cana-2991	110	10	embeddings	embedding	NOUN
cana-2991	110	11	of	of	ADP
cana-2991	110	12	word2vec	word2vec	PRON
cana-2991	110	13	and	and	CCONJ
cana-2991	110	14	glove	glove	NOUN
cana-2991	110	15	models	model	NOUN
cana-2991	110	16	to	to	PART
cana-2991	110	17	recognize	recognize	VERB
cana-2991	110	18	fake	fake	ADJ
cana-2991	110	19	news	news	NOUN
cana-2991	110	20	and	and	CCONJ
cana-2991	110	21	have	have	AUX
cana-2991	110	22	shown	show	VERB
cana-2991	110	23	a	a	DET
cana-2991	110	24	better	well	ADJ
cana-2991	110	25	output	output	NOUN
cana-2991	110	26	when	when	SCONJ
cana-2991	110	27	compared	compare	VERB
cana-2991	110	28	with	with	ADP
cana-2991	110	29	classical	classical	ADJ
cana-2991	110	30	models	model	NOUN
cana-2991	110	31	[	[	X
cana-2991	110	32	12	12	NUM
cana-2991	110	33	]	]	PUNCT
cana-2991	110	34	.	.	PUNCT
cana-2991	111	1	those	those	DET
cana-2991	111	2	embeddings	embedding	NOUN
cana-2991	111	3	were	be	AUX
cana-2991	111	4	particularly	particularly	ADV
cana-2991	111	5	good	good	ADJ
cana-2991	111	6	at	at	ADP
cana-2991	111	7	learning	learn	VERB
cana-2991	111	8	subtle	subtle	ADJ
cana-2991	111	9	semantics	semantic	NOUN
cana-2991	111	10	:	:	PUNCT
cana-2991	111	11	the	the	DET
cana-2991	111	12	detailed	detailed	ADJ
cana-2991	111	13	meanings	meaning	NOUN
cana-2991	111	14	of	of	ADP
cana-2991	111	15	words	word	NOUN
cana-2991	111	16	and	and	CCONJ
cana-2991	111	17	phrases	phrase	NOUN
cana-2991	111	18	that	that	PRON
cana-2991	111	19	are	be	AUX
cana-2991	111	20	often	often	ADV
cana-2991	111	21	crucial	crucial	ADJ
cana-2991	111	22	for	for	ADP
cana-2991	111	23	identifying	identify	VERB
cana-2991	111	24	fake	fake	ADJ
cana-2991	111	25	news	news	NOUN
cana-2991	111	26	.	.	PUNCT
cana-2991	112	1	deep	deep	ADJ
cana-2991	112	2	learning	learning	NOUN
cana-2991	112	3	models	model	NOUN
cana-2991	112	4	in	in	ADP
cana-2991	112	5	addition	addition	NOUN
cana-2991	112	6	,	,	PUNCT
cana-2991	112	7	the	the	DET
cana-2991	112	8	introduction	introduction	NOUN
cana-2991	112	9	of	of	ADP
cana-2991	112	10	deep	deep	ADJ
cana-2991	112	11	learning	learning	NOUN
cana-2991	112	12	methods	method	NOUN
cana-2991	112	13	,	,	PUNCT
cana-2991	112	14	especially	especially	ADV
cana-2991	112	15	bidirectional	bidirectional	ADJ
cana-2991	112	16	encoder	encoder	NOUN
cana-2991	112	17	representations	representation	VERB
cana-2991	112	18	from	from	ADP
cana-2991	112	19	transformers	transformer	NOUN
cana-2991	112	20	(	(	PUNCT
cana-2991	112	21	bert	bert	PROPN
cana-2991	112	22	)	)	PUNCT
cana-2991	112	23	,	,	PUNCT
cana-2991	112	24	greatly	greatly	ADV
cana-2991	112	25	helps	help	VERB
cana-2991	112	26	solve	solve	VERB
cana-2991	112	27	the	the	DET
cana-2991	112	28	problem	problem	NOUN
cana-2991	112	29	of	of	ADP
cana-2991	112	30	fake	fake	ADJ
cana-2991	112	31	news	news	NOUN
cana-2991	112	32	detection	detection	NOUN
cana-2991	112	33	.	.	PUNCT
cana-2991	113	1	although	although	SCONJ
cana-2991	113	2	bert	bert	PROPN
cana-2991	113	3	can	can	AUX
cana-2991	113	4	analyze	analyze	VERB
cana-2991	113	5	the	the	DET
cana-2991	113	6	context	context	NOUN
cana-2991	113	7	to	to	ADP
cana-2991	113	8	the	the	DET
cana-2991	113	9	left	left	NOUN
cana-2991	113	10	and	and	CCONJ
cana-2991	113	11	the	the	DET
cana-2991	113	12	right	right	NOUN
cana-2991	113	13	of	of	ADP
cana-2991	113	14	a	a	DET
cana-2991	113	15	word	word	NOUN
cana-2991	113	16	in	in	ADP
cana-2991	113	17	a	a	DET
cana-2991	113	18	sentence	sentence	NOUN
cana-2991	113	19	(	(	PUNCT
cana-2991	113	20	bidirectional	bidirectional	NOUN
cana-2991	113	21	)	)	PUNCT
cana-2991	113	22	,	,	PUNCT
cana-2991	113	23	this	this	DET
cana-2991	113	24	quality	quality	NOUN
cana-2991	113	25	makes	make	VERB
cana-2991	113	26	it	it	PRON
cana-2991	113	27	well	well	ADV
cana-2991	113	28	-	-	PUNCT
cana-2991	113	29	suited	suit	VERB
cana-2991	113	30	for	for	ADP
cana-2991	113	31	identifying	identify	VERB
cana-2991	113	32	nuanced	nuanced	ADJ
cana-2991	113	33	differences	difference	NOUN
cana-2991	113	34	in	in	ADP
cana-2991	113	35	how	how	SCONJ
cana-2991	113	36	fake	fake	ADJ
cana-2991	113	37	news	news	NOUN
cana-2991	113	38	is	be	AUX
cana-2991	113	39	written	write	VERB
cana-2991	113	40	vs.	vs.	ADP
cana-2991	113	41	real	real	ADJ
cana-2991	113	42	news	news	NOUN
cana-2991	113	43	.	.	PUNCT
cana-2991	114	1	using	use	VERB
cana-2991	114	2	pre	pre	ADJ
cana-2991	114	3	-	-	ADJ
cana-2991	114	4	trained	train	VERB
cana-2991	114	5	embeddings	embedding	NOUN
cana-2991	114	6	from	from	ADP
cana-2991	114	7	large	large	ADJ
cana-2991	114	8	corpora	corpora	NOUN
cana-2991	114	9	like	like	ADP
cana-2991	114	10	wikipedia	wikipedia	PROPN
cana-2991	114	11	and	and	CCONJ
cana-2991	114	12	books	book	NOUN
cana-2991	114	13	,	,	PUNCT
cana-2991	114	14	models	model	NOUN
cana-2991	114	15	built	build	VERB
cana-2991	114	16	on	on	ADP
cana-2991	114	17	bert	bert	PROPN
cana-2991	114	18	outperformed	outperform	VERB
cana-2991	114	19	existing	exist	VERB
cana-2991	114	20	methods	method	NOUN
cana-2991	114	21	w.r.t	w.r.t	VERB
cana-2991	114	22	accuracy	accuracy	NOUN
cana-2991	114	23	and	and	CCONJ
cana-2991	114	24	recall	recall	NOUN
cana-2991	114	25	.	.	PUNCT
cana-2991	115	1	kaliyar	kaliyar	PROPN
cana-2991	115	2	et	et	PROPN
cana-2991	115	3	al	al	PROPN
cana-2991	115	4	.	.	PROPN
cana-2991	116	1	(	(	PUNCT
cana-2991	116	2	2020	2020	NUM
cana-2991	116	3	)	)	PUNCT
cana-2991	116	4	introduced	introduce	VERB
cana-2991	116	5	fakebert	fakebert	NOUN
cana-2991	116	6	,	,	PUNCT
cana-2991	116	7	a	a	DET
cana-2991	116	8	system	system	NOUN
cana-2991	116	9	for	for	ADP
cana-2991	116	10	fake	fake	ADJ
cana-2991	116	11	news	news	NOUN
cana-2991	116	12	detection	detection	NOUN
cana-2991	116	13	built	build	VERB
cana-2991	116	14	on	on	ADP
cana-2991	116	15	top	top	NOUN
cana-2991	116	16	of	of	ADP
cana-2991	116	17	bert	bert	NOUN
cana-2991	116	18	,	,	PUNCT
cana-2991	116	19	by	by	ADP
cana-2991	116	20	adding	add	VERB
cana-2991	116	21	extra	extra	ADJ
cana-2991	116	22	layers	layer	NOUN
cana-2991	116	23	in	in	ADP
cana-2991	116	24	deep	deep	ADJ
cana-2991	116	25	neural	neural	ADJ
cana-2991	116	26	networks	network	NOUN
cana-2991	116	27	and	and	CCONJ
cana-2991	116	28	improving	improve	VERB
cana-2991	116	29	their	their	PRON
cana-2991	116	30	accuracy	accuracy	NOUN
cana-2991	116	31	against	against	ADP
cana-2991	116	32	standard	standard	ADJ
cana-2991	116	33	fake	fake	ADJ
cana-2991	116	34	news	news	NOUN
cana-2991	116	35	datasets	dataset	NOUN
cana-2991	116	36	.	.	PUNCT
cana-2991	117	1	the	the	DET
cana-2991	117	2	system	system	NOUN
cana-2991	117	3	achieved	achieve	VERB
cana-2991	117	4	state	state	NOUN
cana-2991	117	5	-	-	PUNCT
cana-2991	117	6	of	of	ADP
cana-2991	117	7	-	-	PUNCT
cana-2991	117	8	the	the	DET
cana-2991	117	9	-	-	PUNCT
cana-2991	117	10	art	art	NOUN
cana-2991	117	11	classification	classification	NOUN
cana-2991	117	12	performance	performance	NOUN
cana-2991	117	13	,	,	PUNCT
cana-2991	117	14	especially	especially	ADV
cana-2991	117	15	with	with	ADP
cana-2991	117	16	large	large	ADJ
cana-2991	117	17	datasets	dataset	NOUN
cana-2991	117	18	and	and	CCONJ
cana-2991	117	19	intricate	intricate	ADJ
cana-2991	117	20	patterns	pattern	NOUN
cana-2991	117	21	of	of	ADP
cana-2991	117	22	language	language	NOUN
cana-2991	117	23	.	.	PUNCT
cana-2991	118	1	the	the	DET
cana-2991	118	2	works	work	NOUN
cana-2991	118	3	of	of	ADP
cana-2991	118	4	other	other	ADJ
cana-2991	118	5	authors	author	NOUN
cana-2991	118	6	,	,	PUNCT
cana-2991	118	7	e.g.	e.g.	ADV
cana-2991	118	8	,	,	PUNCT
cana-2991	118	9	kula	kula	PROPN
cana-2991	118	10	et	et	PROPN
cana-2991	118	11	al	al	PROPN
cana-2991	118	12	.	.	PROPN
cana-2991	118	13	(	(	PUNCT
cana-2991	118	14	2021	2021	NUM
cana-2991	118	15	)	)	PUNCT
cana-2991	118	16	incorporated	incorporate	VERB
cana-2991	118	17	bert	bert	NOUN
cana-2991	118	18	and	and	CCONJ
cana-2991	118	19	recurrent	recurrent	ADJ
cana-2991	118	20	neural	neural	ADJ
cana-2991	118	21	network	network	NOUN
cana-2991	118	22	(	(	PUNCT
cana-2991	118	23	rnn	rnn	PROPN
cana-2991	118	24	)	)	PUNCT
cana-2991	118	25	to	to	PART
cana-2991	118	26	increase	increase	VERB
cana-2991	118	27	robustness	robustness	NOUN
cana-2991	118	28	of	of	ADP
cana-2991	118	29	fake	fake	ADJ
cana-2991	118	30	news	news	NOUN
cana-2991	118	31	detection	detection	NOUN
cana-2991	118	32	along	along	ADP
cana-2991	118	33	with	with	ADP
cana-2991	118	34	different	different	ADJ
cana-2991	118	35	text	text	NOUN
cana-2991	118	36	types	type	NOUN
cana-2991	119	1	[	[	X
cana-2991	119	2	38	38	NUM
cana-2991	119	3	]	]	PUNCT
cana-2991	119	4	.	.	PUNCT
cana-2991	120	1	on	on	ADP
cana-2991	120	2	the	the	DET
cana-2991	120	3	other	other	ADJ
cana-2991	120	4	hand	hand	NOUN
cana-2991	120	5	,	,	PUNCT
cana-2991	120	6	works	work	VERB
cana-2991	120	7	like	like	ADP
cana-2991	120	8	those	those	PRON
cana-2991	120	9	done	do	VERB
cana-2991	120	10	by	by	ADP
cana-2991	120	11	hauschild	hauschild	NOUN
cana-2991	120	12	and	and	CCONJ
cana-2991	120	13	eskridge	eskridge	NOUN
cana-2991	120	14	[	[	X
cana-2991	120	15	39	39	NUM
cana-2991	120	16	]	]	PUNCT
cana-2991	120	17	also	also	ADV
cana-2991	120	18	demonstrated	demonstrate	VERB
cana-2991	120	19	that	that	SCONJ
cana-2991	120	20	neural	neural	ADJ
cana-2991	120	21	network	network	NOUN
cana-2991	120	22	models	model	NOUN
cana-2991	120	23	based	base	VERB
cana-2991	120	24	on	on	ADP
cana-2991	120	25	deep	deep	ADJ
cana-2991	120	26	learning	learning	NOUN
cana-2991	120	27	(	(	PUNCT
cana-2991	120	28	e.g.	e.g.	ADV
cana-2991	120	29	,	,	PUNCT
cana-2991	120	30	convolutional	convolutional	ADJ
cana-2991	120	31	neural	neural	ADJ
cana-2991	120	32	networks	network	NOUN
cana-2991	120	33	cnns	cnn	NOUN
cana-2991	120	34	and	and	CCONJ
cana-2991	120	35	long	long	ADJ
cana-2991	120	36	short	short	ADJ
cana-2991	120	37	term	term	NOUN
cana-2991	120	38	memory	memory	NOUN
cana-2991	120	39	lstms	lstms	NOUN
cana-2991	120	40	)	)	PUNCT
cana-2991	120	41	effectively	effectively	ADV
cana-2991	120	42	captured	capture	VERB
cana-2991	120	43	sophisticated	sophisticated	ADJ
cana-2991	120	44	representations	representation	NOUN
cana-2991	120	45	about	about	ADP
cana-2991	120	46	text	text	NOUN
cana-2991	120	47	above	above	ADP
cana-2991	120	48	simple	simple	ADJ
cana-2991	120	49	word	word	NOUN
cana-2991	120	50	associations	association	NOUN
cana-2991	120	51	.	.	PUNCT
cana-2991	121	1	to	to	PART
cana-2991	121	2	identify	identify	VERB
cana-2991	121	3	those	those	DET
cana-2991	121	4	models	model	NOUN
cana-2991	121	5	that	that	PRON
cana-2991	121	6	are	be	AUX
cana-2991	121	7	particularly	particularly	ADV
cana-2991	121	8	useful	useful	ADJ
cana-2991	121	9	to	to	PART
cana-2991	121	10	know	know	VERB
cana-2991	121	11	,	,	PUNCT
cana-2991	121	12	it	it	PRON
cana-2991	121	13	was	be	AUX
cana-2991	121	14	used	use	VERB
cana-2991	121	15	on	on	ADP
cana-2991	121	16	fake	fake	ADJ
cana-2991	121	17	news	news	NOUN
cana-2991	121	18	using	use	VERB
cana-2991	121	19	misleading	mislead	VERB
cana-2991	121	20	narratives	narrative	NOUN
cana-2991	121	21	or	or	CCONJ
cana-2991	121	22	fancy	fancy	ADJ
cana-2991	121	23	rhetoric	rhetoric	NOUN
cana-2991	121	24	.	.	PUNCT
cana-2991	122	1	fake	fake	ADJ
cana-2991	122	2	news	news	NOUN
cana-2991	122	3	detection	detection	NOUN
cana-2991	122	4	for	for	ADP
cana-2991	122	5	scalability	scalability	NOUN
cana-2991	122	6	deep	deep	ADJ
cana-2991	122	7	learning	learning	NOUN
cana-2991	122	8	and	and	CCONJ
cana-2991	122	9	nlp	nlp	NOUN
cana-2991	122	10	models	model	NOUN
cana-2991	122	11	have	have	AUX
cana-2991	122	12	shown	show	VERB
cana-2991	122	13	state	state	NOUN
cana-2991	122	14	-	-	PUNCT
cana-2991	122	15	of	of	ADP
cana-2991	122	16	-	-	PUNCT
cana-2991	122	17	the	the	DET
cana-2991	122	18	-	-	PUNCT
cana-2991	122	19	art	art	NOUN
cana-2991	122	20	performance	performance	NOUN
cana-2991	122	21	in	in	ADP
cana-2991	122	22	fake	fake	ADJ
cana-2991	122	23	news	news	NOUN
cana-2991	122	24	detection	detection	NOUN
cana-2991	122	25	,	,	PUNCT
cana-2991	122	26	however	however	SCONJ
cana-2991	122	27	scalability	scalability	NOUN
cana-2991	122	28	is	be	AUX
cana-2991	122	29	a	a	DET
cana-2991	122	30	major	major	ADJ
cana-2991	122	31	limitation	limitation	NOUN
cana-2991	122	32	especially	especially	ADV
cana-2991	122	33	at	at	ADP
cana-2991	122	34	scale	scale	NOUN
cana-2991	122	35	as	as	ADP
cana-2991	122	36	large	large	ADJ
cana-2991	122	37	datasets	dataset	NOUN
cana-2991	122	38	.	.	PUNCT
cana-2991	123	1	the	the	DET
cana-2991	123	2	findings	finding	NOUN
cana-2991	123	3	of	of	ADP
cana-2991	123	4	sadeghi	sadeghi	PROPN
cana-2991	123	5	et	et	PROPN
cana-2991	123	6	al	al	PROPN
cana-2991	123	7	.	.	PROPN
cana-2991	124	1	in	in	ADP
cana-2991	124	2	a	a	DET
cana-2991	124	3	recent	recent	ADJ
cana-2991	124	4	paper	paper	NOUN
cana-2991	124	5	,	,	PUNCT
cana-2991	124	6	khabsa	khabsa	PROPN
cana-2991	124	7	et	et	PROPN
cana-2991	124	8	.	.	PUNCT
cana-2991	124	9	al[40	al[40	PROPN
cana-2991	124	10	]	]	X
cana-2991	124	11	(	(	PUNCT
cana-2991	124	12	2020	2020	NUM
cana-2991	124	13	)	)	PUNCT
cana-2991	124	14	demonstrates	demonstrate	VERB
cana-2991	124	15	the	the	DET
cana-2991	124	16	issues	issue	NOUN
cana-2991	124	17	of	of	ADP
cana-2991	124	18	using	use	VERB
cana-2991	124	19	standard	standard	ADJ
cana-2991	124	20	machine	machine	NOUN
cana-2991	124	21	communications	communication	NOUN
cana-2991	124	22	on	on	ADP
cana-2991	124	23	applied	apply	VERB
cana-2991	124	24	nonlinear	nonlinear	ADJ
cana-2991	124	25	analysis	analysis	NOUN
cana-2991	124	26	issn	issn	NOUN
cana-2991	124	27	:	:	PUNCT
cana-2991	124	28	1074	1074	NUM
cana-2991	124	29	-	-	PUNCT
cana-2991	124	30	133x	133x	NUM
cana-2991	124	31	vol	vol	NOUN
cana-2991	124	32	32	32	NUM
cana-2991	124	33	no	no	NOUN
cana-2991	124	34	.	.	PUNCT
cana-2991	125	1	5s	5s	NUM
cana-2991	125	2	(	(	PUNCT
cana-2991	125	3	2025	2025	NUM
cana-2991	125	4	)	)	PUNCT
cana-2991	125	5	157	157	NUM
cana-2991	125	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	125	7	learning	learn	VERB
cana-2991	125	8	models	model	NOUN
cana-2991	125	9	for	for	ADP
cana-2991	125	10	processing	process	VERB
cana-2991	125	11	large	large	ADJ
cana-2991	125	12	datasets	dataset	NOUN
cana-2991	125	13	containing	contain	VERB
cana-2991	125	14	millions	million	NOUN
cana-2991	125	15	of	of	ADP
cana-2991	125	16	articles	article	NOUN
cana-2991	125	17	.	.	PUNCT
cana-2991	126	1	they	they	PRON
cana-2991	126	2	highlighted	highlight	VERB
cana-2991	126	3	the	the	DET
cana-2991	126	4	necessity	necessity	NOUN
cana-2991	126	5	for	for	ADP
cana-2991	126	6	distributed	distribute	VERB
cana-2991	126	7	processing	processing	NOUN
cana-2991	126	8	frameworks	framework	NOUN
cana-2991	126	9	capable	capable	ADJ
cana-2991	126	10	of	of	ADP
cana-2991	126	11	handling	handle	VERB
cana-2991	126	12	computation	computation	NOUN
cana-2991	126	13	heavy	heavy	ADJ
cana-2991	126	14	embedding	embed	VERB
cana-2991	126	15	models	model	NOUN
cana-2991	126	16	like	like	ADP
cana-2991	126	17	bert	bert	NOUN
cana-2991	126	18	and	and	CCONJ
cana-2991	126	19	glove	glove	NOUN
cana-2991	126	20	.	.	PUNCT
cana-2991	127	1	to	to	PART
cana-2991	127	2	address	address	VERB
cana-2991	127	3	this	this	DET
cana-2991	127	4	requirement	requirement	NOUN
cana-2991	127	5	,	,	PUNCT
cana-2991	127	6	the	the	DET
cana-2991	127	7	present	present	ADJ
cana-2991	127	8	study	study	NOUN
cana-2991	127	9	illustrates	illustrate	VERB
cana-2991	127	10	how	how	SCONJ
cana-2991	127	11	these	these	DET
cana-2991	127	12	methods	method	NOUN
cana-2991	127	13	can	can	AUX
cana-2991	127	14	be	be	AUX
cana-2991	127	15	scaled	scale	VERB
cana-2991	127	16	out	out	ADP
cana-2991	127	17	with	with	ADP
cana-2991	127	18	regard	regard	NOUN
cana-2991	127	19	to	to	ADP
cana-2991	127	20	fake	fake	ADJ
cana-2991	127	21	news	news	NOUN
cana-2991	127	22	detection	detection	NOUN
cana-2991	127	23	using	use	VERB
cana-2991	127	24	distributed	distribute	VERB
cana-2991	127	25	computing	computing	NOUN
cana-2991	127	26	frameworks	framework	NOUN
cana-2991	127	27	.	.	PUNCT
cana-2991	128	1	thanks	thank	NOUN
cana-2991	128	2	to	to	ADP
cana-2991	128	3	the	the	DET
cana-2991	128	4	integration	integration	NOUN
cana-2991	128	5	with	with	ADP
cana-2991	128	6	systems	system	NOUN
cana-2991	128	7	like	like	ADP
cana-2991	128	8	apache	apache	NOUN
cana-2991	128	9	spark	spark	NOUN
cana-2991	128	10	,	,	PUNCT
cana-2991	128	11	those	those	DET
cana-2991	128	12	datasets	dataset	NOUN
cana-2991	128	13	can	can	AUX
cana-2991	128	14	be	be	AUX
cana-2991	128	15	processed	process	VERB
cana-2991	128	16	in	in	ADP
cana-2991	128	17	parallel	parallel	NOUN
cana-2991	128	18	,	,	PUNCT
cana-2991	128	19	allowing	allow	VERB
cana-2991	128	20	us	we	PRON
cana-2991	128	21	to	to	PART
cana-2991	128	22	train	train	VERB
cana-2991	128	23	intricate	intricate	ADJ
cana-2991	128	24	models	model	NOUN
cana-2991	128	25	like	like	ADP
cana-2991	128	26	bert	bert	PROPN
cana-2991	128	27	on	on	ADP
cana-2991	128	28	millions	million	NOUN
cana-2991	128	29	of	of	ADP
cana-2991	128	30	news	news	NOUN
cana-2991	128	31	articles	article	NOUN
cana-2991	128	32	.	.	PUNCT
cana-2991	129	1	this	this	DET
cana-2991	129	2	technique	technique	NOUN
cana-2991	129	3	not	not	PART
cana-2991	129	4	only	only	ADV
cana-2991	129	5	accelerates	accelerate	VERB
cana-2991	129	6	training	training	NOUN
cana-2991	129	7	of	of	ADP
cana-2991	129	8	the	the	DET
cana-2991	129	9	model	model	NOUN
cana-2991	129	10	but	but	CCONJ
cana-2991	129	11	also	also	ADV
cana-2991	129	12	efficiently	efficiently	ADV
cana-2991	129	13	identifies	identify	VERB
cana-2991	129	14	fake	fake	ADJ
cana-2991	129	15	news	news	NOUN
cana-2991	129	16	over	over	ADP
cana-2991	129	17	platforms	platform	NOUN
cana-2991	129	18	like	like	ADP
cana-2991	129	19	social	social	ADJ
cana-2991	129	20	media	medium	NOUN
cana-2991	129	21	,	,	PUNCT
cana-2991	129	22	which	which	PRON
cana-2991	129	23	churns	churn	VERB
cana-2991	129	24	out	out	ADP
cana-2991	129	25	huge	huge	ADJ
cana-2991	129	26	amounts	amount	NOUN
cana-2991	129	27	of	of	ADP
cana-2991	129	28	data	datum	NOUN
cana-2991	129	29	every	every	DET
cana-2991	129	30	second	second	NOUN
cana-2991	129	31	.	.	PUNCT
cana-2991	130	1	source	source	NOUN
cana-2991	130	2	objective	objective	ADJ
cana-2991	130	3	methodology	methodology	NOUN
cana-2991	130	4	results	result	VERB
cana-2991	130	5	research	research	NOUN
cana-2991	130	6	gap	gap	NOUN
cana-2991	130	7	[	[	X
cana-2991	130	8	5	5	NUM
cana-2991	130	9	]	]	PUNCT
cana-2991	130	10	●	●	PUNCT
cana-2991	130	11	adapt	adapt	VERB
cana-2991	130	12	fake	fake	ADJ
cana-2991	130	13	news	news	NOUN
cana-2991	130	14	detectors	detector	NOUN
cana-2991	130	15	to	to	ADP
cana-2991	130	16	large	large	ADJ
cana-2991	130	17	language	language	NOUN
cana-2991	130	18	models	model	NOUN
cana-2991	130	19	era	era	NOUN
cana-2991	130	20	.	.	PUNCT
cana-2991	131	1	●	●	NUM
cana-2991	131	2	study	study	NOUN
cana-2991	131	3	interplay	interplay	NOUN
cana-2991	131	4	between	between	ADP
cana-2991	131	5	human	human	NOUN
cana-2991	131	6	-	-	PUNCT
cana-2991	131	7	written	write	VERB
cana-2991	131	8	and	and	CCONJ
cana-2991	131	9	machinegenerated	machinegenerate	VERB
cana-2991	131	10	news	news	NOUN
cana-2991	131	11	.	.	PUNCT
cana-2991	132	1	●	●	PUNCT
cana-2991	132	2	evaluate	evaluate	VERB
cana-2991	132	3	fake	fake	ADJ
cana-2991	132	4	news	news	NOUN
cana-2991	132	5	detectors	detector	NOUN
cana-2991	132	6	trained	train	VERB
cana-2991	132	7	in	in	ADP
cana-2991	132	8	various	various	ADJ
cana-2991	132	9	scenarios	scenario	NOUN
cana-2991	132	10	●	●	PUNCT
cana-2991	132	11	provide	provide	VERB
cana-2991	132	12	a	a	DET
cana-2991	132	13	practical	practical	ADJ
cana-2991	132	14	strategy	strategy	NOUN
cana-2991	132	15	for	for	ADP
cana-2991	132	16	robust	robust	ADJ
cana-2991	132	17	fake	fake	ADJ
cana-2991	132	18	news	news	NOUN
cana-2991	132	19	detectors	detector	NOUN
cana-2991	132	20	●	●	NUM
cana-2991	132	21	detectors	detector	NOUN
cana-2991	132	22	trained	train	VERB
cana-2991	132	23	on	on	ADP
cana-2991	132	24	humanwritten	humanwritten	VERB
cana-2991	132	25	articles	article	NOUN
cana-2991	132	26	perform	perform	VERB
cana-2991	132	27	well	well	ADV
cana-2991	132	28	on	on	ADP
cana-2991	132	29	machine	machine	NOUN
cana-2991	132	30	-	-	PUNCT
cana-2991	132	31	generated	generate	VERB
cana-2991	132	32	fake	fake	ADJ
cana-2991	132	33	news	news	NOUN
cana-2991	132	34	.	.	PUNCT
cana-2991	133	1	●	●	PUNCT
cana-2991	133	2	detectors	detector	NOUN
cana-2991	133	3	should	should	AUX
cana-2991	133	4	be	be	AUX
cana-2991	133	5	trained	train	VERB
cana-2991	133	6	on	on	ADP
cana-2991	133	7	datasets	dataset	NOUN
cana-2991	133	8	with	with	ADP
cana-2991	133	9	lower	low	ADJ
cana-2991	133	10	machine	machine	NOUN
cana-2991	133	11	-	-	PUNCT
cana-2991	133	12	generated	generate	VERB
cana-2991	133	13	news	news	NOUN
cana-2991	133	14	ratio	ratio	NOUN
cana-2991	133	15	.	.	PUNCT
cana-2991	134	1	●	●	PUNCT
cana-2991	134	2	understanding	understand	VERB
cana-2991	134	3	interplay	interplay	NOUN
cana-2991	134	4	between	between	ADP
cana-2991	134	5	human	human	NOUN
cana-2991	134	6	-	-	PUNCT
cana-2991	134	7	written	write	VERB
cana-2991	134	8	and	and	CCONJ
cana-2991	134	9	machine	machine	NOUN
cana-2991	134	10	-	-	PUNCT
cana-2991	134	11	generated	generate	VERB
cana-2991	134	12	news	news	NOUN
cana-2991	134	13	.	.	PUNCT
cana-2991	135	1	●	●	PUNCT
cana-2991	135	2	detecting	detect	VERB
cana-2991	135	3	machine	machine	NOUN
cana-2991	135	4	-	-	PUNCT
cana-2991	135	5	generated	generate	VERB
cana-2991	135	6	fake	fake	ADJ
cana-2991	135	7	news	news	NOUN
cana-2991	135	8	vs.	vs.	ADP
cana-2991	135	9	humanwritten	humanwritten	VERB
cana-2991	135	10	fake	fake	ADJ
cana-2991	135	11	news	news	NOUN
cana-2991	135	12	.	.	PUNCT
cana-2991	136	1	[	[	X
cana-2991	136	2	6	6	NUM
cana-2991	136	3	]	]	SYM
cana-2991	136	4	●	●	NUM
cana-2991	136	5	highlight	highlight	NOUN
cana-2991	136	6	dataset	dataset	VERB
cana-2991	136	7	quality	quality	NOUN
cana-2991	136	8	and	and	CCONJ
cana-2991	136	9	diversity	diversity	NOUN
cana-2991	136	10	importance	importance	NOUN
cana-2991	136	11	in	in	ADP
cana-2991	136	12	fake	fake	ADJ
cana-2991	136	13	news	news	NOUN
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cana-2991	137	1	●	●	PUNCT
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cana-2991	137	8	in	in	ADP
cana-2991	137	9	one	one	NUM
cana-2991	137	10	portal	portal	NOUN
cana-2991	137	11	.	.	PUNCT
cana-2991	138	1	●	●	NUM
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cana-2991	138	4	and	and	CCONJ
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cana-2991	138	6	emphasized	emphasize	VERB
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cana-2991	138	10	.	.	PUNCT
cana-2991	139	1	●	●	PUNCT
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cana-2991	140	1	●	●	PUNCT
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cana-2991	140	5	diversity	diversity	NOUN
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cana-2991	141	1	●	●	PUNCT
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cana-2991	141	7	datasets	dataset	NOUN
cana-2991	141	8	for	for	ADP
cana-2991	141	9	research	research	NOUN
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cana-2991	141	11	.	.	PUNCT
cana-2991	142	1	●	●	NUM
cana-2991	142	2	dataset	dataset	ADJ
cana-2991	142	3	quality	quality	NOUN
cana-2991	142	4	,	,	PUNCT
cana-2991	142	5	diversity	diversity	NOUN
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cana-2991	142	7	on	on	ADP
cana-2991	142	8	model	model	NOUN
cana-2991	142	9	effectiveness	effectiveness	NOUN
cana-2991	142	10	●	●	PUNCT
cana-2991	142	11	addressing	address	VERB
cana-2991	142	12	biases	bias	NOUN
cana-2991	142	13	,	,	PUNCT
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cana-2991	142	16	,	,	PUNCT
cana-2991	142	17	best	good	ADJ
cana-2991	142	18	practices	practice	NOUN
cana-2991	142	19	in	in	ADP
cana-2991	142	20	dataset	dataset	ADJ
cana-2991	142	21	creation	creation	NOUN
cana-2991	142	22	[	[	X
cana-2991	142	23	7	7	X
cana-2991	142	24	]	]	SYM
cana-2991	142	25	●	●	PUNCT
cana-2991	142	26	investigate	investigate	VERB
cana-2991	142	27	preprocessing	preprocessing	NOUN
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cana-2991	142	29	and	and	CCONJ
cana-2991	142	30	model	model	NOUN
cana-2991	142	31	architectures	architecture	NOUN
cana-2991	142	32	for	for	ADP
cana-2991	142	33	fake	fake	ADJ
cana-2991	142	34	news	news	NOUN
cana-2991	142	35	detection	detection	NOUN
cana-2991	142	36	.	.	PUNCT
cana-2991	143	1	●	●	NUM
cana-2991	143	2	test	test	NOUN
cana-2991	143	3	model	model	NOUN
cana-2991	143	4	performance	performance	NOUN
cana-2991	143	5	on	on	ADP
cana-2991	143	6	●	●	NUM
cana-2991	143	7	preprocessing	preprocesse	VERB
cana-2991	143	8	techniques	technique	NOUN
cana-2991	143	9	and	and	CCONJ
cana-2991	143	10	model	model	NOUN
cana-2991	143	11	architectures	architecture	NOUN
cana-2991	143	12	●	●	NUM
cana-2991	143	13	deep	deep	ADJ
cana-2991	143	14	learning	learning	NOUN
cana-2991	143	15	(	(	PUNCT
cana-2991	143	16	cnn	cnn	PROPN
cana-2991	143	17	,	,	PUNCT
cana-2991	143	18	lstm	lstm	PROPN
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cana-2991	143	20	and	and	CCONJ
cana-2991	143	21	conventional	conventional	ADJ
cana-2991	143	22	ml	ml	X
cana-2991	143	23	(	(	PUNCT
cana-2991	143	24	random	random	ADJ
cana-2991	143	25	forest	forest	NOUN
cana-2991	143	26	,	,	PUNCT
cana-2991	143	27	gradient	gradient	ADJ
cana-2991	143	28	boost	boost	NOUN
cana-2991	143	29	)	)	PUNCT
cana-2991	143	30	●	●	NUM
cana-2991	143	31	investigated	investigate	VERB
cana-2991	143	32	various	various	ADJ
cana-2991	143	33	preprocessing	preprocessing	NOUN
cana-2991	143	34	techniques	technique	NOUN
cana-2991	143	35	and	and	CCONJ
cana-2991	143	36	model	model	NOUN
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cana-2991	143	38	for	for	ADP
cana-2991	143	39	fake	fake	ADJ
cana-2991	143	40	news	news	NOUN
cana-2991	143	41	detection	detection	NOUN
cana-2991	143	42	.	.	PUNCT
cana-2991	144	1	●	●	NUM
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cana-2991	144	4	on	on	ADP
cana-2991	144	5	two	two	NUM
cana-2991	144	6	●	●	NUM
cana-2991	144	7	model	model	NOUN
cana-2991	144	8	implementation	implementation	NOUN
cana-2991	144	9	issues	issue	NOUN
cana-2991	144	10	hinder	hinder	VERB
cana-2991	144	11	effective	effective	ADJ
cana-2991	144	12	fake	fake	ADJ
cana-2991	144	13	news	news	NOUN
cana-2991	144	14	detection	detection	NOUN
cana-2991	144	15	.	.	PUNCT
cana-2991	145	1	●	●	PUNCT
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cana-2991	145	4	clean	clean	ADJ
cana-2991	145	5	,	,	PUNCT
cana-2991	145	6	unbiased	unbiased	ADJ
cana-2991	145	7	data	datum	NOUN
cana-2991	145	8	poses	pose	VERB
cana-2991	145	9	a	a	DET
cana-2991	145	10	challenge	challenge	NOUN
cana-2991	145	11	in	in	ADP
cana-2991	145	12	research	research	NOUN
cana-2991	145	13	.	.	PUNCT
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cana-2991	146	4	nonlinear	nonlinear	ADJ
cana-2991	146	5	analysis	analysis	NOUN
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cana-2991	146	7	:	:	PUNCT
cana-2991	146	8	1074	1074	NUM
cana-2991	146	9	-	-	PUNCT
cana-2991	146	10	133x	133x	NUM
cana-2991	146	11	vol	vol	NOUN
cana-2991	146	12	32	32	NUM
cana-2991	146	13	no	no	NOUN
cana-2991	146	14	.	.	PUNCT
cana-2991	147	1	5s	5s	NUM
cana-2991	147	2	(	(	PUNCT
cana-2991	147	3	2025	2025	NUM
cana-2991	147	4	)	)	PUNCT
cana-2991	147	5	158	158	NUM
cana-2991	147	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	147	7	widely	widely	ADV
cana-2991	147	8	used	use	VERB
cana-2991	147	9	datasets	dataset	NOUN
cana-2991	147	10	.	.	PUNCT
cana-2991	148	1	widely	widely	ADV
cana-2991	148	2	used	use	VERB
cana-2991	148	3	datasets	dataset	NOUN
cana-2991	148	4	,	,	PUNCT
cana-2991	148	5	contributing	contribute	VERB
cana-2991	148	6	to	to	ADP
cana-2991	148	7	the	the	DET
cana-2991	148	8	field	field	NOUN
cana-2991	148	9	.	.	PUNCT
cana-2991	149	1	[	[	X
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cana-2991	149	3	]	]	X
cana-2991	149	4	●	●	PUNCT
cana-2991	149	5	develop	develop	VERB
cana-2991	149	6	sustainable	sustainable	ADJ
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cana-2991	149	13	.	.	PUNCT
cana-2991	150	1	●	●	PUNCT
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cana-2991	150	4	technology	technology	NOUN
cana-2991	150	5	to	to	PART
cana-2991	150	6	eradicate	eradicate	VERB
cana-2991	150	7	and	and	CCONJ
cana-2991	150	8	control	control	VERB
cana-2991	150	9	fake	fake	ADJ
cana-2991	150	10	news	news	NOUN
cana-2991	150	11	.	.	PUNCT
cana-2991	151	1	●	●	PUNCT
cana-2991	151	2	backdated	backdate	VERB
cana-2991	151	3	neural	neural	ADJ
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cana-2991	151	6	●	●	NUM
cana-2991	151	7	bert	bert	NOUN
cana-2991	151	8	technology	technology	NOUN
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cana-2991	151	13	●	●	PUNCT
cana-2991	151	14	ai	ai	NOUN
cana-2991	151	15	solution	solution	NOUN
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cana-2991	151	18	for	for	ADP
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cana-2991	151	20	news	news	NOUN
cana-2991	151	21	detection	detection	NOUN
cana-2991	151	22	.	.	PUNCT
cana-2991	152	1	●	●	PUNCT
cana-2991	152	2	aims	aim	VERB
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cana-2991	152	5	,	,	PUNCT
cana-2991	152	6	eliminate	eliminate	VERB
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cana-2991	152	13	news	news	NOUN
cana-2991	152	14	.	.	PUNCT
cana-2991	153	1	●	●	PUNCT
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cana-2991	153	5	on	on	ADP
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cana-2991	153	7	implementation	implementation	NOUN
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cana-2991	153	9	.	.	PUNCT
cana-2991	154	1	●	●	NUM
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cana-2991	154	4	of	of	ADP
cana-2991	154	5	alternative	alternative	ADJ
cana-2991	154	6	ai	ai	NOUN
cana-2991	154	7	models	model	NOUN
cana-2991	154	8	for	for	ADP
cana-2991	154	9	fake	fake	ADJ
cana-2991	154	10	news	news	NOUN
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cana-2991	154	12	.	.	PUNCT
cana-2991	155	1	[	[	X
cana-2991	155	2	9	9	NUM
cana-2991	155	3	]	]	SYM
cana-2991	155	4	●	●	PUNCT
cana-2991	155	5	evaluate	evaluate	VERB
cana-2991	155	6	llm	llm	NOUN
cana-2991	155	7	integration	integration	NOUN
cana-2991	155	8	in	in	ADP
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cana-2991	155	12	.	.	PUNCT
cana-2991	156	1	●	●	PUNCT
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cana-2991	157	9	(	(	PUNCT
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cana-2991	157	14	●	●	PUNCT
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cana-2991	157	23	news	news	NOUN
cana-2991	157	24	detection	detection	NOUN
cana-2991	157	25	.	.	PUNCT
cana-2991	158	1	●	●	PUNCT
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cana-2991	159	1	●	●	PUNCT
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cana-2991	160	1	●	●	PUNCT
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cana-2991	160	7	in	in	ADP
cana-2991	160	8	conventional	conventional	ADJ
cana-2991	160	9	machine	machine	NOUN
cana-2991	160	10	learning	learning	NOUN
cana-2991	160	11	methods	method	NOUN
cana-2991	160	12	.	.	PUNCT
cana-2991	161	1	[	[	X
cana-2991	161	2	10	10	NUM
cana-2991	161	3	]	]	X
cana-2991	161	4	●	●	PUNCT
cana-2991	161	5	utilize	utilize	VERB
cana-2991	161	6	llms	llm	NOUN
cana-2991	161	7	for	for	ADP
cana-2991	161	8	news	news	NOUN
cana-2991	161	9	event	event	NOUN
cana-2991	161	10	detection	detection	NOUN
cana-2991	161	11	framework	framework	NOUN
cana-2991	161	12	.	.	PUNCT
cana-2991	162	1	●	●	PUNCT
cana-2991	162	2	evaluate	evaluate	VERB
cana-2991	162	3	impact	impact	NOUN
cana-2991	162	4	of	of	ADP
cana-2991	162	5	textual	textual	ADJ
cana-2991	162	6	embeddings	embedding	NOUN
cana-2991	162	7	on	on	ADP
cana-2991	162	8	clustering	cluster	VERB
cana-2991	162	9	outcomes	outcome	NOUN
cana-2991	162	10	.	.	PUNCT
cana-2991	163	1	●	●	PUNCT
cana-2991	163	2	large	large	ADJ
cana-2991	163	3	language	language	NOUN
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cana-2991	163	5	(	(	PUNCT
cana-2991	163	6	llms	llm	NOUN
cana-2991	163	7	)	)	PUNCT
cana-2991	163	8	combined	combine	VERB
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cana-2991	163	10	clustering	cluster	VERB
cana-2991	163	11	analysis	analysis	NOUN
cana-2991	163	12	●	●	NUM
cana-2991	163	13	cluster	cluster	NOUN
cana-2991	163	14	stability	stability	NOUN
cana-2991	163	15	assessment	assessment	NOUN
cana-2991	163	16	index	index	NOUN
cana-2991	163	17	(	(	PUNCT
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cana-2991	163	19	)	)	PUNCT
cana-2991	163	20	for	for	ADP
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cana-2991	163	23	quality	quality	NOUN
cana-2991	163	24	●	●	NUM
cana-2991	163	25	llm	llm	NOUN
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cana-2991	163	28	clustering	clustering	ADJ
cana-2991	163	29	yield	yield	NOUN
cana-2991	163	30	best	good	ADJ
cana-2991	163	31	results	result	NOUN
cana-2991	163	32	.	.	PUNCT
cana-2991	164	1	●	●	PUNCT
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cana-2991	164	6	provide	provide	VERB
cana-2991	164	7	meaningful	meaningful	ADJ
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cana-2991	164	11	.	.	PUNCT
cana-2991	165	1	●	●	PUNCT
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cana-2991	165	5	textual	textual	ADJ
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cana-2991	165	7	on	on	ADP
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cana-2991	165	9	quality	quality	NOUN
cana-2991	165	10	.	.	PUNCT
cana-2991	166	1	●	●	PUNCT
cana-2991	166	2	introduce	introduce	NOUN
cana-2991	166	3	cluster	cluster	NOUN
cana-2991	166	4	stability	stability	NOUN
cana-2991	166	5	assessment	assessment	NOUN
cana-2991	166	6	index	index	NOUN
cana-2991	166	7	(	(	PUNCT
cana-2991	166	8	csai	csai	PROPN
cana-2991	166	9	)	)	PUNCT
cana-2991	166	10	for	for	ADP
cana-2991	166	11	measuring	measure	VERB
cana-2991	166	12	clustering	clustering	ADJ
cana-2991	166	13	quality	quality	NOUN
cana-2991	166	14	.	.	PUNCT
cana-2991	167	1	[	[	X
cana-2991	167	2	11	11	NUM
cana-2991	167	3	]	]	SYM
cana-2991	167	4	●	●	PUNCT
cana-2991	167	5	develop	develop	VERB
cana-2991	167	6	model	model	NOUN
cana-2991	167	7	for	for	ADP
cana-2991	167	8	detecting	detect	VERB
cana-2991	167	9	fake	fake	ADJ
cana-2991	167	10	news	news	NOUN
cana-2991	167	11	.	.	PUNCT
cana-2991	168	1	●	●	PUNCT
cana-2991	168	2	assess	assess	NOUN
cana-2991	168	3	effectiveness	effectiveness	NOUN
cana-2991	168	4	in	in	ADP
cana-2991	168	5	recognizing	recognize	VERB
cana-2991	168	6	false	false	ADJ
cana-2991	168	7	information	information	NOUN
cana-2991	168	8	.	.	PUNCT
cana-2991	169	1	●	●	PUNCT
cana-2991	169	2	supervised	supervised	ADJ
cana-2991	169	3	learning	learning	NOUN
cana-2991	169	4	techniques	technique	NOUN
cana-2991	169	5	used	use	VERB
cana-2991	169	6	for	for	ADP
cana-2991	169	7	model	model	NOUN
cana-2991	169	8	selection	selection	NOUN
cana-2991	169	9	●	●	PUNCT
cana-2991	169	10	naïve	naïve	ADJ
cana-2991	169	11	bayes	bayes	NOUN
cana-2991	169	12	,	,	PUNCT
cana-2991	169	13	logistic	logistic	ADJ
cana-2991	169	14	regression	regression	NOUN
cana-2991	169	15	,	,	PUNCT
cana-2991	169	16	and	and	CCONJ
cana-2991	169	17	random	random	ADJ
cana-2991	169	18	forest	forest	NOUN
cana-2991	169	19	algorithms	algorithm	NOUN
cana-2991	169	20	applied	apply	VERB
cana-2991	169	21	●	●	NUM
cana-2991	169	22	random	random	ADJ
cana-2991	169	23	forest	forest	NOUN
cana-2991	169	24	model	model	NOUN
cana-2991	169	25	showed	show	VERB
cana-2991	169	26	best	good	ADJ
cana-2991	169	27	accuracy	accuracy	NOUN
cana-2991	169	28	.	.	PUNCT
cana-2991	170	1	●	●	PUNCT
cana-2991	170	2	framework	framework	NOUN
cana-2991	170	3	effectively	effectively	ADV
cana-2991	170	4	detects	detect	VERB
cana-2991	170	5	fake	fake	ADJ
cana-2991	170	6	news	news	NOUN
cana-2991	170	7	in	in	ADP
cana-2991	170	8	various	various	ADJ
cana-2991	170	9	settings	setting	NOUN
cana-2991	170	10	.	.	PUNCT
cana-2991	171	1	●	●	PUNCT
cana-2991	171	2	framework	framework	NOUN
cana-2991	171	3	focuses	focus	VERB
cana-2991	171	4	on	on	ADP
cana-2991	171	5	news	news	NOUN
cana-2991	171	6	sources	source	NOUN
cana-2991	171	7	and	and	CCONJ
cana-2991	171	8	content	content	NOUN
cana-2991	171	9	credibility	credibility	NOUN
cana-2991	171	10	.	.	PUNCT
cana-2991	172	1	●	●	PUNCT
cana-2991	172	2	random	random	ADJ
cana-2991	172	3	forest	forest	NOUN
cana-2991	172	4	model	model	NOUN
cana-2991	172	5	shows	show	VERB
cana-2991	172	6	highest	high	ADJ
cana-2991	172	7	accuracy	accuracy	NOUN
cana-2991	172	8	in	in	ADP
cana-2991	172	9	fake	fake	ADJ
cana-2991	172	10	news	news	NOUN
cana-2991	172	11	detection	detection	NOUN
cana-2991	172	12	.	.	PUNCT
cana-2991	173	1	communications	communication	NOUN
cana-2991	173	2	on	on	ADP
cana-2991	173	3	applied	apply	VERB
cana-2991	173	4	nonlinear	nonlinear	ADJ
cana-2991	173	5	analysis	analysis	NOUN
cana-2991	173	6	issn	issn	NOUN
cana-2991	173	7	:	:	PUNCT
cana-2991	173	8	1074	1074	NUM
cana-2991	173	9	-	-	PUNCT
cana-2991	173	10	133x	133x	NUM
cana-2991	173	11	vol	vol	NOUN
cana-2991	173	12	32	32	NUM
cana-2991	173	13	no	no	NOUN
cana-2991	173	14	.	.	PUNCT
cana-2991	174	1	5s	5s	NUM
cana-2991	174	2	(	(	PUNCT
cana-2991	174	3	2025	2025	NUM
cana-2991	174	4	)	)	PUNCT
cana-2991	174	5	159	159	NUM
cana-2991	174	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	175	1	[	[	X
cana-2991	175	2	12	12	NUM
cana-2991	175	3	]	]	X
cana-2991	175	4	●	●	PUNCT
cana-2991	175	5	identify	identify	VERB
cana-2991	175	6	false	false	ADJ
cana-2991	175	7	news	news	NOUN
cana-2991	175	8	using	use	VERB
cana-2991	175	9	advanced	advanced	ADJ
cana-2991	175	10	machine	machine	NOUN
cana-2991	175	11	learning	learn	VERB
cana-2991	175	12	techniques	technique	NOUN
cana-2991	175	13	.	.	PUNCT
cana-2991	176	1	●	●	PUNCT
cana-2991	176	2	improve	improve	VERB
cana-2991	176	3	accuracy	accuracy	NOUN
cana-2991	176	4	and	and	CCONJ
cana-2991	176	5	scalability	scalability	NOUN
cana-2991	176	6	in	in	ADP
cana-2991	176	7	detecting	detect	VERB
cana-2991	176	8	misinformation	misinformation	NOUN
cana-2991	176	9	.	.	PUNCT
cana-2991	177	1	●	●	NUM
cana-2991	177	2	advanced	advanced	ADJ
cana-2991	177	3	feature	feature	NOUN
cana-2991	177	4	selection	selection	NOUN
cana-2991	177	5	,	,	PUNCT
cana-2991	177	6	classification	classification	NOUN
cana-2991	177	7	algorithms	algorithm	NOUN
cana-2991	177	8	,	,	PUNCT
cana-2991	177	9	nlp	nlp	NOUN
cana-2991	177	10	approaches	approach	VERB
cana-2991	177	11	●	●	NUM
cana-2991	177	12	hybrid	hybrid	ADJ
cana-2991	177	13	stacking	stacking	NOUN
cana-2991	177	14	classifier	classifier	NOUN
cana-2991	177	15	:	:	PUNCT
cana-2991	177	16	random	random	ADJ
cana-2991	177	17	forest	forest	NOUN
cana-2991	177	18	,	,	PUNCT
cana-2991	177	19	xgboost	xgboost	ADV
cana-2991	177	20	,	,	PUNCT
cana-2991	177	21	logistic	logistic	ADJ
cana-2991	177	22	regression	regression	NOUN
cana-2991	177	23	●	●	PUNCT
cana-2991	177	24	high	high	ADJ
cana-2991	177	25	recall	recall	NOUN
cana-2991	177	26	rates	rate	NOUN
cana-2991	177	27	and	and	CCONJ
cana-2991	177	28	precision	precision	NOUN
cana-2991	177	29	achieved	achieve	VERB
cana-2991	177	30	.	.	PUNCT
cana-2991	178	1	●	●	PUNCT
cana-2991	178	2	improved	improved	ADJ
cana-2991	178	3	accuracy	accuracy	NOUN
cana-2991	178	4	and	and	CCONJ
cana-2991	178	5	scalability	scalability	NOUN
cana-2991	178	6	in	in	ADP
cana-2991	178	7	detecting	detect	VERB
cana-2991	178	8	fake	fake	ADJ
cana-2991	178	9	news	news	NOUN
cana-2991	178	10	.	.	PUNCT
cana-2991	179	1	●	●	NUM
cana-2991	179	2	nuanced	nuanced	ADJ
cana-2991	179	3	language	language	NOUN
cana-2991	179	4	patterns	pattern	NOUN
cana-2991	179	5	detection	detection	VERB
cana-2991	179	6	●	●	PUNCT
cana-2991	179	7	high	high	ADJ
cana-2991	179	8	false	false	ADJ
cana-2991	179	9	positive	positive	ADJ
cana-2991	179	10	rates	rate	NOUN
cana-2991	179	11	and	and	CCONJ
cana-2991	179	12	scalability	scalability	NOUN
cana-2991	179	13	issues	issue	NOUN
cana-2991	179	14	[	[	X
cana-2991	179	15	13	13	NUM
cana-2991	179	16	]	]	X
cana-2991	179	17	●	●	PUNCT
cana-2991	179	18	evaluate	evaluate	VERB
cana-2991	179	19	large	large	ADJ
cana-2991	179	20	language	language	NOUN
cana-2991	179	21	models	model	NOUN
cana-2991	179	22	in	in	ADP
cana-2991	179	23	detecting	detect	VERB
cana-2991	179	24	fake	fake	ADJ
cana-2991	179	25	news	news	NOUN
cana-2991	179	26	.	.	PUNCT
cana-2991	180	1	●	●	PUNCT
cana-2991	180	2	discuss	discuss	VERB
cana-2991	180	3	implications	implication	NOUN
cana-2991	180	4	for	for	ADP
cana-2991	180	5	developers	developer	NOUN
cana-2991	180	6	and	and	CCONJ
cana-2991	180	7	policymaker	policymaker	NOUN
cana-2991	180	8	.	.	PUNCT
cana-2991	181	1	●	●	PUNCT
cana-2991	181	2	statistical	statistical	ADJ
cana-2991	181	3	evaluation	evaluation	NOUN
cana-2991	181	4	and	and	CCONJ
cana-2991	181	5	caseby	caseby	ADJ
cana-2991	181	6	-	-	PUNCT
cana-2991	181	7	case	case	NOUN
cana-2991	181	8	processing	processing	NOUN
cana-2991	181	9	methods	method	NOUN
cana-2991	181	10	●	●	NOUN
cana-2991	181	11	zero	zero	NUM
cana-2991	181	12	-	-	PUNCT
cana-2991	181	13	shot	shot	NOUN
cana-2991	181	14	prompting	prompt	VERB
cana-2991	181	15	for	for	ADP
cana-2991	181	16	fair	fair	ADJ
cana-2991	181	17	model	model	NOUN
cana-2991	181	18	comparison	comparison	NOUN
cana-2991	181	19	●	●	PUNCT
cana-2991	181	20	highparameter	highparameter	NOUN
cana-2991	181	21	llms	llm	NOUN
cana-2991	181	22	effective	effective	ADJ
cana-2991	181	23	in	in	ADP
cana-2991	181	24	detecting	detect	VERB
cana-2991	181	25	fake	fake	ADJ
cana-2991	181	26	news	news	NOUN
cana-2991	181	27	.	.	PUNCT
cana-2991	182	1	●	●	NUM
cana-2991	182	2	models	model	NOUN
cana-2991	182	3	with	with	ADP
cana-2991	182	4	more	more	ADJ
cana-2991	182	5	parameters	parameter	NOUN
cana-2991	182	6	outperform	outperform	VERB
cana-2991	182	7	those	those	PRON
cana-2991	182	8	with	with	ADP
cana-2991	182	9	fewer	few	ADJ
cana-2991	182	10	.	.	PUNCT
cana-2991	183	1	●	●	PUNCT
cana-2991	183	2	need	need	NOUN
cana-2991	183	3	for	for	ADP
cana-2991	183	4	larger	large	ADJ
cana-2991	183	5	,	,	PUNCT
cana-2991	183	6	diverse	diverse	ADJ
cana-2991	183	7	datasets	dataset	NOUN
cana-2991	183	8	to	to	PART
cana-2991	183	9	challenge	challenge	VERB
cana-2991	183	10	advanced	advanced	ADJ
cana-2991	183	11	models	model	NOUN
cana-2991	183	12	.	.	PUNCT
cana-2991	184	1	●	●	PUNCT
cana-2991	184	2	integration	integration	NOUN
cana-2991	184	3	of	of	ADP
cana-2991	184	4	contextual	contextual	ADJ
cana-2991	184	5	and	and	CCONJ
cana-2991	184	6	source	source	VERB
cana-2991	184	7	credibility	credibility	NOUN
cana-2991	184	8	analysis	analysis	NOUN
cana-2991	184	9	for	for	ADP
cana-2991	184	10	improvement	improvement	NOUN
cana-2991	184	11	.	.	PUNCT
cana-2991	185	1	[	[	X
cana-2991	185	2	14	14	NUM
cana-2991	185	3	]	]	SYM
cana-2991	185	4	●	●	PUNCT
cana-2991	185	5	evaluate	evaluate	VERB
cana-2991	185	6	chatgpt	chatgpt	NOUN
cana-2991	185	7	and	and	CCONJ
cana-2991	185	8	google	google	PROPN
cana-2991	185	9	gemini	gemini	PROPN
cana-2991	185	10	models	model	NOUN
cana-2991	185	11	for	for	ADP
cana-2991	185	12	fake	fake	ADJ
cana-2991	185	13	news	news	NOUN
cana-2991	185	14	detection	detection	NOUN
cana-2991	185	15	.	.	PUNCT
cana-2991	186	1	●	●	PUNCT
cana-2991	186	2	analyze	analyze	NOUN
cana-2991	186	3	strengths	strength	NOUN
cana-2991	186	4	and	and	CCONJ
cana-2991	186	5	limitations	limitation	NOUN
cana-2991	186	6	of	of	ADP
cana-2991	186	7	each	each	DET
cana-2991	186	8	model	model	NOUN
cana-2991	186	9	for	for	ADP
cana-2991	186	10	future	future	ADJ
cana-2991	186	11	enhancements	enhancement	NOUN
cana-2991	186	12	.	.	PUNCT
cana-2991	187	1	●	●	PUNCT
cana-2991	187	2	evaluation	evaluation	NOUN
cana-2991	187	3	of	of	ADP
cana-2991	187	4	chatgpt	chatgpt	NOUN
cana-2991	187	5	and	and	CCONJ
cana-2991	187	6	google	google	PROPN
cana-2991	187	7	gemini	gemini	PROPN
cana-2991	187	8	models	model	NOUN
cana-2991	187	9	●	●	PUNCT
cana-2991	187	10	comparative	comparative	ADJ
cana-2991	187	11	analysis	analysis	NOUN
cana-2991	187	12	and	and	CCONJ
cana-2991	187	13	error	error	NOUN
cana-2991	187	14	examination	examination	NOUN
cana-2991	187	15	of	of	ADP
cana-2991	187	16	model	model	NOUN
cana-2991	187	17	strengths	strength	NOUN
cana-2991	187	18	and	and	CCONJ
cana-2991	187	19	limitations	limitation	NOUN
cana-2991	187	20	●	●	NUM
cana-2991	187	21	high	high	ADJ
cana-2991	187	22	performance	performance	NOUN
cana-2991	187	23	metrics	metric	NOUN
cana-2991	187	24	on	on	ADP
cana-2991	187	25	liar	liar	NOUN
cana-2991	187	26	dataset	dataset	VERB
cana-2991	187	27	●	●	PUNCT
cana-2991	187	28	chatgpt	chatgpt	NOUN
cana-2991	187	29	and	and	CCONJ
cana-2991	187	30	google	google	PROPN
cana-2991	187	31	gemini	gemini	PROPN
cana-2991	187	32	models	model	NOUN
cana-2991	187	33	show	show	VERB
cana-2991	187	34	substantial	substantial	ADJ
cana-2991	187	35	capabilities	capability	NOUN
cana-2991	187	36	●	●	PUNCT
cana-2991	187	37	comparative	comparative	ADJ
cana-2991	187	38	analysis	analysis	NOUN
cana-2991	187	39	highlights	highlight	NOUN
cana-2991	187	40	strengths	strength	NOUN
cana-2991	187	41	and	and	CCONJ
cana-2991	187	42	limitations	limitation	NOUN
cana-2991	187	43	of	of	ADP
cana-2991	187	44	each	each	DET
cana-2991	187	45	model	model	NOUN
cana-2991	187	46	.	.	PUNCT
cana-2991	188	1	●	●	PUNCT
cana-2991	188	2	insights	insight	NOUN
cana-2991	188	3	provided	provide	VERB
cana-2991	188	4	for	for	ADP
cana-2991	188	5	future	future	ADJ
cana-2991	188	6	enhancements	enhancement	NOUN
cana-2991	188	7	in	in	ADP
cana-2991	188	8	fake	fake	ADJ
cana-2991	188	9	news	news	NOUN
cana-2991	188	10	detection	detection	NOUN
cana-2991	188	11	.	.	PUNCT
cana-2991	189	1	table	table	NOUN
cana-2991	189	2	1	1	NUM
cana-2991	189	3	.	.	PUNCT
cana-2991	190	1	literature	literature	PROPN
cana-2991	190	2	review	review	VERB
cana-2991	190	3	comparison	comparison	NOUN
cana-2991	190	4	of	of	ADP
cana-2991	190	5	the	the	DET
cana-2991	190	6	models	model	NOUN
cana-2991	190	7	in	in	ADP
cana-2991	190	8	experimental	experimental	ADJ
cana-2991	190	9	comparison	comparison	NOUN
cana-2991	190	10	amongst	amongst	ADP
cana-2991	190	11	embedding	embed	VERB
cana-2991	190	12	from	from	ADP
cana-2991	190	13	diverse	diverse	ADJ
cana-2991	190	14	models	model	NOUN
cana-2991	190	15	,	,	PUNCT
cana-2991	190	16	it	it	PRON
cana-2991	190	17	was	be	AUX
cana-2991	190	18	noticed	notice	VERB
cana-2991	190	19	that	that	SCONJ
cana-2991	190	20	deep	deep	ADJ
cana-2991	190	21	learning	learning	NOUN
cana-2991	190	22	based	base	VERB
cana-2991	190	23	models	model	NOUN
cana-2991	190	24	with	with	ADP
cana-2991	190	25	bert	bert	PROPN
cana-2991	190	26	and	and	CCONJ
cana-2991	190	27	word2vec	word2vec	AUX
cana-2991	190	28	as	as	SCONJ
cana-2991	190	29	embeddings	embeddings	NOUN
cana-2991	190	30	yields	yield	VERB
cana-2991	190	31	better	well	ADJ
cana-2991	190	32	accuracy	accuracy	NOUN
cana-2991	190	33	than	than	ADP
cana-2991	190	34	traditional	traditional	ADJ
cana-2991	190	35	methodologies	methodology	NOUN
cana-2991	190	36	like	like	ADP
cana-2991	190	37	bow	bow	NOUN
cana-2991	190	38	and	and	CCONJ
cana-2991	190	39	tf	tf	PROPN
cana-2991	190	40	-	-	PUNCT
cana-2991	190	41	idf	idf	PROPN
cana-2991	190	42	in	in	ADP
cana-2991	190	43	tackling	tackle	VERB
cana-2991	190	44	detection	detection	NOUN
cana-2991	190	45	of	of	ADP
cana-2991	190	46	fake	fake	ADJ
cana-2991	190	47	news	news	NOUN
cana-2991	190	48	.	.	PUNCT
cana-2991	191	1	hauschild	hauschild	PROPN
cana-2991	191	2	&	&	CCONJ
cana-2991	191	3	eskridge	eskridge	PROPN
cana-2991	191	4	2024	2024	NUM
cana-2991	191	5	)	)	PUNCT
cana-2991	191	6	performed	perform	VERB
cana-2991	191	7	the	the	DET
cana-2991	191	8	same	same	ADJ
cana-2991	191	9	comparison	comparison	NOUN
cana-2991	191	10	on	on	ADP
cana-2991	191	11	the	the	DET
cana-2991	191	12	liar	liar	NOUN
cana-2991	191	13	dataset	dataset	NOUN
cana-2991	191	14	,	,	PUNCT
cana-2991	191	15	and	and	CCONJ
cana-2991	191	16	found	find	VERB
cana-2991	191	17	bert	bert	PROPN
cana-2991	191	18	had	have	VERB
cana-2991	191	19	better	well	ADJ
cana-2991	191	20	average	average	ADJ
cana-2991	191	21	accuracy	accuracy	NOUN
cana-2991	191	22	as	as	ADV
cana-2991	191	23	well	well	ADV
cana-2991	191	24	as	as	ADP
cana-2991	191	25	recall	recall	NOUN
cana-2991	191	26	than	than	ADP
cana-2991	191	27	other	other	ADJ
cana-2991	191	28	embeddings	embedding	NOUN
cana-2991	191	29	.	.	PUNCT
cana-2991	192	1	bert	bert	PROPN
cana-2991	192	2	works	work	VERB
cana-2991	192	3	really	really	ADV
cana-2991	192	4	well	well	ADV
cana-2991	192	5	on	on	ADP
cana-2991	192	6	this	this	DET
cana-2991	192	7	problem	problem	NOUN
cana-2991	192	8	because	because	SCONJ
cana-2991	192	9	bert	bert	PROPN
cana-2991	192	10	is	be	AUX
cana-2991	192	11	able	able	ADJ
cana-2991	192	12	to	to	PART
cana-2991	192	13	capture	capture	VERB
cana-2991	192	14	some	some	PRON
cana-2991	192	15	of	of	ADP
cana-2991	192	16	the	the	DET
cana-2991	192	17	long	long	ADJ
cana-2991	192	18	-	-	PUNCT
cana-2991	192	19	distance	distance	NOUN
cana-2991	192	20	contextual	contextual	ADJ
cana-2991	192	21	dependencies	dependency	NOUN
cana-2991	192	22	between	between	ADP
cana-2991	192	23	the	the	DET
cana-2991	192	24	words	word	NOUN
cana-2991	192	25	,	,	PUNCT
cana-2991	192	26	which	which	PRON
cana-2991	192	27	is	be	AUX
cana-2991	192	28	often	often	ADV
cana-2991	192	29	necessary	necessary	ADJ
cana-2991	192	30	to	to	PART
cana-2991	192	31	identify	identify	VERB
cana-2991	192	32	subtle	subtle	ADJ
cana-2991	192	33	manipulations	manipulation	NOUN
cana-2991	192	34	of	of	ADP
cana-2991	192	35	facts	fact	NOUN
cana-2991	192	36	typical	typical	ADJ
cana-2991	192	37	in	in	ADP
cana-2991	192	38	fake	fake	ADJ
cana-2991	192	39	news	news	NOUN
cana-2991	192	40	articles	article	NOUN
cana-2991	192	41	.	.	PUNCT
cana-2991	193	1	although	although	SCONJ
cana-2991	193	2	deep	deep	ADJ
cana-2991	193	3	learning	learning	NOUN
cana-2991	193	4	models	model	NOUN
cana-2991	193	5	provide	provide	VERB
cana-2991	193	6	better	well	ADJ
cana-2991	193	7	accuracy	accuracy	NOUN
cana-2991	193	8	,	,	PUNCT
cana-2991	193	9	it	it	PRON
cana-2991	193	10	is	be	AUX
cana-2991	193	11	computationally	computationally	ADV
cana-2991	193	12	expensive	expensive	ADJ
cana-2991	193	13	.	.	PUNCT
cana-2991	194	1	the	the	DET
cana-2991	194	2	training	training	NOUN
cana-2991	194	3	of	of	ADP
cana-2991	194	4	models	model	NOUN
cana-2991	194	5	like	like	ADP
cana-2991	194	6	bert	bert	PROPN
cana-2991	194	7	is	be	AUX
cana-2991	194	8	computationally	computationally	ADV
cana-2991	194	9	intensive	intensive	ADJ
cana-2991	194	10	and	and	CCONJ
cana-2991	194	11	requires	require	VERB
cana-2991	194	12	an	an	DET
cana-2991	194	13	excessive	excessive	ADJ
cana-2991	194	14	amount	amount	NOUN
cana-2991	194	15	of	of	ADP
cana-2991	194	16	memory	memory	NOUN
cana-2991	194	17	that	that	PRON
cana-2991	194	18	may	may	AUX
cana-2991	194	19	exceed	exceed	VERB
cana-2991	194	20	resource	resource	NOUN
cana-2991	194	21	capacity	capacity	NOUN
cana-2991	194	22	for	for	ADP
cana-2991	194	23	many	many	ADJ
cana-2991	194	24	companies	company	NOUN
cana-2991	194	25	or	or	CCONJ
cana-2991	194	26	organizations	organization	NOUN
cana-2991	194	27	,	,	PUNCT
cana-2991	194	28	especially	especially	ADV
cana-2991	194	29	in	in	ADP
cana-2991	194	30	the	the	DET
cana-2991	194	31	case	case	NOUN
cana-2991	194	32	where	where	SCONJ
cana-2991	194	33	realcommunications	realcommunication	NOUN
cana-2991	194	34	on	on	ADP
cana-2991	194	35	applied	apply	VERB
cana-2991	194	36	nonlinear	nonlinear	ADJ
cana-2991	194	37	analysis	analysis	NOUN
cana-2991	194	38	issn	issn	NOUN
cana-2991	194	39	:	:	PUNCT
cana-2991	194	40	1074	1074	NUM
cana-2991	194	41	-	-	PUNCT
cana-2991	194	42	133x	133x	NUM
cana-2991	194	43	vol	vol	NOUN
cana-2991	194	44	32	32	NUM
cana-2991	194	45	no	no	NOUN
cana-2991	194	46	.	.	PUNCT
cana-2991	195	1	5s	5s	NUM
cana-2991	195	2	(	(	PUNCT
cana-2991	195	3	2025	2025	NUM
cana-2991	195	4	)	)	PUNCT
cana-2991	195	5	160	160	NUM
cana-2991	195	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-2991	195	7	time	time	NOUN
cana-2991	195	8	applications	application	NOUN
cana-2991	195	9	are	be	AUX
cana-2991	195	10	involved	involve	VERB
cana-2991	195	11	.	.	PUNCT
cana-2991	196	1	as	as	ADP
cana-2991	196	2	a	a	DET
cana-2991	196	3	result	result	NOUN
cana-2991	196	4	,	,	PUNCT
cana-2991	196	5	many	many	ADJ
cana-2991	196	6	have	have	AUX
cana-2991	196	7	become	become	VERB
cana-2991	196	8	interested	interested	ADJ
cana-2991	196	9	in	in	ADP
cana-2991	196	10	investigating	investigate	VERB
cana-2991	196	11	the	the	DET
cana-2991	196	12	tradeoffs	tradeoff	NOUN
cana-2991	196	13	between	between	ADP
cana-2991	196	14	model	model	NOUN
cana-2991	196	15	complexity	complexity	NOUN
cana-2991	196	16	and	and	CCONJ
cana-2991	196	17	computational	computational	ADJ
cana-2991	196	18	efficiency	efficiency	NOUN
cana-2991	196	19	.	.	PUNCT
cana-2991	197	1	the	the	DET
cana-2991	197	2	proposed	propose	VERB
cana-2991	197	3	study	study	NOUN
cana-2991	197	4	fits	fit	VERB
cana-2991	197	5	in	in	ADP
cana-2991	197	6	this	this	DET
cana-2991	197	7	body	body	NOUN
cana-2991	197	8	of	of	ADP
cana-2991	197	9	work	work	NOUN
cana-2991	197	10	meticulously	meticulously	ADV
cana-2991	197	11	,	,	PUNCT
cana-2991	197	12	by	by	ADP
cana-2991	197	13	both	both	PRON
cana-2991	197	14	employing	employ	VERB
cana-2991	197	15	sophisticated	sophisticated	ADJ
cana-2991	197	16	models	model	NOUN
cana-2991	197	17	(	(	PUNCT
cana-2991	197	18	bert	bert	PROPN
cana-2991	197	19	)	)	PUNCT
cana-2991	197	20	and	and	CCONJ
cana-2991	197	21	analyzing	analyze	VERB
cana-2991	197	22	the	the	DET
cana-2991	197	23	effects	effect	NOUN
cana-2991	197	24	of	of	ADP
cana-2991	197	25	pre	pre	ADJ
cana-2991	197	26	-	-	ADJ
cana-2991	197	27	processing	processing	ADJ
cana-2991	197	28	techniques	technique	NOUN
cana-2991	197	29	:	:	PUNCT
cana-2991	197	30	stop	stop	VERB
cana-2991	197	31	-	-	PUNCT
cana-2991	197	32	word	word	NOUN
cana-2991	197	33	removal	removal	NOUN
cana-2991	197	34	,	,	PUNCT
cana-2991	197	35	tokenization	tokenization	NOUN
cana-2991	197	36	,	,	PUNCT
cana-2991	197	37	stemming	stem	VERB
cana-2991	197	38	on	on	ADP
cana-2991	197	39	classification	classification	NOUN
cana-2991	197	40	outcome	outcome	NOUN
cana-2991	197	41	.	.	PUNCT
cana-2991	198	1	the	the	DET
cana-2991	198	2	results	result	NOUN
cana-2991	198	3	seem	seem	VERB
cana-2991	198	4	to	to	PART
cana-2991	198	5	suggest	suggest	VERB
cana-2991	198	6	that	that	SCONJ
cana-2991	198	7	preprocessing	preprocesse	VERB
cana-2991	198	8	steps	step	NOUN
cana-2991	198	9	can	can	AUX
cana-2991	198	10	have	have	AUX
cana-2991	198	11	wildly	wildly	ADV
cana-2991	198	12	differing	differ	VERB
cana-2991	198	13	outcomes	outcome	NOUN
cana-2991	198	14	on	on	ADP
cana-2991	198	15	the	the	DET
cana-2991	198	16	model	model	NOUN
cana-2991	198	17	,	,	PUNCT
cana-2991	198	18	and	and	CCONJ
cana-2991	198	19	that	that	SCONJ
cana-2991	198	20	for	for	ADP
cana-2991	198	21	certain	certain	ADJ
cana-2991	198	22	models	model	NOUN
cana-2991	198	23	where	where	SCONJ
cana-2991	198	24	context	context	NOUN
cana-2991	198	25	is	be	AUX
cana-2991	198	26	key	key	ADJ
cana-2991	198	27	for	for	ADP
cana-2991	198	28	determining	determine	VERB
cana-2991	198	29	a	a	DET
cana-2991	198	30	piece	piece	NOUN
cana-2991	198	31	of	of	ADP
cana-2991	198	32	fake	fake	ADJ
cana-2991	198	33	news	news	NOUN
cana-2991	198	34	,	,	PUNCT
cana-2991	198	35	they	they	PRON
cana-2991	198	36	should	should	AUX
cana-2991	198	37	not	not	PART
cana-2991	198	38	be	be	AUX
cana-2991	198	39	done	do	VERB
cana-2991	198	40	.	.	PUNCT
cana-2991	199	1	the	the	DET
cana-2991	199	2	previous	previous	ADJ
cana-2991	199	3	articles	article	NOUN
cana-2991	199	4	on	on	ADP
cana-2991	199	5	fake	fake	ADJ
cana-2991	199	6	news	news	NOUN
cana-2991	199	7	detection	detection	NOUN
cana-2991	199	8	:	:	PUNCT
cana-2991	199	9	from	from	ADP
cana-2991	199	10	simple	simple	ADJ
cana-2991	199	11	stylistic	stylistic	ADJ
cana-2991	199	12	based	base	VERB
cana-2991	199	13	approaches	approach	NOUN
cana-2991	199	14	to	to	ADP
cana-2991	199	15	sophisticated	sophisticated	ADJ
cana-2991	199	16	deep	deep	ADJ
cana-2991	199	17	learning	learning	NOUN
cana-2991	199	18	models	model	NOUN
cana-2991	199	19	using	use	VERB
cana-2991	199	20	word	word	NOUN
cana-2991	199	21	embeddings	embedding	NOUN
cana-2991	199	22	and	and	CCONJ
cana-2991	199	23	contextual	contextual	ADJ
cana-2991	199	24	information	information	NOUN
cana-2991	199	25	in	in	ADP
cana-2991	199	26	fact	fact	NOUN
cana-2991	199	27	,	,	PUNCT
cana-2991	199	28	with	with	ADP
cana-2991	199	29	all	all	DET
cana-2991	199	30	social	social	ADJ
cana-2991	199	31	media	medium	NOUN
cana-2991	199	32	and	and	CCONJ
cana-2991	199	33	news	news	NOUN
cana-2991	199	34	outlets	outlet	NOUN
cana-2991	199	35	contributing	contribute	VERB
cana-2991	199	36	to	to	ADP
cana-2991	199	37	more	more	ADJ
cana-2991	199	38	data	datum	NOUN
cana-2991	199	39	than	than	SCONJ
cana-2991	199	40	we	we	PRON
cana-2991	199	41	can	can	AUX
cana-2991	199	42	imagine	imagine	VERB
cana-2991	199	43	causing	cause	VERB
cana-2991	199	44	a	a	DET
cana-2991	199	45	considerable	considerable	ADJ
cana-2991	199	46	push	push	NOUN
cana-2991	199	47	for	for	ADP
cana-2991	199	48	interoperability	interoperability	NOUN
cana-2991	199	49	on	on	ADP
cana-2991	199	50	scalability	scalability	NOUN
cana-2991	199	51	of	of	ADP
cana-2991	199	52	these	these	DET
cana-2991	199	53	models	model	NOUN
cana-2991	199	54	.	.	PUNCT
cana-2991	200	1	in	in	ADP
cana-2991	200	2	this	this	DET
cana-2991	200	3	paper	paper	NOUN
cana-2991	200	4	,	,	PUNCT
cana-2991	200	5	we	we	PRON
cana-2991	200	6	go	go	VERB
cana-2991	200	7	beyond	beyond	ADP
cana-2991	200	8	these	these	DET
cana-2991	200	9	approaches	approach	NOUN
cana-2991	200	10	by	by	ADP
cana-2991	200	11	constructing	construct	VERB
cana-2991	200	12	a	a	DET
cana-2991	200	13	scalable	scalable	ADJ
cana-2991	200	14	solution	solution	NOUN
cana-2991	200	15	for	for	ADP
cana-2991	200	16	fake	fake	ADJ
cana-2991	200	17	news	news	NOUN
cana-2991	200	18	detection	detection	NOUN
cana-2991	200	19	using	use	VERB
cana-2991	200	20	word	word	NOUN
cana-2991	200	21	embedding	embed	VERB
cana-2991	200	22	models	model	NOUN
cana-2991	200	23	and	and	CCONJ
cana-2991	200	24	distributed	distribute	VERB
cana-2991	200	25	processing	processing	NOUN
cana-2991	200	26	frameworks[41	frameworks[41	NOUN
cana-2991	200	27	-	-	PUNCT
cana-2991	200	28	59	59	NUM
cana-2991	200	29	]	]	PUNCT
cana-2991	200	30	.	.	PUNCT
cana-2991	201	1	this	this	DET
cana-2991	201	2	work	work	NOUN
cana-2991	201	3	provides	provide	VERB
cana-2991	201	4	important	important	ADJ
cana-2991	201	5	guidance	guidance	NOUN
cana-2991	201	6	in	in	ADP
cana-2991	201	7	large	large	ADJ
cana-2991	201	8	-	-	PUNCT
cana-2991	201	9	scale	scale	NOUN
cana-2991	201	10	automatic	automatic	ADJ
cana-2991	201	11	fake	fake	ADJ
cana-2991	201	12	news	news	NOUN
cana-2991	201	13	detection	detection	NOUN
cana-2991	201	14	systems	system	NOUN
cana-2991	201	15	by	by	ADP
cana-2991	201	16	comparing	compare	VERB
cana-2991	201	17	model	model	NOUN
cana-2991	201	18	complexity	complexity	NOUN
cana-2991	201	19	,	,	PUNCT
cana-2991	201	20	computational	computational	ADJ
cana-2991	201	21	efficiency	efficiency	NOUN
cana-2991	201	22	,	,	PUNCT
cana-2991	201	23	and	and	CCONJ
cana-2991	201	24	classification	classification	NOUN
cana-2991	201	25	accuracy	accuracy	NOUN
cana-2991	201	26	trade	trade	NOUN
cana-2991	201	27	-	-	PUNCT
cana-2991	201	28	offs	off	NOUN
cana-2991	201	29	.	.	PUNCT
cana-2991	202	1	2	2	X
cana-2991	202	2	.	.	NUM
cana-2991	202	3	proposed	propose	VERB
cana-2991	202	4	methodology	methodology	NOUN
cana-2991	202	5	scaling	scale	VERB
cana-2991	202	6	fake	fake	ADJ
cana-2991	202	7	news	news	NOUN
cana-2991	202	8	detection	detection	NOUN
cana-2991	202	9	:	:	PUNCT
cana-2991	202	10	a	a	DET
cana-2991	202	11	proposed	propose	VERB
cana-2991	202	12	methodology	methodology	NOUN
cana-2991	202	13	(	(	PUNCT
cana-2991	202	14	nlp	nlp	NOUN
cana-2991	202	15	and	and	CCONJ
cana-2991	202	16	word	word	NOUN
cana-2991	202	17	embeddings	embedding	NOUN
cana-2991	202	18	)	)	PUNCT
cana-2991	202	19	based	base	VERB
cana-2991	202	20	on	on	ADP
cana-2991	202	21	stateof	stateof	ADJ
cana-2991	202	22	-	-	PUNCT
cana-2991	202	23	the	the	DET
cana-2991	202	24	-	-	PUNCT
cana-2991	202	25	art	art	NOUN
cana-2991	202	26	text	text	NOUN
cana-2991	202	27	classification	classification	NOUN
cana-2991	202	28	techniques	technique	NOUN
cana-2991	202	29	,	,	PUNCT
cana-2991	202	30	the	the	DET
cana-2991	202	31	approach	approach	NOUN
cana-2991	202	32	is	be	AUX
cana-2991	202	33	designed	design	VERB
cana-2991	202	34	for	for	ADP
cana-2991	202	35	scalability	scalability	NOUN
cana-2991	202	36	in	in	ADP
cana-2991	202	37	practice	practice	NOUN
cana-2991	202	38	and	and	CCONJ
cana-2991	202	39	ability	ability	NOUN
cana-2991	202	40	to	to	PART
cana-2991	202	41	process	process	VERB
cana-2991	202	42	large	large	ADJ
cana-2991	202	43	-	-	PUNCT
cana-2991	202	44	scale	scale	NOUN
cana-2991	202	45	datasets	dataset	NOUN
cana-2991	202	46	in	in	ADP
cana-2991	202	47	real	real	ADJ
cana-2991	202	48	-	-	PUNCT
cana-2991	202	49	time	time	NOUN
cana-2991	202	50	environments	environment	NOUN
cana-2991	202	51	.	.	PUNCT
cana-2991	203	1	the	the	DET
cana-2991	203	2	framework	framework	NOUN
cana-2991	203	3	comprises	comprise	VERB
cana-2991	203	4	a	a	DET
cana-2991	203	5	set	set	NOUN
cana-2991	203	6	of	of	ADP
cana-2991	203	7	components	component	NOUN
cana-2991	203	8	such	such	ADJ
cana-2991	203	9	as	as	ADP
cana-2991	203	10	data	data	NOUN
cana-2991	203	11	preprocessing	preprocessing	NOUN
cana-2991	203	12	techniques	technique	NOUN
cana-2991	203	13	,	,	PUNCT
cana-2991	203	14	word	word	NOUN
cana-2991	203	15	embedding	embed	VERB
cana-2991	203	16	models	model	NOUN
cana-2991	203	17	,	,	PUNCT
cana-2991	203	18	machine	machine	NOUN
cana-2991	203	19	learning	learn	VERB
cana-2991	203	20	classifiers	classifier	NOUN
cana-2991	203	21	and	and	CCONJ
cana-2991	203	22	distributed	distribute	VERB
cana-2991	203	23	processing	processing	NOUN
cana-2991	203	24	frameworks	framework	NOUN
cana-2991	203	25	.	.	PUNCT
cana-2991	204	1	hereafter	hereafter	ADV
cana-2991	204	2	,	,	PUNCT
cana-2991	204	3	an	an	DET
cana-2991	204	4	elaborate	elaborate	ADJ
cana-2991	204	5	explanation	explanation	NOUN
cana-2991	204	6	shall	shall	AUX
cana-2991	204	7	be	be	AUX
cana-2991	204	8	given	give	VERB
cana-2991	204	9	for	for	ADP
cana-2991	204	10	each	each	DET
cana-2991	204	11	component	component	NOUN
cana-2991	204	12	,	,	PUNCT
cana-2991	204	13	then	then	ADV
cana-2991	204	14	the	the	DET
cana-2991	204	15	experiments	experiment	NOUN
cana-2991	204	16	and	and	CCONJ
cana-2991	204	17	used	use	VERB
cana-2991	204	18	evaluation	evaluation	NOUN
cana-2991	204	19	metrics	metric	NOUN
cana-2991	204	20	to	to	PART
cana-2991	204	21	assess	assess	VERB
cana-2991	204	22	the	the	DET
cana-2991	204	23	performance	performance	NOUN
cana-2991	204	24	of	of	ADP
cana-2991	204	25	the	the	DET
cana-2991	204	26	system	system	NOUN
cana-2991	204	27	.	.	PUNCT
cana-2991	205	1	the	the	DET
cana-2991	205	2	architecture	architecture	NOUN
cana-2991	205	3	of	of	ADP
cana-2991	205	4	the	the	DET
cana-2991	205	5	fake	fake	ADJ
cana-2991	205	6	news	news	NOUN
cana-2991	205	7	detection	detection	NOUN
cana-2991	205	8	system	system	NOUN
cana-2991	205	9	embedding	embed	VERB
cana-2991	205	10	model	model	NOUN
cana-2991	205	11	is	be	AUX
cana-2991	205	12	shown	show	VERB
cana-2991	205	13	in	in	ADP
cana-2991	205	14	fig	fig	NOUN
cana-2991	205	15	.	.	PUNCT
cana-2991	206	1	3	3	X
cana-2991	206	2	.	.	X
cana-2991	206	3	it	it	PRON
cana-2991	206	4	is	be	AUX
cana-2991	206	5	made	make	VERB
cana-2991	206	6	of	of	ADP
cana-2991	206	7	four	four	NUM
cana-2991	206	8	main	main	ADJ
cana-2991	206	9	stages	stage	NOUN
cana-2991	206	10	;	;	PUNCT
cana-2991	206	11	●	●	NUM
cana-2991	206	12	data	datum	NOUN
cana-2991	206	13	preprocessing	preprocessing	NOUN
cana-2991	206	14	:	:	PUNCT
cana-2991	206	15	this	this	PRON
cana-2991	206	16	is	be	AUX
cana-2991	206	17	the	the	DET
cana-2991	206	18	phase	phase	NOUN
cana-2991	206	19	where	where	SCONJ
cana-2991	206	20	we	we	PRON
cana-2991	206	21	go	go	VERB
cana-2991	206	22	about	about	ADP
cana-2991	206	23	cleaning	clean	VERB
cana-2991	206	24	the	the	DET
cana-2991	206	25	raw	raw	ADJ
cana-2991	206	26	textual	textual	ADJ
cana-2991	206	27	data	datum	NOUN
cana-2991	206	28	so	so	SCONJ
cana-2991	206	29	that	that	SCONJ
cana-2991	206	30	it	it	PRON
cana-2991	206	31	can	can	AUX
cana-2991	206	32	be	be	AUX
cana-2991	206	33	useful	useful	ADJ
cana-2991	206	34	for	for	ADP
cana-2991	206	35	further	further	ADJ
cana-2991	206	36	analysis	analysis	NOUN
cana-2991	206	37	.	.	PUNCT
cana-2991	207	1	these	these	DET
cana-2991	207	2	steps	step	NOUN
cana-2991	207	3	involve	involve	VERB
cana-2991	207	4	such	such	ADJ
cana-2991	207	5	processes	process	NOUN
cana-2991	207	6	as	as	ADP
cana-2991	207	7	removing	remove	VERB
cana-2991	207	8	stop	stop	NOUN
cana-2991	207	9	-	-	PUNCT
cana-2991	207	10	words	word	NOUN
cana-2991	207	11	,	,	PUNCT
cana-2991	207	12	tokenizing	tokenize	VERB
cana-2991	207	13	the	the	DET
cana-2991	207	14	text	text	NOUN
cana-2991	207	15	,	,	PUNCT
cana-2991	207	16	lemmatizing	lemmatizing	NOUN
cana-2991	207	17	and	and	CCONJ
cana-2991	207	18	vectorizing	vectorize	VERB
cana-2991	207	19	it	it	PRON
cana-2991	207	20	.	.	PUNCT
cana-2991	208	1	●	●	PUNCT
cana-2991	208	2	word	word	NOUN
cana-2991	208	3	embedding	embed	VERB
cana-2991	208	4	models	model	NOUN
cana-2991	208	5	:	:	PUNCT
cana-2991	208	6	the	the	DET
cana-2991	208	7	cleaned	clean	VERB
cana-2991	208	8	text	text	NOUN
cana-2991	208	9	is	be	AUX
cana-2991	208	10	converted	convert	VERB
cana-2991	208	11	into	into	ADP
cana-2991	208	12	numbers	number	NOUN
cana-2991	208	13	by	by	ADP
cana-2991	208	14	the	the	DET
cana-2991	208	15	means	mean	NOUN
cana-2991	208	16	of	of	ADP
cana-2991	208	17	many	many	ADJ
cana-2991	208	18	word	word	NOUN
cana-2991	208	19	embedding	embed	VERB
cana-2991	208	20	model	model	NOUN
cana-2991	208	21	;	;	PUNCT
cana-2991	208	22	bag	bag	NOUN
cana-2991	208	23	of	of	ADP
cana-2991	208	24	words	word	NOUN
cana-2991	208	25	(	(	PUNCT
cana-2991	208	26	bow	bow	NOUN
cana-2991	208	27	)	)	PUNCT
cana-2991	208	28	,	,	PUNCT
cana-2991	208	29	term	term	NOUN
cana-2991	208	30	frequency	frequency	NOUN
cana-2991	208	31	-	-	PUNCT
cana-2991	208	32	inverse	inverse	NOUN
cana-2991	208	33	document	document	NOUN
cana-2991	208	34	frequency	frequency	NOUN
cana-2991	208	35	(	(	PUNCT
cana-2991	208	36	tfidf	tfidf	NOUN
cana-2991	208	37	)	)	PUNCT
cana-2991	208	38	,	,	PUNCT
cana-2991	208	39	word2vec	word2vec	X
cana-2991	208	40	,	,	PUNCT
cana-2991	208	41	bidirectional	bidirectional	ADJ
cana-2991	208	42	encoder	encoder	NOUN
cana-2991	208	43	representations	representation	VERB
cana-2991	208	44	from	from	ADP
cana-2991	208	45	transformers	transformer	NOUN
cana-2991	208	46	(	(	PUNCT
cana-2991	208	47	bert	bert	PROPN
cana-2991	208	48	)	)	PUNCT
cana-2991	208	49	etc	etc	X
cana-2991	208	50	.	.	X
cana-2991	209	1	●	●	PUNCT
cana-2991	209	2	machine	machine	NOUN
cana-2991	209	3	learning	learn	VERB
cana-2991	209	4	classification	classification	NOUN
cana-2991	209	5	:	:	PUNCT
cana-2991	209	6	in	in	ADP
cana-2991	209	7	this	this	DET
cana-2991	209	8	phase	phase	NOUN
cana-2991	209	9	,	,	PUNCT
cana-2991	209	10	we	we	PRON
cana-2991	209	11	train	train	VERB
cana-2991	209	12	different	different	ADJ
cana-2991	209	13	machine	machine	NOUN
cana-2991	209	14	learning	learn	VERB
cana-2991	209	15	classifiers	classifier	NOUN
cana-2991	209	16	namely	namely	ADV
cana-2991	209	17	logistic	logistic	ADJ
cana-2991	209	18	regression	regression	NOUN
cana-2991	209	19	,	,	PUNCT
cana-2991	209	20	random	random	ADJ
cana-2991	209	21	forests	forest	NOUN
cana-2991	209	22	and	and	CCONJ
cana-2991	209	23	neural	neural	ADJ
cana-2991	209	24	networks	network	NOUN
cana-2991	209	25	on	on	ADP
cana-2991	209	26	the	the	DET
cana-2991	209	27	embedded	embed	VERB
cana-2991	209	28	data	datum	NOUN
cana-2991	209	29	to	to	PART
cana-2991	209	30	predict	predict	VERB
cana-2991	209	31	whether	whether	SCONJ
cana-2991	209	32	the	the	DET
cana-2991	209	33	news	news	NOUN
cana-2991	209	34	is	be	AUX
cana-2991	209	35	real	real	ADJ
cana-2991	209	36	or	or	CCONJ
cana-2991	209	37	fake	fake	ADJ
cana-2991	209	38	.	.	PUNCT
cana-2991	210	1	●	●	NUM
cana-2991	210	2	distributed	distributed	ADJ
cana-2991	210	3	processing	processing	NOUN
cana-2991	210	4	:	:	PUNCT
cana-2991	210	5	high	high	ADJ
cana-2991	210	6	scalability	scalability	NOUN
cana-2991	210	7	by	by	ADP
cana-2991	210	8	incorporating	incorporate	VERB
cana-2991	210	9	distributed	distribute	VERB
cana-2991	210	10	processing	processing	NOUN
cana-2991	210	11	frameworks	framework	NOUN
cana-2991	210	12	like	like	ADP
cana-2991	210	13	apache	apache	NOUN
cana-2991	210	14	spark	spark	NOUN
cana-2991	210	15	for	for	ADP
cana-2991	210	16	handling	handle	VERB
cana-2991	210	17	large	large	ADJ
cana-2991	210	18	-	-	PUNCT
cana-2991	210	19	scale	scale	NOUN
cana-2991	210	20	datasets	dataset	NOUN
cana-2991	210	21	within	within	ADP
cana-2991	210	22	the	the	DET
cana-2991	210	23	system	system	NOUN
cana-2991	210	24	.	.	PUNCT
cana-2991	211	1	this	this	PRON
cana-2991	211	2	enables	enable	VERB
cana-2991	211	3	the	the	DET
cana-2991	211	4	model	model	NOUN
cana-2991	211	5	to	to	PART
cana-2991	211	6	execute	execute	VERB
cana-2991	211	7	data	datum	NOUN
cana-2991	211	8	in	in	ADP
cana-2991	211	9	a	a	DET
cana-2991	211	10	very	very	ADV
cana-2991	211	11	parallel	parallel	ADJ
cana-2991	211	12	fashion	fashion	NOUN
cana-2991	211	13	and	and	CCONJ
cana-2991	211	14	hence	hence	ADV
cana-2991	211	15	is	be	AUX
cana-2991	211	16	extremely	extremely	ADV
cana-2991	211	17	useful	useful	ADJ
cana-2991	211	18	for	for	ADP
cana-2991	211	19	training	training	NOUN
cana-2991	211	20	models	model	NOUN
cana-2991	211	21	on	on	ADP
cana-2991	211	22	highdimensional	highdimensional	NOUN
cana-2991	211	23	enter	enter	VERB
cana-2991	211	24	facts	fact	NOUN
cana-2991	211	25	.	.	PUNCT
cana-2991	212	1	communications	communication	NOUN
cana-2991	212	2	on	on	ADP
cana-2991	212	3	applied	apply	VERB
cana-2991	212	4	nonlinear	nonlinear	ADJ
cana-2991	212	5	analysis	analysis	NOUN
cana-2991	212	6	issn	issn	NOUN
cana-2991	212	7	:	:	PUNCT
cana-2991	212	8	1074	1074	NUM
cana-2991	212	9	-	-	PUNCT
cana-2991	212	10	133x	133x	NUM
cana-2991	212	11	vol	vol	NOUN
cana-2991	212	12	32	32	NUM
cana-2991	212	13	no	no	NOUN
cana-2991	212	14	.	.	PUNCT
cana-2991	213	1	5s	5s	NUM
cana-2991	213	2	(	(	PUNCT
cana-2991	213	3	2025	2025	NUM
cana-2991	213	4	)	)	PUNCT
cana-2991	213	5	161	161	NUM
cana-2991	213	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	213	7	1	1	X
cana-2991	213	8	.	.	PUNCT
cana-2991	214	1	data	datum	NOUN
cana-2991	214	2	preprocessing	preprocesse	VERB
cana-2991	214	3	we	we	PRON
cana-2991	214	4	do	do	AUX
cana-2991	214	5	preprocessing	preprocesse	VERB
cana-2991	214	6	to	to	PART
cana-2991	214	7	make	make	VERB
cana-2991	214	8	sure	sure	ADJ
cana-2991	214	9	that	that	SCONJ
cana-2991	214	10	the	the	DET
cana-2991	214	11	data	data	NOUN
cana-2991	214	12	is	be	AUX
cana-2991	214	13	in	in	ADP
cana-2991	214	14	a	a	DET
cana-2991	214	15	cleaner	clean	ADJ
cana-2991	214	16	and	and	CCONJ
cana-2991	214	17	structured	structured	ADJ
cana-2991	214	18	shape	shape	NOUN
cana-2991	214	19	so	so	SCONJ
cana-2991	214	20	the	the	DET
cana-2991	214	21	machine	machine	NOUN
cana-2991	214	22	learning	learning	NOUN
cana-2991	214	23	models	model	NOUN
cana-2991	214	24	can	can	AUX
cana-2991	214	25	understand	understand	VERB
cana-2991	214	26	it	it	PRON
cana-2991	214	27	directly	directly	ADV
cana-2991	214	28	.	.	PUNCT
cana-2991	215	1	in	in	ADP
cana-2991	215	2	this	this	DET
cana-2991	215	3	study	study	NOUN
cana-2991	215	4	,	,	PUNCT
cana-2991	215	5	we	we	PRON
cana-2991	215	6	process	process	VERB
cana-2991	215	7	the	the	DET
cana-2991	215	8	above	above	ADJ
cana-2991	215	9	textual	textual	ADJ
cana-2991	215	10	data	datum	NOUN
cana-2991	215	11	through	through	ADP
cana-2991	215	12	various	various	ADJ
cana-2991	215	13	steps	step	NOUN
cana-2991	215	14	as	as	ADP
cana-2991	215	15	:	:	PUNCT
cana-2991	215	16	1.1	1.1	NUM
cana-2991	215	17	.	.	PUNCT
cana-2991	216	1	tokenization	tokenization	NOUN
cana-2991	216	2	tokenization	tokenization	NOUN
cana-2991	216	3	:	:	PUNCT
cana-2991	216	4	split	split	VERB
cana-2991	216	5	the	the	DET
cana-2991	216	6	raw	raw	ADJ
cana-2991	216	7	text	text	NOUN
cana-2991	216	8	into	into	ADP
cana-2991	216	9	individual	individual	ADJ
cana-2991	216	10	words	word	NOUN
cana-2991	216	11	or	or	CCONJ
cana-2991	216	12	tokens	token	NOUN
cana-2991	216	13	.	.	PUNCT
cana-2991	217	1	for	for	ADP
cana-2991	217	2	a	a	DET
cana-2991	217	3	document	document	NOUN
cana-2991	217	4	𝐷	𝐷	NOUN
cana-2991	217	5	=	=	SYM
cana-2991	217	6	{	{	PUNCT
cana-2991	217	7	𝑑1	𝑑1	NOUN
cana-2991	217	8	,	,	PUNCT
cana-2991	217	9	𝑑2	𝑑2	NOUN
cana-2991	217	10	,	,	PUNCT
cana-2991	217	11	…	…	PUNCT
cana-2991	217	12	,	,	PUNCT
cana-2991	217	13	𝑑𝑛	𝑑𝑛	INTJ
cana-2991	217	14	}	}	PUNCT
cana-2991	217	15	where	where	SCONJ
cana-2991	217	16	d_i	d_i	PROPN
cana-2991	217	17	is	be	AUX
cana-2991	217	18	the	the	DET
cana-2991	217	19	i	i	PROPN
cana-2991	217	20	-	-	PUNCT
cana-2991	217	21	th	th	VERB
cana-2991	217	22	document	document	NOUN
cana-2991	217	23	in	in	ADP
cana-2991	217	24	the	the	DET
cana-2991	217	25	dataset	dataset	NOUN
cana-2991	217	26	,	,	PUNCT
cana-2991	217	27	tokenization	tokenization	NOUN
cana-2991	217	28	will	will	AUX
cana-2991	217	29	separate	separate	VERB
cana-2991	217	30	every	every	DET
cana-2991	217	31	document	document	NOUN
cana-2991	217	32	into	into	ADP
cana-2991	217	33	its	its	PRON
cana-2991	217	34	basic	basic	ADJ
cana-2991	217	35	words	word	NOUN
cana-2991	217	36	as	as	SCONJ
cana-2991	217	37	follows	follow	VERB
cana-2991	217	38	:	:	PUNCT
cana-2991	217	39	𝐷𝑖	𝐷𝑖	PROPN
cana-2991	217	40	=	=	SYM
cana-2991	217	41	{	{	PUNCT
cana-2991	217	42	𝑤1	𝑤1	VERB
cana-2991	217	43	,	,	PUNCT
cana-2991	217	44	𝑤2	𝑤2	NOUN
cana-2991	217	45	,	,	PUNCT
cana-2991	217	46	…	…	PUNCT
cana-2991	217	47	,	,	PUNCT
cana-2991	217	48	𝑤𝑚	𝑤𝑚	NOUN
cana-2991	217	49	}	}	PUNCT
cana-2991	217	50	the	the	DET
cana-2991	217	51	first	first	ADJ
cana-2991	217	52	step	step	NOUN
cana-2991	217	53	of	of	ADP
cana-2991	217	54	turning	turn	VERB
cana-2991	217	55	un	un	ADJ
cana-2991	217	56	-	-	ADJ
cana-2991	217	57	structured	structured	ADJ
cana-2991	217	58	text	text	NOUN
cana-2991	217	59	into	into	ADP
cana-2991	217	60	structured	structured	ADJ
cana-2991	217	61	data	datum	NOUN
cana-2991	217	62	is	be	AUX
cana-2991	217	63	tokenization	tokenization	NOUN
cana-2991	217	64	(	(	PUNCT
cana-2991	217	65	w_1	w_1	NOUN
cana-2991	217	66	,	,	PUNCT
cana-2991	217	67	w_2	w_2	PROPN
cana-2991	217	68	,	,	PUNCT
cana-2991	217	69	…	…	PUNCT
cana-2991	217	70	,	,	PUNCT
cana-2991	218	1	w_i	w_i	NUM
cana-2991	218	2	:	:	PUNCT
cana-2991	218	3	the	the	DET
cana-2991	218	4	i’th	i’th	ADJ
cana-2991	218	5	word	word	NOUN
cana-2991	218	6	in	in	ADP
cana-2991	218	7	document	document	NOUN
cana-2991	218	8	d_i	d_i	PROPN
cana-2991	218	9	.	.	PUNCT
cana-2991	218	10	)	)	PUNCT
cana-2991	218	11	.	.	PUNCT
cana-2991	219	1	1.2	1.2	NUM
cana-2991	219	2	.	.	X
cana-2991	219	3	stop	stop	VERB
cana-2991	219	4	-	-	PUNCT
cana-2991	219	5	word	word	NOUN
cana-2991	219	6	removal	removal	NOUN
cana-2991	219	7	stop	stop	NOUN
cana-2991	219	8	-	-	PUNCT
cana-2991	219	9	words	word	NOUN
cana-2991	219	10	are	be	AUX
cana-2991	219	11	the	the	DET
cana-2991	219	12	words	word	NOUN
cana-2991	219	13	which	which	PRON
cana-2991	219	14	usually	usually	ADV
cana-2991	219	15	do	do	AUX
cana-2991	219	16	not	not	PART
cana-2991	219	17	have	have	VERB
cana-2991	219	18	any	any	DET
cana-2991	219	19	semantic	semantic	ADJ
cana-2991	219	20	meaning	meaning	NOUN
cana-2991	219	21	and	and	CCONJ
cana-2991	219	22	could	could	AUX
cana-2991	219	23	introduce	introduce	VERB
cana-2991	219	24	noise	noise	NOUN
cana-2991	219	25	in	in	ADP
cana-2991	219	26	the	the	DET
cana-2991	219	27	model	model	NOUN
cana-2991	219	28	.	.	PUNCT
cana-2991	220	1	net	net	ADJ
cana-2991	220	2	effect	effect	NOUN
cana-2991	220	3	being	be	AUX
cana-2991	220	4	:	:	PUNCT
cana-2991	220	5	to	to	PART
cana-2991	220	6	reduce	reduce	VERB
cana-2991	220	7	the	the	DET
cana-2991	220	8	dimensionality	dimensionality	NOUN
cana-2991	220	9	and	and	CCONJ
cana-2991	220	10	thus	thus	ADV
cana-2991	220	11	make	make	VERB
cana-2991	220	12	model	model	NOUN
cana-2991	220	13	training	training	NOUN
cana-2991	220	14	easier	easy	ADJ
cana-2991	220	15	.	.	PUNCT
cana-2991	221	1	the	the	DET
cana-2991	221	2	resulting	result	VERB
cana-2991	221	3	document	document	NOUN
cana-2991	221	4	is	be	AUX
cana-2991	221	5	:	:	PUNCT
cana-2991	221	6	𝐷𝑖	𝐷𝑖	ADP
cana-2991	221	7	′	′	NOUN
cana-2991	221	8	=	=	PUNCT
cana-2991	221	9	{	{	PUNCT
cana-2991	221	10	𝑤1	𝑤1	VERB
cana-2991	221	11	′	′	NOUN
cana-2991	221	12	,	,	PUNCT
cana-2991	221	13	𝑤2	𝑤2	NOUN
cana-2991	221	14	′	′	NOUN
cana-2991	221	15	,	,	PUNCT
cana-2991	221	16	…	…	PUNCT
cana-2991	221	17	,	,	PUNCT
cana-2991	221	18	𝑤	𝑤	ADP
cana-2991	221	19	𝑚′	𝑚′	NUM
cana-2991	221	20	′	′	NUM
cana-2991	221	21	}	}	PUNCT
cana-2991	221	22	,	,	PUNCT
cana-2991	221	23	 	 	SPACE
cana-2991	221	24	𝑤𝑖	𝑤𝑖	ADP
cana-2991	221	25	′	′	NUM
cana-2991	221	26	∉	∉	PROPN
cana-2991	221	27	𝑆𝑡𝑜𝑝𝑊𝑜𝑟𝑑𝑠	𝑆𝑡𝑜𝑝𝑊𝑜𝑟𝑑𝑠	PROPN
cana-2991	221	28	for	for	ADP
cana-2991	221	29	each	each	DET
cana-2991	221	30	word	word	NOUN
cana-2991	221	31	w	w	ADP
cana-2991	221	32	i	i	PRON
cana-2991	221	33	in	in	ADP
cana-2991	221	34	document	document	NOUN
cana-2991	222	1	d	d	PROPN
cana-2991	222	2	i	i	PRON
cana-2991	222	3	,	,	PUNCT
cana-2991	222	4	where	where	SCONJ
cana-2991	222	5	d_i^	d_i^	X
cana-2991	222	6	'	'	PUNCT
cana-2991	222	7	is	be	AUX
cana-2991	222	8	the	the	DET
cana-2991	222	9	stop	stop	VERB
cana-2991	222	10	-	-	PUNCT
cana-2991	222	11	word	word	NOUN
cana-2991	222	12	removed	remove	VERB
cana-2991	222	13	document	document	NOUN
cana-2991	222	14	and	and	CCONJ
cana-2991	222	15	w_i^	w_i^	PRON
cana-2991	222	16	'	'	PUNCT
cana-2991	222	17	is	be	AUX
cana-2991	222	18	nonstop	nonstop	ADJ
cana-2991	222	19	-	-	PUNCT
cana-2991	222	20	word	word	NOUN
cana-2991	222	21	token	token	VERB
cana-2991	222	22	.	.	PUNCT
cana-2991	223	1	1.3	1.3	NUM
cana-2991	223	2	.	.	PUNCT
cana-2991	224	1	lemmatization	lemmatization	NOUN
cana-2991	224	2	and	and	CCONJ
cana-2991	224	3	stemming	stem	VERB
cana-2991	224	4	figure	figure	NOUN
cana-2991	224	5	3	3	NUM
cana-2991	224	6	.	.	PUNCT
cana-2991	224	7	flowchart	flowchart	NOUN
cana-2991	224	8	of	of	ADP
cana-2991	224	9	proposed	propose	VERB
cana-2991	224	10	methodology	methodology	NOUN
cana-2991	224	11	lemmatization	lemmatization	NOUN
cana-2991	224	12	is	be	AUX
cana-2991	224	13	the	the	DET
cana-2991	224	14	process	process	NOUN
cana-2991	224	15	of	of	ADP
cana-2991	224	16	converting	convert	VERB
cana-2991	224	17	words	word	NOUN
cana-2991	224	18	to	to	ADP
cana-2991	224	19	their	their	PRON
cana-2991	224	20	dictionary	dictionary	ADJ
cana-2991	224	21	or	or	CCONJ
cana-2991	224	22	base	base	NOUN
cana-2991	224	23	form	form	NOUN
cana-2991	224	24	(	(	PUNCT
cana-2991	224	25	i.e.	i.e.	X
cana-2991	224	26	lemma	lemma	PROPN
cana-2991	224	27	)	)	PUNCT
cana-2991	224	28	.	.	PUNCT
cana-2991	225	1	for	for	ADP
cana-2991	225	2	instance	instance	NOUN
cana-2991	225	3	,	,	PUNCT
cana-2991	225	4	"	"	PUNCT
cana-2991	225	5	run	run	VERB
cana-2991	225	6	"	"	PUNCT
cana-2991	225	7	,	,	PUNCT
cana-2991	225	8	names	name	NOUN
cana-2991	225	9	like	like	ADP
cana-2991	225	10	"	"	PUNCT
cana-2991	225	11	running	run	VERB
cana-2991	225	12	"	"	PUNCT
cana-2991	225	13	and	and	CCONJ
cana-2991	225	14	"	"	PUNCT
cana-2991	225	15	ran	ran	NOUN
cana-2991	225	16	"	"	PUNCT
cana-2991	225	17	are	be	AUX
cana-2991	225	18	made	make	VERB
cana-2991	225	19	all	all	PRON
cana-2991	225	20	to	to	ADP
cana-2991	225	21	the	the	DET
cana-2991	225	22	root	root	NOUN
cana-2991	225	23	form	form	NOUN
cana-2991	225	24	.	.	PUNCT
cana-2991	226	1	when	when	SCONJ
cana-2991	226	2	we	we	PRON
cana-2991	226	3	perform	perform	VERB
cana-2991	226	4	lemmatization	lemmatization	NOUN
cana-2991	226	5	,	,	PUNCT
cana-2991	226	6	the	the	DET
cana-2991	226	7	model	model	NOUN
cana-2991	226	8	will	will	AUX
cana-2991	226	9	consider	consider	VERB
cana-2991	226	10	different	different	ADJ
cana-2991	226	11	cases	case	NOUN
cana-2991	226	12	of	of	ADP
cana-2991	226	13	a	a	DET
cana-2991	226	14	word	word	NOUN
cana-2991	226	15	as	as	ADP
cana-2991	226	16	single	single	ADJ
cana-2991	226	17	submission	submission	NOUN
cana-2991	226	18	:	:	PUNCT
cana-2991	226	19	𝐿𝑒𝑚𝑚𝑎(𝑤𝑖	𝐿𝑒𝑚𝑚𝑎(𝑤𝑖	PROPN
cana-2991	226	20	)	)	PUNCT
cana-2991	226	21	=	=	PRON
cana-2991	226	22	{	{	PUNCT
cana-2991	226	23	𝑤𝑟𝑜𝑜𝑡	𝑤𝑟𝑜𝑜𝑡	NOUN
cana-2991	226	24	}	}	PUNCT
cana-2991	226	25	it	it	PRON
cana-2991	226	26	is	be	AUX
cana-2991	226	27	a	a	DET
cana-2991	226	28	more	more	ADV
cana-2991	226	29	semantically	semantically	ADV
cana-2991	226	30	oriented	orient	VERB
cana-2991	226	31	process	process	NOUN
cana-2991	226	32	compared	compare	VERB
cana-2991	226	33	to	to	ADP
cana-2991	226	34	stemming	stemming	NOUN
cana-2991	226	35	,	,	PUNCT
cana-2991	226	36	which	which	PRON
cana-2991	226	37	only	only	ADV
cana-2991	226	38	removes	remove	VERB
cana-2991	226	39	common	common	ADJ
cana-2991	226	40	parts	part	NOUN
cana-2991	226	41	of	of	ADP
cana-2991	226	42	the	the	DET
cana-2991	226	43	ending	ending	NOUN
cana-2991	226	44	of	of	ADP
cana-2991	226	45	the	the	DET
cana-2991	226	46	word	word	NOUN
cana-2991	226	47	,	,	PUNCT
cana-2991	226	48	whereas	whereas	SCONJ
cana-2991	226	49	lemmatization	lemmatization	NOUN
cana-2991	226	50	looks	look	VERB
cana-2991	226	51	at	at	ADP
cana-2991	226	52	words	word	NOUN
cana-2991	226	53	and	and	CCONJ
cana-2991	226	54	considers	consider	VERB
cana-2991	226	55	whether	whether	SCONJ
cana-2991	226	56	they	they	PRON
cana-2991	226	57	are	be	AUX
cana-2991	226	58	nouns	noun	NOUN
cana-2991	226	59	,	,	PUNCT
cana-2991	226	60	verbs	verb	NOUN
cana-2991	226	61	,	,	PUNCT
cana-2991	226	62	adjectives	adjective	NOUN
cana-2991	226	63	,	,	PUNCT
cana-2991	226	64	or	or	CCONJ
cana-2991	226	65	adverbs	adverb	NOUN
cana-2991	226	66	.	.	PUNCT
cana-2991	227	1	communications	communication	NOUN
cana-2991	227	2	on	on	ADP
cana-2991	227	3	applied	apply	VERB
cana-2991	227	4	nonlinear	nonlinear	ADJ
cana-2991	227	5	analysis	analysis	NOUN
cana-2991	227	6	issn	issn	NOUN
cana-2991	227	7	:	:	PUNCT
cana-2991	227	8	1074	1074	NUM
cana-2991	227	9	-	-	PUNCT
cana-2991	227	10	133x	133x	NUM
cana-2991	227	11	vol	vol	NOUN
cana-2991	227	12	32	32	NUM
cana-2991	227	13	no	no	NOUN
cana-2991	227	14	.	.	PUNCT
cana-2991	228	1	5s	5s	NUM
cana-2991	228	2	(	(	PUNCT
cana-2991	228	3	2025	2025	NUM
cana-2991	228	4	)	)	PUNCT
cana-2991	228	5	162	162	NUM
cana-2991	228	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	228	7	1.4	1.4	NUM
cana-2991	228	8	.	.	PUNCT
cana-2991	229	1	text	text	NOUN
cana-2991	229	2	vectorization	vectorization	NOUN
cana-2991	229	3	after	after	SCONJ
cana-2991	229	4	the	the	DET
cana-2991	229	5	text	text	NOUN
cana-2991	229	6	is	be	AUX
cana-2991	229	7	cleaned	clean	VERB
cana-2991	229	8	it	it	PRON
cana-2991	229	9	needs	need	VERB
cana-2991	229	10	to	to	PART
cana-2991	229	11	be	be	AUX
cana-2991	229	12	converted	convert	VERB
cana-2991	229	13	into	into	ADP
cana-2991	229	14	a	a	DET
cana-2991	229	15	machine	machine	NOUN
cana-2991	229	16	readable	readable	ADJ
cana-2991	229	17	numerical	numerical	ADJ
cana-2991	229	18	format	format	NOUN
cana-2991	229	19	for	for	ADP
cana-2991	229	20	the	the	DET
cana-2991	229	21	machine	machine	NOUN
cana-2991	229	22	learning	learning	NOUN
cana-2991	229	23	models	model	NOUN
cana-2991	229	24	.	.	PUNCT
cana-2991	230	1	section	section	NOUN
cana-2991	230	2	iii	iii	PROPN
cana-2991	230	3	discusses	discuss	VERB
cana-2991	230	4	several	several	ADJ
cana-2991	230	5	techniques	technique	NOUN
cana-2991	230	6	of	of	ADP
cana-2991	230	7	word	word	NOUN
cana-2991	230	8	embedding	embed	VERB
cana-2991	230	9	that	that	PRON
cana-2991	230	10	are	be	AUX
cana-2991	230	11	used	use	VERB
cana-2991	230	12	in	in	ADP
cana-2991	230	13	this	this	DET
cana-2991	230	14	study	study	NOUN
cana-2991	230	15	.	.	PUNCT
cana-2991	231	1	algorithm	algorithm	NOUN
cana-2991	231	2	1	1	NUM
cana-2991	231	3	:	:	PUNCT
cana-2991	231	4	data	datum	NOUN
cana-2991	231	5	preprocessing	preprocessing	NOUN
cana-2991	231	6	and	and	CCONJ
cana-2991	231	7	embedding	embed	VERB
cana-2991	231	8	generation	generation	NOUN
cana-2991	231	9	1	1	NUM
cana-2991	231	10	.	.	PUNCT
cana-2991	232	1	input	input	NOUN
cana-2991	232	2	:	:	PUNCT
cana-2991	232	3	raw	raw	ADJ
cana-2991	232	4	dataset	dataset	NOUN
cana-2991	232	5	𝐷	𝐷	PROPN
cana-2991	232	6	=	=	SYM
cana-2991	232	7	{	{	PUNCT
cana-2991	232	8	𝑑1	𝑑1	NOUN
cana-2991	232	9	,	,	PUNCT
cana-2991	232	10	𝑑2	𝑑2	NOUN
cana-2991	232	11	,	,	PUNCT
cana-2991	232	12	…	…	PUNCT
cana-2991	232	13	,	,	PUNCT
cana-2991	232	14	𝑑𝑛	𝑑𝑛	NOUN
cana-2991	232	15	}	}	PUNCT
cana-2991	232	16	,	,	PUNCT
cana-2991	232	17	where	where	SCONJ
cana-2991	232	18	each	each	DET
cana-2991	232	19	document	document	NOUN
cana-2991	232	20	𝑑𝑖	𝑑𝑖	VERB
cana-2991	232	21	consists	consist	VERB
cana-2991	232	22	of	of	ADP
cana-2991	232	23	a	a	DET
cana-2991	232	24	collection	collection	NOUN
cana-2991	232	25	of	of	ADP
cana-2991	232	26	words	word	NOUN
cana-2991	232	27	.	.	PUNCT
cana-2991	233	1	2	2	X
cana-2991	233	2	.	.	X
cana-2991	233	3	output	output	NOUN
cana-2991	233	4	:	:	PUNCT
cana-2991	233	5	embedded	embed	VERB
cana-2991	233	6	vectors	vector	NOUN
cana-2991	233	7	for	for	ADP
cana-2991	233	8	each	each	DET
cana-2991	233	9	document	document	NOUN
cana-2991	233	10	𝐸𝐷	𝐸𝐷	NOUN
cana-2991	233	11	=	=	SYM
cana-2991	233	12	{	{	PUNCT
cana-2991	233	13	𝑒1	𝑒1	NOUN
cana-2991	233	14	,	,	PUNCT
cana-2991	233	15	𝑒2	𝑒2	PROPN
cana-2991	233	16	,	,	PUNCT
cana-2991	233	17	…	…	PUNCT
cana-2991	233	18	,	,	PUNCT
cana-2991	233	19	𝑒𝑛	𝑒𝑛	NOUN
cana-2991	233	20	}	}	PUNCT
cana-2991	233	21	.	.	PUNCT
cana-2991	234	1	steps	step	NOUN
cana-2991	234	2	:	:	PUNCT
cana-2991	234	3	1	1	X
cana-2991	234	4	.	.	X
cana-2991	235	1	for	for	ADP
cana-2991	235	2	each	each	DET
cana-2991	235	3	document	document	NOUN
cana-2991	235	4	𝑑𝑖	𝑑𝑖	VERB
cana-2991	235	5	∈	∈	PROPN
cana-2991	235	6	𝐷	𝐷	PROPN
cana-2991	235	7	:	:	PUNCT
cana-2991	235	8	o	o	NOUN
cana-2991	235	9	tokenize	tokenize	VERB
cana-2991	235	10	document	document	NOUN
cana-2991	235	11	into	into	ADP
cana-2991	235	12	words	word	NOUN
cana-2991	235	13	𝑤	𝑤	PRON
cana-2991	235	14	=	=	PUNCT
cana-2991	235	15	{	{	PUNCT
cana-2991	235	16	𝑤1	𝑤1	NOUN
cana-2991	235	17	,	,	PUNCT
cana-2991	235	18	𝑤2	𝑤2	NOUN
cana-2991	235	19	,	,	PUNCT
cana-2991	235	20	…	…	PUNCT
cana-2991	235	21	,	,	PUNCT
cana-2991	235	22	𝑤𝑚	𝑤𝑚	NOUN
cana-2991	235	23	}	}	PUNCT
cana-2991	235	24	.	.	PUNCT
cana-2991	236	1	o	o	PROPN
cana-2991	236	2	remove	remove	VERB
cana-2991	236	3	stop	stop	NOUN
cana-2991	236	4	-	-	PUNCT
cana-2991	236	5	words	word	NOUN
cana-2991	236	6	:	:	PUNCT
cana-2991	236	7	filter	filter	VERB
cana-2991	236	8	out	out	ADP
cana-2991	236	9	common	common	ADJ
cana-2991	236	10	stop	stop	NOUN
cana-2991	236	11	-	-	PUNCT
cana-2991	236	12	words	word	NOUN
cana-2991	236	13	from	from	ADP
cana-2991	236	14	the	the	DET
cana-2991	236	15	tokenized	tokenized	ADJ
cana-2991	236	16	list	list	NOUN
cana-2991	236	17	.	.	PUNCT
cana-2991	237	1	𝑤	𝑤	X
cana-2991	237	2	′	′	NUM
cana-2991	238	1	=	=	PUNCT
cana-2991	238	2	{	{	PUNCT
cana-2991	238	3	𝑤𝑗	𝑤𝑗	PART
cana-2991	238	4	∣	∣	PROPN
cana-2991	238	5	𝑤𝑗	𝑤𝑗	PROPN
cana-2991	238	6	∉	∉	PROPN
cana-2991	238	7	𝑆𝑡𝑜𝑝𝑊𝑜𝑟𝑑𝑠	𝑆𝑡𝑜𝑝𝑊𝑜𝑟𝑑𝑠	PROPN
cana-2991	238	8	,	,	PUNCT
cana-2991	238	9	𝑤𝑗	𝑤𝑗	ADP
cana-2991	238	10	∈	∈	PROPN
cana-2991	238	11	𝑤	𝑤	ADP
cana-2991	238	12	}	}	PUNCT
cana-2991	238	13	o	o	NOUN
cana-2991	238	14	lemmatize	lemmatize	NOUN
cana-2991	238	15	/	/	SYM
cana-2991	238	16	stemming	stemming	NOUN
cana-2991	238	17	:	:	PUNCT
cana-2991	238	18	convert	convert	VERB
cana-2991	238	19	each	each	DET
cana-2991	238	20	word	word	NOUN
cana-2991	238	21	to	to	ADP
cana-2991	238	22	its	its	PRON
cana-2991	238	23	base	base	NOUN
cana-2991	238	24	form	form	NOUN
cana-2991	238	25	:	:	PUNCT
cana-2991	238	26	𝑤𝑙𝑒𝑚𝑚𝑎	𝑤𝑙𝑒𝑚𝑚𝑎	ADJ
cana-2991	238	27	=	=	SYM
cana-2991	238	28	{	{	PUNCT
cana-2991	238	29	𝑤𝑟𝑜𝑜𝑡	𝑤𝑟𝑜𝑜𝑡	PROPN
cana-2991	238	30	∣	∣	PROPN
cana-2991	238	31	𝑤𝑟𝑜𝑜𝑡	𝑤𝑟𝑜𝑜𝑡	NOUN
cana-2991	238	32	=	=	SYM
cana-2991	238	33	𝐿𝑒𝑚𝑚𝑎(𝑤𝑗	𝐿𝑒𝑚𝑚𝑎(𝑤𝑗	PROPN
cana-2991	238	34	)	)	PUNCT
cana-2991	238	35	}	}	PUNCT
cana-2991	239	1	o	o	NOUN
cana-2991	239	2	convert	convert	NOUN
cana-2991	239	3	to	to	PART
cana-2991	239	4	lowercase	lowercase	VERB
cana-2991	239	5	:	:	PUNCT
cana-2991	239	6	ensure	ensure	VERB
cana-2991	239	7	uniform	uniform	ADJ
cana-2991	239	8	casing	case	VERB
cana-2991	239	9	for	for	ADP
cana-2991	239	10	all	all	DET
cana-2991	239	11	words	word	NOUN
cana-2991	239	12	.	.	PUNCT
cana-2991	240	1	𝑤𝑙𝑜𝑤𝑒𝑟	𝑤𝑙𝑜𝑤𝑒𝑟	PROPN
cana-2991	240	2	=	=	PUNCT
cana-2991	240	3	{	{	PUNCT
cana-2991	240	4	𝑤𝑙𝑒𝑚𝑚𝑎	𝑤𝑙𝑒𝑚𝑚𝑎	ADJ
cana-2991	240	5	∣	∣	ADJ
cana-2991	240	6	𝑙𝑜𝑤𝑒𝑟(𝑤𝑙𝑒𝑚𝑚𝑎	𝑙𝑜𝑤𝑒𝑟(𝑤𝑙𝑒𝑚𝑚𝑎	PROPN
cana-2991	240	7	)	)	PUNCT
cana-2991	240	8	}	}	PUNCT
cana-2991	241	1	2	2	X
cana-2991	241	2	.	.	X
cana-2991	241	3	for	for	ADP
cana-2991	241	4	each	each	DET
cana-2991	241	5	cleaned	clean	VERB
cana-2991	241	6	document	document	NOUN
cana-2991	241	7	𝑑𝑖	𝑑𝑖	VERB
cana-2991	241	8	′	′	NUM
cana-2991	241	9	∈	∈	PROPN
cana-2991	241	10	𝐷′	𝐷′	NOUN
cana-2991	241	11	:	:	PUNCT
cana-2991	241	12	o	o	NOUN
cana-2991	241	13	select	select	ADJ
cana-2991	241	14	embedding	embed	VERB
cana-2991	241	15	model	model	NOUN
cana-2991	241	16	:	:	PUNCT
cana-2991	241	17	choose	choose	VERB
cana-2991	241	18	between	between	ADP
cana-2991	241	19	bow	bow	PROPN
cana-2991	241	20	,	,	PUNCT
cana-2991	241	21	tf	tf	PROPN
cana-2991	241	22	-	-	PUNCT
cana-2991	241	23	idf	idf	PROPN
cana-2991	241	24	,	,	PUNCT
cana-2991	241	25	word2vec	word2vec	X
cana-2991	241	26	,	,	PUNCT
cana-2991	241	27	or	or	CCONJ
cana-2991	241	28	bert	bert	NOUN
cana-2991	241	29	.	.	PUNCT
cana-2991	242	1	o	o	NOUN
cana-2991	242	2	generate	generate	VERB
cana-2991	242	3	embedding	embed	VERB
cana-2991	242	4	:	:	PUNCT
cana-2991	242	5	i.	i.	NOUN
cana-2991	242	6	if	if	SCONJ
cana-2991	242	7	bow	bow	NOUN
cana-2991	242	8	:	:	PUNCT
cana-2991	242	9	𝑣𝐵𝑜𝑊	𝑣𝐵𝑜𝑊	NOUN
cana-2991	242	10	=	=	PUNCT
cana-2991	243	1	[	[	X
cana-2991	243	2	𝑓(𝑤1	𝑓(𝑤1	NOUN
cana-2991	243	3	)	)	PUNCT
cana-2991	243	4	,	,	PUNCT
cana-2991	243	5	𝑓(𝑤2	𝑓(𝑤2	NOUN
cana-2991	243	6	)	)	PUNCT
cana-2991	243	7	,	,	PUNCT
cana-2991	243	8	…	…	PUNCT
cana-2991	243	9	,	,	PUNCT
cana-2991	243	10	𝑓(𝑤𝑛	𝑓(𝑤𝑛	PROPN
cana-2991	243	11	)	)	PUNCT
cana-2991	243	12	]	]	X
cana-2991	243	13	ii	ii	X
cana-2991	243	14	.	.	PUNCT
cana-2991	244	1	if	if	SCONJ
cana-2991	244	2	tf	tf	PROPN
cana-2991	244	3	-	-	PUNCT
cana-2991	244	4	idf	idf	PROPN
cana-2991	244	5	:	:	PUNCT
cana-2991	244	6	𝑣𝑇𝐹−𝐼𝐷𝐹	𝑣𝑇𝐹−𝐼𝐷𝐹	PROPN
cana-2991	244	7	=	=	SYM
cana-2991	244	8	𝑇𝐹(𝑤𝑗	𝑇𝐹(𝑤𝑗	PROPN
cana-2991	244	9	,	,	PUNCT
cana-2991	244	10	𝑑𝑖	𝑑𝑖	PROPN
cana-2991	244	11	′	′	NUM
cana-2991	244	12	)	)	PUNCT
cana-2991	244	13	×	×	NOUN
cana-2991	244	14	𝑙𝑜𝑔	𝑙𝑜𝑔	NOUN
cana-2991	244	15	𝑁	𝑁	PROPN
cana-2991	244	16	𝐷𝐹(𝑤𝑗	𝐷𝐹(𝑤𝑗	NOUN
cana-2991	244	17	)	)	PUNCT
cana-2991	244	18	iii	iii	NOUN
cana-2991	244	19	.	.	PUNCT
cana-2991	245	1	if	if	SCONJ
cana-2991	245	2	word2vec	word2vec	X
cana-2991	245	3	(	(	PUNCT
cana-2991	245	4	cbow	cbow	VERB
cana-2991	245	5	/	/	SYM
cana-2991	245	6	skip	skip	NOUN
cana-2991	245	7	-	-	PUNCT
cana-2991	245	8	gram	gram	NOUN
cana-2991	245	9	):	):	PUNCT
cana-2991	245	10	𝑃(𝑤𝑗	𝑃(𝑤𝑗	NOUN
cana-2991	245	11	∣	∣	ADJ
cana-2991	245	12	𝑐𝑜𝑛𝑡𝑒𝑥𝑡	𝑐𝑜𝑛𝑡𝑒𝑥𝑡	NOUN
cana-2991	245	13	)	)	PUNCT
cana-2991	246	1	=	=	PRON
cana-2991	246	2	𝑒𝑥𝑝	𝑒𝑥𝑝	INTJ
cana-2991	246	3	(	(	PUNCT
cana-2991	246	4	𝑣𝑤𝑗	𝑣𝑤𝑗	PROPN
cana-2991	246	5	⊤	⊤	PROPN
cana-2991	246	6	ℎ	ℎ	PROPN
cana-2991	246	7	)	)	PUNCT
cana-2991	246	8	∑	∑	PUNCT
cana-2991	246	9	𝑤𝑘∈𝑉	𝑤𝑘∈𝑉	PROPN
cana-2991	246	10	𝑒𝑥𝑝(𝑣𝑤𝑘	𝑒𝑥𝑝(𝑣𝑤𝑘	PROPN
cana-2991	246	11	⊤	⊤	PROPN
cana-2991	246	12	ℎ	ℎ	PROPN
cana-2991	246	13	)	)	PUNCT
cana-2991	246	14	iv	iv	NUM
cana-2991	246	15	.	.	PUNCT
cana-2991	247	1	if	if	SCONJ
cana-2991	247	2	bert	bert	PROPN
cana-2991	247	3	:	:	PUNCT
cana-2991	247	4	𝐿𝐵𝐸𝑅𝑇	𝐿𝐵𝐸𝑅𝑇	PROPN
cana-2991	247	5	=	=	PUNCT
cana-2991	248	1	−	−	PROPN
cana-2991	248	2	∑	∑	PUNCT
cana-2991	248	3	𝑛	𝑛	DET
cana-2991	248	4	𝑖=1	𝑖=1	PROPN
cana-2991	248	5	𝑙𝑜𝑔𝑃(𝑤𝑖	𝑙𝑜𝑔𝑃(𝑤𝑖	PROPN
cana-2991	248	6	∣	∣	PROPN
cana-2991	248	7	𝑤1	𝑤1	PROPN
cana-2991	248	8	,	,	PUNCT
cana-2991	248	9	…	…	PUNCT
cana-2991	248	10	,	,	PUNCT
cana-2991	248	11	𝑤𝑖−1	𝑤𝑖−1	PROPN
cana-2991	248	12	,	,	PUNCT
cana-2991	248	13	𝑤𝑖+1	𝑤𝑖+1	NUM
cana-2991	248	14	,	,	PUNCT
cana-2991	248	15	…	…	PUNCT
cana-2991	248	16	,	,	PUNCT
cana-2991	248	17	𝑤𝑛	𝑤𝑛	NOUN
cana-2991	248	18	)	)	PUNCT
cana-2991	248	19	communications	communication	NOUN
cana-2991	248	20	on	on	ADP
cana-2991	248	21	applied	apply	VERB
cana-2991	248	22	nonlinear	nonlinear	ADJ
cana-2991	248	23	analysis	analysis	NOUN
cana-2991	248	24	issn	issn	NOUN
cana-2991	248	25	:	:	PUNCT
cana-2991	248	26	1074	1074	NUM
cana-2991	248	27	-	-	PUNCT
cana-2991	248	28	133x	133x	NUM
cana-2991	248	29	vol	vol	NOUN
cana-2991	248	30	32	32	NUM
cana-2991	248	31	no	no	NOUN
cana-2991	248	32	.	.	PUNCT
cana-2991	249	1	5s	5s	NUM
cana-2991	249	2	(	(	PUNCT
cana-2991	249	3	2025	2025	NUM
cana-2991	249	4	)	)	PUNCT
cana-2991	249	5	163	163	NUM
cana-2991	249	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	249	7	3	3	X
cana-2991	249	8	.	.	X
cana-2991	249	9	store	store	NOUN
cana-2991	249	10	embedding	embed	VERB
cana-2991	249	11	:	:	PUNCT
cana-2991	249	12	o	o	NOUN
cana-2991	249	13	collect	collect	VERB
cana-2991	249	14	the	the	DET
cana-2991	249	15	generated	generate	VERB
cana-2991	249	16	embeddings	embedding	NOUN
cana-2991	249	17	for	for	ADP
cana-2991	249	18	all	all	DET
cana-2991	249	19	documents	document	NOUN
cana-2991	249	20	in	in	ADP
cana-2991	249	21	𝐸𝐷	𝐸𝐷	PROPN
cana-2991	249	22	=	=	SYM
cana-2991	249	23	{	{	PUNCT
cana-2991	249	24	𝑣1	𝑣1	PROPN
cana-2991	249	25	,	,	PUNCT
cana-2991	249	26	𝑣2	𝑣2	PROPN
cana-2991	249	27	,	,	PUNCT
cana-2991	249	28	…	…	PUNCT
cana-2991	249	29	,	,	PUNCT
cana-2991	249	30	𝑣𝑛	𝑣𝑛	NOUN
cana-2991	249	31	}	}	PUNCT
cana-2991	249	32	.	.	PUNCT
cana-2991	250	1	4	4	X
cana-2991	250	2	.	.	X
cana-2991	250	3	return	return	NOUN
cana-2991	250	4	:	:	PUNCT
cana-2991	250	5	embedded	embed	VERB
cana-2991	250	6	document	document	NOUN
cana-2991	250	7	vectors	vector	NOUN
cana-2991	250	8	𝐸𝐷	𝐸𝐷	PROPN
cana-2991	250	9	.	.	PUNCT
cana-2991	251	1	in	in	ADP
cana-2991	251	2	algorithm	algorithm	NOUN
cana-2991	251	3	1	1	NUM
cana-2991	251	4	,	,	PUNCT
cana-2991	251	5	the	the	DET
cana-2991	251	6	preprocessing	preprocessing	NOUN
cana-2991	251	7	of	of	ADP
cana-2991	251	8	raw	raw	ADJ
cana-2991	251	9	text	text	NOUN
cana-2991	251	10	data	datum	NOUN
cana-2991	251	11	and	and	CCONJ
cana-2991	251	12	word	word	NOUN
cana-2991	251	13	embedding	embed	VERB
cana-2991	251	14	using	use	VERB
cana-2991	251	15	the	the	DET
cana-2991	251	16	principal	principal	ADJ
cana-2991	251	17	models	model	NOUN
cana-2991	251	18	,	,	PUNCT
cana-2991	251	19	bow	bow	NOUN
cana-2991	251	20	,	,	PUNCT
cana-2991	251	21	tf	tf	PROPN
cana-2991	251	22	-	-	PUNCT
cana-2991	251	23	idf	idf	PROPN
cana-2991	251	24	,	,	PUNCT
cana-2991	251	25	word2vec	word2vec	X
cana-2991	251	26	,	,	PUNCT
cana-2991	251	27	and	and	CCONJ
cana-2991	251	28	bert	bert	PROPN
cana-2991	251	29	need	need	VERB
cana-2991	251	30	to	to	PART
cana-2991	251	31	be	be	AUX
cana-2991	251	32	prepared	prepare	VERB
cana-2991	251	33	.	.	PUNCT
cana-2991	252	1	this	this	PRON
cana-2991	252	2	covers	cover	VERB
cana-2991	252	3	term	term	NOUN
cana-2991	252	4	frequency	frequency	NOUN
cana-2991	252	5	and	and	CCONJ
cana-2991	252	6	inverse	inverse	NOUN
cana-2991	252	7	document	document	NOUN
cana-2991	252	8	frequency	frequency	NOUN
cana-2991	252	9	,	,	PUNCT
cana-2991	252	10	plus	plus	CCONJ
cana-2991	252	11	the	the	DET
cana-2991	252	12	loss	loss	NOUN
cana-2991	252	13	functions	function	NOUN
cana-2991	252	14	for	for	ADP
cana-2991	252	15	word2vec	word2vec	X
cana-2991	252	16	and	and	CCONJ
cana-2991	252	17	bert	bert	PROPN
cana-2991	252	18	embeddings	embedding	NOUN
cana-2991	252	19	.	.	PUNCT
cana-2991	253	1	2	2	X
cana-2991	253	2	.	.	X
cana-2991	253	3	word	word	NOUN
cana-2991	253	4	embedding	embed	VERB
cana-2991	253	5	models	model	NOUN
cana-2991	253	6	at	at	ADP
cana-2991	253	7	the	the	DET
cana-2991	253	8	heart	heart	NOUN
cana-2991	253	9	of	of	ADP
cana-2991	253	10	the	the	DET
cana-2991	253	11	recommended	recommend	VERB
cana-2991	253	12	approach	approach	NOUN
cana-2991	253	13	is	be	AUX
cana-2991	253	14	converting	convert	VERB
cana-2991	253	15	text	text	NOUN
cana-2991	253	16	data	datum	NOUN
cana-2991	253	17	into	into	ADP
cana-2991	253	18	interpretable	interpretable	ADJ
cana-2991	253	19	numerical	numerical	ADJ
cana-2991	253	20	features	feature	NOUN
cana-2991	253	21	.	.	PUNCT
cana-2991	254	1	word	word	NOUN
cana-2991	254	2	embedding	embed	VERB
cana-2991	254	3	techniques	technique	NOUN
cana-2991	254	4	convert	convert	NOUN
cana-2991	254	5	words	word	NOUN
cana-2991	254	6	or	or	CCONJ
cana-2991	254	7	text	text	NOUN
cana-2991	254	8	in	in	ADP
cana-2991	254	9	a	a	DET
cana-2991	254	10	corpus	corpus	NOUN
cana-2991	254	11	to	to	ADP
cana-2991	254	12	a	a	DET
cana-2991	254	13	vector	vector	NOUN
cana-2991	254	14	of	of	ADP
cana-2991	254	15	real	real	ADJ
cana-2991	254	16	numbers	number	NOUN
cana-2991	254	17	based	base	VERB
cana-2991	254	18	on	on	ADP
cana-2991	254	19	semantic	semantic	ADJ
cana-2991	254	20	meaning	meaning	NOUN
cana-2991	254	21	of	of	ADP
cana-2991	254	22	the	the	DET
cana-2991	254	23	text	text	NOUN
cana-2991	254	24	.	.	PUNCT
cana-2991	255	1	we	we	PRON
cana-2991	255	2	use	use	VERB
cana-2991	255	3	the	the	DET
cana-2991	255	4	following	follow	VERB
cana-2991	255	5	embedding	embed	VERB
cana-2991	255	6	methodology	methodology	NOUN
cana-2991	255	7	:	:	PUNCT
cana-2991	255	8	2.1	2.1	NUM
cana-2991	255	9	.	.	PUNCT
cana-2991	256	1	bag	bag	NOUN
cana-2991	256	2	of	of	ADP
cana-2991	256	3	words	word	NOUN
cana-2991	256	4	(	(	PUNCT
cana-2991	256	5	bow	bow	NOUN
cana-2991	256	6	)	)	PUNCT
cana-2991	256	7	a	a	DET
cana-2991	256	8	bag	bag	NOUN
cana-2991	256	9	of	of	ADP
cana-2991	256	10	words	word	NOUN
cana-2991	256	11	model	model	VERB
cana-2991	256	12	one	one	NUM
cana-2991	256	13	of	of	ADP
cana-2991	256	14	the	the	DET
cana-2991	256	15	simplest	simple	ADJ
cana-2991	256	16	ways	way	NOUN
cana-2991	256	17	to	to	PART
cana-2991	256	18	turn	turn	VERB
cana-2991	256	19	text	text	NOUN
cana-2991	256	20	into	into	ADP
cana-2991	256	21	vectors	vector	NOUN
cana-2991	256	22	in	in	ADP
cana-2991	256	23	bow	bow	NOUN
cana-2991	256	24	,	,	PUNCT
cana-2991	256	25	every	every	DET
cana-2991	256	26	document	document	NOUN
cana-2991	256	27	is	be	AUX
cana-2991	256	28	represented	represent	VERB
cana-2991	256	29	as	as	ADP
cana-2991	256	30	a	a	DET
cana-2991	256	31	vector	vector	NOUN
cana-2991	256	32	where	where	SCONJ
cana-2991	256	33	each	each	PRON
cana-2991	256	34	of	of	ADP
cana-2991	256	35	the	the	DET
cana-2991	256	36	dimensions	dimension	NOUN
cana-2991	256	37	represents	represent	VERB
cana-2991	256	38	a	a	DET
cana-2991	256	39	particular	particular	ADJ
cana-2991	256	40	word	word	NOUN
cana-2991	256	41	in	in	ADP
cana-2991	256	42	the	the	DET
cana-2991	256	43	vocabulary	vocabulary	NOUN
cana-2991	256	44	of	of	ADP
cana-2991	256	45	the	the	DET
cana-2991	256	46	corpus	corpus	NOUN
cana-2991	256	47	.	.	PUNCT
cana-2991	257	1	the	the	DET
cana-2991	257	2	dimensions	dimension	NOUN
cana-2991	257	3	will	will	AUX
cana-2991	257	4	be	be	AUX
cana-2991	257	5	counted	count	VERB
cana-2991	257	6	n	n	PRON
cana-2991	257	7	times	time	NOUN
cana-2991	257	8	of	of	ADP
cana-2991	257	9	the	the	DET
cana-2991	257	10	word	word	NOUN
cana-2991	257	11	present	present	ADJ
cana-2991	257	12	in	in	ADP
cana-2991	257	13	the	the	DET
cana-2991	257	14	document	document	NOUN
cana-2991	257	15	.	.	PUNCT
cana-2991	258	1	𝑣𝐵𝑜𝑊	𝑣𝐵𝑜𝑊	NOUN
cana-2991	258	2	=	=	PUNCT
cana-2991	259	1	[	[	X
cana-2991	259	2	𝑓(𝑤1	𝑓(𝑤1	NOUN
cana-2991	259	3	)	)	PUNCT
cana-2991	259	4	,	,	PUNCT
cana-2991	259	5	𝑓(𝑤2	𝑓(𝑤2	NOUN
cana-2991	259	6	)	)	PUNCT
cana-2991	259	7	,	,	PUNCT
cana-2991	259	8	…	…	PUNCT
cana-2991	259	9	,	,	PUNCT
cana-2991	259	10	𝑓(𝑤𝑁	𝑓(𝑤𝑁	PROPN
cana-2991	259	11	)	)	PUNCT
cana-2991	259	12	]	]	PUNCT
cana-2991	259	13	where	where	SCONJ
cana-2991	259	14	f(w_i	f(w_i	PROPN
cana-2991	259	15	)	)	PUNCT
cana-2991	259	16	is	be	AUX
cana-2991	259	17	the	the	DET
cana-2991	259	18	frequency	frequency	NOUN
cana-2991	259	19	of	of	ADP
cana-2991	259	20	word	word	NOUN
cana-2991	259	21	w_i	w_i	NUM
cana-2991	259	22	in	in	ADP
cana-2991	259	23	the	the	DET
cana-2991	259	24	document	document	NOUN
cana-2991	259	25	,	,	PUNCT
cana-2991	259	26	and	and	CCONJ
cana-2991	259	27	n	n	PRON
cana-2991	259	28	is	be	AUX
cana-2991	259	29	size	size	NOUN
cana-2991	259	30	of	of	ADP
cana-2991	259	31	vocabulary	vocabulary	NOUN
cana-2991	259	32	.	.	PUNCT
cana-2991	260	1	still	still	ADV
cana-2991	260	2	,	,	PUNCT
cana-2991	260	3	bow	bow	VERB
cana-2991	260	4	is	be	AUX
cana-2991	260	5	primitive	primitive	ADJ
cana-2991	260	6	:	:	PUNCT
cana-2991	260	7	it	it	PRON
cana-2991	260	8	does	do	AUX
cana-2991	260	9	not	not	PART
cana-2991	260	10	encode	encode	VERB
cana-2991	260	11	the	the	DET
cana-2991	260	12	contextual	contextual	ADJ
cana-2991	260	13	meaning	meaning	NOUN
cana-2991	260	14	of	of	ADP
cana-2991	260	15	words	word	NOUN
cana-2991	260	16	and	and	CCONJ
cana-2991	260	17	operates	operate	VERB
cana-2991	260	18	under	under	ADP
cana-2991	260	19	a	a	DET
cana-2991	260	20	lax	lax	ADJ
cana-2991	260	21	assumption	assumption	NOUN
cana-2991	260	22	of	of	ADP
cana-2991	260	23	word	word	NOUN
cana-2991	260	24	independence	independence	NOUN
cana-2991	260	25	.	.	PUNCT
cana-2991	261	1	2.2	2.2	NUM
cana-2991	261	2	.	.	PUNCT
cana-2991	262	1	tf	tf	PROPN
cana-2991	262	2	-	-	PUNCT
cana-2991	262	3	idf	idf	ADJ
cana-2991	262	4	(	(	PUNCT
cana-2991	262	5	term	term	NOUN
cana-2991	262	6	frequency	frequency	NOUN
cana-2991	262	7	-	-	PUNCT
cana-2991	262	8	inverse	inverse	NOUN
cana-2991	262	9	document	document	NOUN
cana-2991	262	10	frequency	frequency	NOUN
cana-2991	262	11	)	)	PUNCT
cana-2991	262	12	this	this	PRON
cana-2991	262	13	is	be	AUX
cana-2991	262	14	an	an	DET
cana-2991	262	15	improvement	improvement	NOUN
cana-2991	262	16	over	over	ADP
cana-2991	262	17	bow	bow	PROPN
cana-2991	262	18	,	,	PUNCT
cana-2991	262	19	where	where	SCONJ
cana-2991	262	20	it	it	PRON
cana-2991	262	21	modifies	modify	VERB
cana-2991	262	22	word	word	NOUN
cana-2991	262	23	frequencies	frequency	NOUN
cana-2991	262	24	with	with	ADP
cana-2991	262	25	respect	respect	NOUN
cana-2991	262	26	to	to	ADP
cana-2991	262	27	the	the	DET
cana-2991	262	28	words	word	NOUN
cana-2991	262	29	in	in	ADP
cana-2991	262	30	a	a	DET
cana-2991	262	31	corpus	corpus	NOUN
cana-2991	262	32	.	.	PUNCT
cana-2991	263	1	so	so	ADV
cana-2991	263	2	,	,	PUNCT
cana-2991	263	3	they	they	PRON
cana-2991	263	4	are	be	AUX
cana-2991	263	5	extracted	extract	VERB
cana-2991	263	6	from	from	ADP
cana-2991	263	7	the	the	DET
cana-2991	263	8	text	text	NOUN
cana-2991	263	9	file1	file1	PROPN
cana-2991	263	10	as	as	SCONJ
cana-2991	263	11	follows	follow	VERB
cana-2991	263	12	:	:	PUNCT
cana-2991	263	13	term	term	NOUN
cana-2991	263	14	frequency	frequency	NOUN
cana-2991	263	15	(	(	PUNCT
cana-2991	263	16	tf	tf	X
cana-2991	263	17	):	):	PUNCT
cana-2991	263	18	𝑇𝐹(𝑤𝑖	𝑇𝐹(𝑤𝑖	PROPN
cana-2991	263	19	,	,	PUNCT
cana-2991	263	20	𝐷	𝐷	PROPN
cana-2991	263	21	)	)	PUNCT
cana-2991	263	22	=	=	PUNCT
cana-2991	264	1	𝐹𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦	𝐹𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦	PROPN
cana-2991	264	2	𝑜𝑓	𝑜𝑓	ADP
cana-2991	264	3	𝑤𝑖	𝑤𝑖	ADV
cana-2991	264	4	𝑖𝑛	𝑖𝑛	NOUN
cana-2991	264	5	𝐷	𝐷	PROPN
cana-2991	264	6	𝑇𝑜𝑡𝑎𝑙	𝑇𝑜𝑡𝑎𝑙	PROPN
cana-2991	264	7	𝑛𝑢𝑚𝑏𝑒𝑟	𝑛𝑢𝑚𝑏𝑒𝑟	NOUN
cana-2991	264	8	𝑜𝑓	𝑜𝑓	ADP
cana-2991	264	9	𝑤𝑜𝑟𝑑𝑠	𝑤𝑜𝑟𝑑𝑠	PROPN
cana-2991	264	10	𝑖𝑛	𝑖𝑛	PROPN
cana-2991	264	11	𝐷	𝐷	PROPN
cana-2991	264	12	inverse	inverse	NOUN
cana-2991	264	13	document	document	NOUN
cana-2991	264	14	frequency	frequency	NOUN
cana-2991	264	15	as	as	ADP
cana-2991	264	16	:	:	PUNCT
cana-2991	264	17	𝐼𝐷𝐹(𝑤𝑖	𝐼𝐷𝐹(𝑤𝑖	PROPN
cana-2991	264	18	,	,	PUNCT
cana-2991	264	19	𝐷	𝐷	NOUN
cana-2991	264	20	)	)	PUNCT
cana-2991	264	21	=	=	PUNCT
cana-2991	265	1	𝑙𝑜𝑔	𝑙𝑜𝑔	NOUN
cana-2991	266	1	𝑇𝑜𝑡𝑎𝑙	𝑇𝑜𝑡𝑎𝑙	PRON
cana-2991	266	2	𝑛𝑢𝑚𝑏𝑒𝑟	𝑛𝑢𝑚𝑏𝑒𝑟	NOUN
cana-2991	266	3	𝑜𝑓	𝑜𝑓	ADP
cana-2991	266	4	𝑑𝑜𝑐𝑢𝑚𝑒𝑛𝑡𝑠	𝑑𝑜𝑐𝑢𝑚𝑒𝑛𝑡𝑠	NOUN
cana-2991	266	5	𝑁𝑢𝑚𝑏𝑒𝑟	𝑁𝑢𝑚𝑏𝑒𝑟	PROPN
cana-2991	266	6	𝑜𝑓	𝑜𝑓	ADP
cana-2991	266	7	𝑑𝑜𝑐𝑢𝑚𝑒𝑛𝑡𝑠	𝑑𝑜𝑐𝑢𝑚𝑒𝑛𝑡𝑠	NOUN
cana-2991	266	8	𝑐𝑜𝑛𝑡𝑎𝑖𝑛𝑖𝑛𝑔	𝑐𝑜𝑛𝑡𝑎𝑖𝑛𝑖𝑛𝑔	NOUN
cana-2991	266	9	𝑤𝑖	𝑤𝑖	ADP
cana-2991	266	10	ti	ti	PROPN
cana-2991	266	11	-	-	ADJ
cana-2991	266	12	idf	idf	ADJ
cana-2991	266	13	score	score	NOUN
cana-2991	266	14	calculated	calculate	VERB
cana-2991	266	15	as	as	ADP
cana-2991	266	16	:	:	PUNCT
cana-2991	266	17	𝑇𝐹	𝑇𝐹	PROPN
cana-2991	266	18	−	−	PROPN
cana-2991	266	19	𝐼𝐷𝐹(𝑤𝑖	𝐼𝐷𝐹(𝑤𝑖	PROPN
cana-2991	266	20	,	,	PUNCT
cana-2991	266	21	𝐷	𝐷	PROPN
cana-2991	266	22	)	)	PUNCT
cana-2991	266	23	=	=	SYM
cana-2991	266	24	𝑇𝐹(𝑤𝑖	𝑇𝐹(𝑤𝑖	PROPN
cana-2991	266	25	,	,	PUNCT
cana-2991	266	26	𝐷	𝐷	PROPN
cana-2991	266	27	)	)	PUNCT
cana-2991	266	28	×	×	NOUN
cana-2991	266	29	𝐼𝐷𝐹(𝑤𝑖	𝐼𝐷𝐹(𝑤𝑖	PROPN
cana-2991	266	30	,	,	PUNCT
cana-2991	266	31	𝐷	𝐷	PROPN
cana-2991	266	32	)	)	PUNCT
cana-2991	266	33	this	this	DET
cana-2991	266	34	method	method	NOUN
cana-2991	266	35	assigns	assign	VERB
cana-2991	266	36	words	word	NOUN
cana-2991	266	37	by	by	ADP
cana-2991	266	38	their	their	PRON
cana-2991	266	39	informative	informative	ADJ
cana-2991	266	40	value	value	NOUN
cana-2991	266	41	when	when	SCONJ
cana-2991	266	42	it	it	PRON
cana-2991	266	43	comes	come	VERB
cana-2991	266	44	to	to	ADP
cana-2991	266	45	the	the	DET
cana-2991	266	46	document	document	NOUN
cana-2991	266	47	,	,	PUNCT
cana-2991	266	48	thus	thus	ADV
cana-2991	266	49	minimizing	minimize	VERB
cana-2991	266	50	the	the	DET
cana-2991	266	51	effects	effect	NOUN
cana-2991	266	52	of	of	ADP
cana-2991	266	53	frequent	frequent	ADJ
cana-2991	266	54	but	but	CCONJ
cana-2991	266	55	uninformative	uninformative	ADJ
cana-2991	266	56	terms	term	NOUN
cana-2991	266	57	.	.	PUNCT
cana-2991	267	1	2.3	2.3	NUM
cana-2991	267	2	.	.	PUNCT
cana-2991	268	1	word2vec	word2vec	AUX
cana-2991	268	2	this	this	PRON
cana-2991	268	3	is	be	AUX
cana-2991	268	4	exactly	exactly	ADV
cana-2991	268	5	what	what	PRON
cana-2991	268	6	word2vec	word2vec	X
cana-2991	268	7	,	,	PUNCT
cana-2991	268	8	a	a	DET
cana-2991	268	9	neural	neural	ADJ
cana-2991	268	10	network	network	NOUN
cana-2991	268	11	-	-	PUNCT
cana-2991	268	12	based	base	VERB
cana-2991	268	13	model	model	NOUN
cana-2991	268	14	does	do	AUX
cana-2991	268	15	in	in	ADP
cana-2991	268	16	that	that	SCONJ
cana-2991	268	17	it	it	PRON
cana-2991	268	18	gets	get	VERB
cana-2991	268	19	to	to	PART
cana-2991	268	20	know	know	VERB
cana-2991	268	21	the	the	DET
cana-2991	268	22	semantic	semantic	ADJ
cana-2991	268	23	relationships	relationship	NOUN
cana-2991	268	24	between	between	ADP
cana-2991	268	25	words	word	NOUN
cana-2991	268	26	by	by	ADP
cana-2991	268	27	trying	try	VERB
cana-2991	268	28	to	to	PART
cana-2991	268	29	predict	predict	VERB
cana-2991	268	30	the	the	DET
cana-2991	268	31	context	context	NOUN
cana-2991	268	32	of	of	ADP
cana-2991	268	33	a	a	DET
cana-2991	268	34	word	word	NOUN
cana-2991	268	35	given	give	VERB
cana-2991	268	36	its	its	PRON
cana-2991	268	37	surrounding	surround	VERB
cana-2991	268	38	neighbors	neighbor	NOUN
cana-2991	268	39	.	.	PUNCT
cana-2991	269	1	there	there	PRON
cana-2991	269	2	are	be	VERB
cana-2991	269	3	two	two	NUM
cana-2991	269	4	modes	mode	NOUN
cana-2991	269	5	of	of	ADP
cana-2991	269	6	operation	operation	NOUN
cana-2991	269	7	employed	employ	VERB
cana-2991	269	8	by	by	ADP
cana-2991	269	9	word2vec	word2vec	NOUN
cana-2991	269	10	:	:	PUNCT
cana-2991	269	11	continuous	continuous	ADJ
cana-2991	269	12	bag	bag	NOUN
cana-2991	269	13	of	of	ADP
cana-2991	269	14	words	word	NOUN
cana-2991	269	15	(	(	PUNCT
cana-2991	269	16	cbow	cbow	PROPN
cana-2991	269	17	)	)	PUNCT
cana-2991	269	18	,	,	PUNCT
cana-2991	269	19	and	and	CCONJ
cana-2991	269	20	skip	skip	NOUN
cana-2991	269	21	-	-	PUNCT
cana-2991	269	22	gram	gram	NOUN
cana-2991	269	23	.	.	PUNCT
cana-2991	270	1	in	in	ADP
cana-2991	270	2	cbow	cbow	PROPN
cana-2991	270	3	model	model	NOUN
cana-2991	270	4	,	,	PUNCT
cana-2991	270	5	we	we	PRON
cana-2991	270	6	predict	predict	VERB
cana-2991	270	7	word	word	NOUN
cana-2991	270	8	given	give	VERB
cana-2991	270	9	its	its	PRON
cana-2991	270	10	context	context	NOUN
cana-2991	270	11	,	,	PUNCT
cana-2991	270	12	which	which	PRON
cana-2991	270	13	are	be	AUX
cana-2991	270	14	the	the	DET
cana-2991	270	15	surrounding	surround	VERB
cana-2991	270	16	words	word	NOUN
cana-2991	270	17	:	:	PUNCT
cana-2991	270	18	communications	communication	NOUN
cana-2991	270	19	on	on	ADP
cana-2991	270	20	applied	apply	VERB
cana-2991	270	21	nonlinear	nonlinear	ADJ
cana-2991	270	22	analysis	analysis	NOUN
cana-2991	270	23	issn	issn	NOUN
cana-2991	270	24	:	:	PUNCT
cana-2991	270	25	1074	1074	NUM
cana-2991	270	26	-	-	PUNCT
cana-2991	270	27	133x	133x	NUM
cana-2991	270	28	vol	vol	NOUN
cana-2991	270	29	32	32	NUM
cana-2991	270	30	no	no	NOUN
cana-2991	270	31	.	.	PUNCT
cana-2991	271	1	5s	5s	NUM
cana-2991	271	2	(	(	PUNCT
cana-2991	271	3	2025	2025	NUM
cana-2991	271	4	)	)	PUNCT
cana-2991	271	5	164	164	NUM
cana-2991	271	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	271	7	𝑃(𝑤𝑖	𝑃(𝑤𝑖	PROPN
cana-2991	271	8	∣	∣	PROPN
cana-2991	271	9	𝑤𝑖−1	𝑤𝑖−1	NOUN
cana-2991	271	10	,	,	PUNCT
cana-2991	271	11	𝑤𝑖+1	𝑤𝑖+1	NUM
cana-2991	271	12	)	)	PUNCT
cana-2991	271	13	=	=	SYM
cana-2991	271	14	𝑒𝑥𝑝(𝑣𝑤𝑖	𝑒𝑥𝑝(𝑣𝑤𝑖	NOUN
cana-2991	271	15	⊤	⊤	PROPN
cana-2991	271	16	ℎ	ℎ	PROPN
cana-2991	271	17	)	)	PUNCT
cana-2991	271	18	∑	∑	ADP
cana-2991	271	19	𝑤𝑗∈𝑉	𝑤𝑗∈𝑉	PRON
cana-2991	271	20	𝑒𝑥𝑝	𝑒𝑥𝑝	INTJ
cana-2991	271	21	(	(	PUNCT
cana-2991	271	22	𝑣𝑤𝑗	𝑣𝑤𝑗	PROPN
cana-2991	271	23	⊤	⊤	NOUN
cana-2991	271	24	ℎ	ℎ	PROPN
cana-2991	271	25	)	)	PUNCT
cana-2991	271	26	v_{w_i	v_{w_i	NOUN
cana-2991	271	27	}	}	PUNCT
cana-2991	271	28	:	:	PUNCT
cana-2991	271	29	the	the	DET
cana-2991	271	30	vector	vector	NOUN
cana-2991	271	31	representation	representation	NOUN
cana-2991	271	32	of	of	ADP
cana-2991	271	33	word	word	NOUN
cana-2991	271	34	w_ih	w_ih	PROPN
cana-2991	271	35	:	:	PUNCT
cana-2991	271	36	the	the	DET
cana-2991	271	37	hidden	hide	VERB
cana-2991	271	38	layer	layer	NOUN
cana-2991	271	39	vector	vector	NOUN
cana-2991	271	40	skip	skip	NOUN
cana-2991	271	41	-	-	PUNCT
cana-2991	271	42	gram	gram	NOUN
cana-2991	271	43	:	:	PUNCT
cana-2991	271	44	given	give	VERB
cana-2991	271	45	a	a	DET
cana-2991	271	46	word	word	NOUN
cana-2991	271	47	we	we	PRON
cana-2991	271	48	will	will	AUX
cana-2991	271	49	predict	predict	VERB
cana-2991	271	50	the	the	DET
cana-2991	271	51	surrounding	surround	VERB
cana-2991	271	52	words	word	NOUN
cana-2991	271	53	eg	eg	ADP
cana-2991	271	54	𝑃(𝑤𝑖−1	𝑃(𝑤𝑖−1	PROPN
cana-2991	271	55	,	,	PUNCT
cana-2991	271	56	𝑤𝑖+1	𝑤𝑖+1	NUM
cana-2991	271	57	∣	∣	VERB
cana-2991	271	58	𝑤𝑖	𝑤𝑖	NOUN
cana-2991	271	59	)	)	PUNCT
cana-2991	271	60	=	=	SYM
cana-2991	271	61	∏	∏	X
cana-2991	271	62	𝑗=𝑖−1,𝑖+1	𝑗=𝑖−1,𝑖+1	X
cana-2991	272	1	𝑒𝑥𝑝	𝑒𝑥𝑝	INTJ
cana-2991	272	2	(	(	PUNCT
cana-2991	272	3	𝑣𝑤𝑗	𝑣𝑤𝑗	PROPN
cana-2991	272	4	⊤	⊤	PROPN
cana-2991	272	5	𝑣𝑤𝑖	𝑣𝑤𝑖	PROPN
cana-2991	272	6	)	)	PUNCT
cana-2991	272	7	∑	∑	PUNCT
cana-2991	272	8	𝑤𝑘∈𝑉	𝑤𝑘∈𝑉	PROPN
cana-2991	272	9	𝑒𝑥𝑝(𝑣𝑤𝑘	𝑒𝑥𝑝(𝑣𝑤𝑘	PROPN
cana-2991	272	10	⊤	⊤	PROPN
cana-2991	272	11	𝑣𝑤𝑖	𝑣𝑤𝑖	PROPN
cana-2991	272	12	)	)	PUNCT
cana-2991	273	1	this	this	DET
cana-2991	273	2	feature	feature	NOUN
cana-2991	273	3	of	of	ADP
cana-2991	273	4	word2vec	word2vec	PRON
cana-2991	273	5	gives	give	VERB
cana-2991	273	6	it	it	PRON
cana-2991	273	7	the	the	DET
cana-2991	273	8	ability	ability	NOUN
cana-2991	273	9	to	to	PART
cana-2991	273	10	learn	learn	VERB
cana-2991	273	11	context	context	NOUN
cana-2991	273	12	-	-	PUNCT
cana-2991	273	13	sensitive	sensitive	ADJ
cana-2991	273	14	embeddings	embedding	NOUN
cana-2991	273	15	and	and	CCONJ
cana-2991	273	16	to	to	ADP
cana-2991	273	17	some	some	DET
cana-2991	273	18	extent	extent	NOUN
cana-2991	273	19	semantic	semantic	ADJ
cana-2991	273	20	as	as	ADV
cana-2991	273	21	well	well	ADV
cana-2991	273	22	as	as	ADP
cana-2991	273	23	syntactic	syntactic	ADJ
cana-2991	273	24	but	but	CCONJ
cana-2991	273	25	for	for	ADP
cana-2991	273	26	more	more	ADJ
cana-2991	273	27	depth	depth	NOUN
cana-2991	273	28	we	we	PRON
cana-2991	273	29	can	can	AUX
cana-2991	273	30	refer	refer	VERB
cana-2991	273	31	to	to	ADP
cana-2991	273	32	glove	glove	NOUN
cana-2991	273	33	.	.	PUNCT
cana-2991	274	1	2.4	2.4	NUM
cana-2991	274	2	.	.	PUNCT
cana-2991	274	3	architecture	architecture	NOUN
cana-2991	274	4	:	:	PUNCT
cana-2991	274	5	bert	bert	PROPN
cana-2991	274	6	(	(	PUNCT
cana-2991	274	7	bidirectional	bidirectional	ADJ
cana-2991	274	8	encoder	encoder	NOUN
cana-2991	274	9	representations	representation	VERB
cana-2991	274	10	from	from	ADP
cana-2991	274	11	transformers	transformer	NOUN
cana-2991	274	12	)	)	PUNCT
cana-2991	274	13	bert	bert	PROPN
cana-2991	274	14	is	be	AUX
cana-2991	274	15	a	a	DET
cana-2991	274	16	transformer	transformer	NOUN
cana-2991	274	17	-	-	PUNCT
cana-2991	274	18	based	base	VERB
cana-2991	274	19	model	model	NOUN
cana-2991	274	20	which	which	PRON
cana-2991	274	21	means	mean	VERB
cana-2991	274	22	bert	bert	PROPN
cana-2991	274	23	can	can	AUX
cana-2991	274	24	get	get	VERB
cana-2991	274	25	the	the	DET
cana-2991	274	26	full	full	ADJ
cana-2991	274	27	context	context	NOUN
cana-2991	274	28	of	of	ADP
cana-2991	274	29	words	word	NOUN
cana-2991	274	30	(	(	PUNCT
cana-2991	274	31	understand	understand	VERB
cana-2991	274	32	words	word	NOUN
cana-2991	274	33	better	well	ADV
cana-2991	274	34	)	)	PUNCT
cana-2991	274	35	because	because	SCONJ
cana-2991	274	36	it	it	PRON
cana-2991	274	37	takes	take	VERB
cana-2991	274	38	both	both	PRON
cana-2991	274	39	left	leave	VERB
cana-2991	274	40	and	and	CCONJ
cana-2991	274	41	right	right	ADJ
cana-2991	274	42	context	context	NOUN
cana-2991	274	43	while	while	SCONJ
cana-2991	274	44	representing	represent	VERB
cana-2991	274	45	the	the	DET
cana-2991	274	46	word	word	NOUN
cana-2991	274	47	in	in	ADP
cana-2991	274	48	that	that	DET
cana-2991	274	49	sentence	sentence	NOUN
cana-2991	274	50	.	.	PUNCT
cana-2991	275	1	instead	instead	ADV
cana-2991	275	2	of	of	ADP
cana-2991	275	3	treating	treat	VERB
cana-2991	275	4	words	word	NOUN
cana-2991	275	5	in	in	ADP
cana-2991	275	6	isolation	isolation	NOUN
cana-2991	275	7	,	,	PUNCT
cana-2991	275	8	the	the	DET
cana-2991	275	9	way	way	NOUN
cana-2991	275	10	that	that	PRON
cana-2991	275	11	traditional	traditional	ADJ
cana-2991	275	12	language	language	NOUN
cana-2991	275	13	models	model	NOUN
cana-2991	275	14	do	do	VERB
cana-2991	275	15	,	,	PUNCT
cana-2991	275	16	bert	bert	PROPN
cana-2991	275	17	learns	learn	VERB
cana-2991	275	18	relationships	relationship	NOUN
cana-2991	275	19	between	between	ADP
cana-2991	275	20	all	all	DET
cana-2991	275	21	words	word	NOUN
cana-2991	275	22	at	at	ADP
cana-2991	275	23	once	once	ADV
cana-2991	275	24	without	without	ADP
cana-2991	275	25	requiring	require	VERB
cana-2991	275	26	human	human	ADJ
cana-2991	275	27	labeling	labeling	NOUN
cana-2991	275	28	.	.	PUNCT
cana-2991	276	1	bert	bert	PROPN
cana-2991	276	2	objective	objective	NOUN
cana-2991	276	3	:	:	PUNCT
cana-2991	276	4	to	to	PART
cana-2991	276	5	predict	predict	VERB
cana-2991	276	6	masked	mask	VERB
cana-2991	276	7	words	word	NOUN
cana-2991	276	8	(	(	PUNCT
cana-2991	276	9	it	it	PRON
cana-2991	276	10	must	must	AUX
cana-2991	276	11	learn	learn	VERB
cana-2991	276	12	deep	deep	ADJ
cana-2991	276	13	contextual	contextual	ADJ
cana-2991	276	14	representation	representation	NOUN
cana-2991	276	15	!	!	PUNCT
cana-2991	276	16	)	)	PUNCT
cana-2991	277	1	𝐿𝐵𝐸𝑅𝑇	𝐿𝐵𝐸𝑅𝑇	PROPN
cana-2991	277	2	=	=	PUNCT
cana-2991	278	1	−	−	PROPN
cana-2991	278	2	∑	∑	PUNCT
cana-2991	278	3	𝑛	𝑛	DET
cana-2991	278	4	𝑖=1	𝑖=1	PROPN
cana-2991	278	5	𝑙𝑜𝑔𝑃(𝑤𝑖	𝑙𝑜𝑔𝑃(𝑤𝑖	PROPN
cana-2991	278	6	∣	∣	PROPN
cana-2991	278	7	𝑤1	𝑤1	PROPN
cana-2991	278	8	,	,	PUNCT
cana-2991	278	9	…	…	PUNCT
cana-2991	278	10	,	,	PUNCT
cana-2991	278	11	𝑤𝑖−1	𝑤𝑖−1	PROPN
cana-2991	278	12	,	,	PUNCT
cana-2991	278	13	𝑤𝑖+1	𝑤𝑖+1	NUM
cana-2991	278	14	,	,	PUNCT
cana-2991	278	15	…	…	PUNCT
cana-2991	278	16	,	,	PUNCT
cana-2991	278	17	𝑤𝑛	𝑤𝑛	PROPN
cana-2991	278	18	)	)	PUNCT
cana-2991	278	19	where	where	SCONJ
cana-2991	278	20	p(w_i∣⋅	p(w_i∣⋅	NOUN
cana-2991	278	21	)	)	PUNCT
cana-2991	278	22	is	be	AUX
cana-2991	278	23	the	the	DET
cana-2991	278	24	probability	probability	NOUN
cana-2991	278	25	of	of	ADP
cana-2991	278	26	w	w	NOUN
cana-2991	278	27	given	give	VERB
cana-2991	278	28	its	its	PRON
cana-2991	278	29	context	context	NOUN
cana-2991	278	30	.	.	PUNCT
cana-2991	279	1	since	since	SCONJ
cana-2991	279	2	bert	bert	PROPN
cana-2991	279	3	embeddings	embedding	NOUN
cana-2991	279	4	are	be	AUX
cana-2991	279	5	pre	pre	ADJ
cana-2991	279	6	-	-	VERB
cana-2991	279	7	trained	trained	ADJ
cana-2991	279	8	using	use	VERB
cana-2991	279	9	massive	massive	ADJ
cana-2991	279	10	corporate	corporate	ADJ
cana-2991	279	11	and	and	CCONJ
cana-2991	279	12	can	can	AUX
cana-2991	279	13	be	be	AUX
cana-2991	279	14	fine	fine	ADV
cana-2991	279	15	-	-	PUNCT
cana-2991	279	16	tuned	tune	VERB
cana-2991	279	17	on	on	ADP
cana-2991	279	18	the	the	DET
cana-2991	279	19	tasks	task	NOUN
cana-2991	279	20	,	,	PUNCT
cana-2991	279	21	they	they	PRON
cana-2991	279	22	show	show	VERB
cana-2991	279	23	great	great	ADJ
cana-2991	279	24	potential	potential	NOUN
cana-2991	279	25	in	in	ADP
cana-2991	279	26	detecting	detect	VERB
cana-2991	279	27	fake	fake	ADJ
cana-2991	279	28	news	news	NOUN
cana-2991	279	29	.	.	PUNCT
cana-2991	280	1	3	3	X
cana-2991	280	2	.	.	X
cana-2991	280	3	machine	machine	NOUN
cana-2991	280	4	learning	learn	VERB
cana-2991	280	5	classifiers	classifier	NOUN
cana-2991	280	6	after	after	ADP
cana-2991	280	7	converting	convert	VERB
cana-2991	280	8	text	text	NOUN
cana-2991	280	9	into	into	ADP
cana-2991	280	10	numeric	numeric	ADJ
cana-2991	280	11	vectors	vector	NOUN
cana-2991	280	12	using	use	VERB
cana-2991	280	13	the	the	DET
cana-2991	280	14	embedding	embed	VERB
cana-2991	280	15	models	model	NOUN
cana-2991	280	16	mentioned	mention	VERB
cana-2991	281	1	,	,	PUNCT
cana-2991	281	2	we	we	PRON
cana-2991	281	3	pass	pass	VERB
cana-2991	281	4	these	these	DET
cana-2991	281	5	vectors	vector	NOUN
cana-2991	281	6	through	through	ADP
cana-2991	281	7	machine	machine	NOUN
cana-2991	281	8	learning	learn	VERB
cana-2991	281	9	classifiers	classifier	NOUN
cana-2991	281	10	to	to	PART
cana-2991	281	11	determine	determine	VERB
cana-2991	281	12	if	if	SCONJ
cana-2991	281	13	a	a	DET
cana-2991	281	14	news	news	NOUN
cana-2991	281	15	article	article	NOUN
cana-2991	281	16	is	be	AUX
cana-2991	281	17	real	real	ADJ
cana-2991	281	18	or	or	CCONJ
cana-2991	281	19	fake	fake	ADJ
cana-2991	281	20	.	.	PUNCT
cana-2991	282	1	the	the	DET
cana-2991	282	2	research	research	NOUN
cana-2991	282	3	used	use	VERB
cana-2991	282	4	logistic	logistic	ADJ
cana-2991	282	5	regression	regression	NOUN
cana-2991	282	6	,	,	PUNCT
cana-2991	282	7	random	random	ADJ
cana-2991	282	8	forests	forest	NOUN
cana-2991	282	9	and	and	CCONJ
cana-2991	282	10	a	a	DET
cana-2991	282	11	neural	neural	ADJ
cana-2991	282	12	network	network	NOUN
cana-2991	282	13	classifier	classifier	NOUN
cana-2991	282	14	.	.	PUNCT
cana-2991	283	1	3.1	3.1	NUM
cana-2991	283	2	.	.	PUNCT
cana-2991	284	1	logistic	logistic	ADJ
cana-2991	284	2	regression	regression	NOUN
cana-2991	284	3	logistic	logistic	ADJ
cana-2991	284	4	regression	regression	NOUN
cana-2991	284	5	is	be	AUX
cana-2991	284	6	a	a	DET
cana-2991	284	7	linear	linear	ADJ
cana-2991	284	8	classifier	classifier	NOUN
cana-2991	284	9	,	,	PUNCT
cana-2991	284	10	in	in	ADP
cana-2991	284	11	which	which	PRON
cana-2991	284	12	the	the	DET
cana-2991	284	13	probability	probability	NOUN
cana-2991	284	14	of	of	ADP
cana-2991	284	15	a	a	DET
cana-2991	284	16	binary	binary	ADJ
cana-2991	284	17	outcome	outcome	NOUN
cana-2991	284	18	is	be	AUX
cana-2991	284	19	modelled	model	VERB
cana-2991	284	20	as	as	ADP
cana-2991	284	21	a	a	DET
cana-2991	284	22	function	function	NOUN
cana-2991	284	23	of	of	ADP
cana-2991	284	24	input	input	NOUN
cana-2991	284	25	features	feature	NOUN
cana-2991	284	26	.	.	PUNCT
cana-2991	285	1	where	where	SCONJ
cana-2991	285	2	the	the	DET
cana-2991	285	3	logistic	logistic	ADJ
cana-2991	285	4	regression	regression	NOUN
cana-2991	285	5	encompasses	encompass	VERB
cana-2991	285	6	from	from	ADP
cana-2991	285	7	logistics	logistic	NOUN
cana-2991	285	8	importing	import	VERB
cana-2991	285	9	model	model	NOUN
cana-2991	285	10	:	:	PUNCT
cana-2991	285	11	𝑃(𝑦	𝑃(𝑦	X
cana-2991	285	12	=	=	SYM
cana-2991	285	13	1	1	NUM
cana-2991	285	14	∣	∣	PROPN
cana-2991	285	15	𝑥	𝑥	NOUN
cana-2991	285	16	)	)	PUNCT
cana-2991	285	17	=	=	SYM
cana-2991	286	1	1	1	NUM
cana-2991	286	2	1	1	NUM
cana-2991	286	3	+	+	CCONJ
cana-2991	286	4	𝑒𝑥𝑝(−(𝑤⊤𝑥	𝑒𝑥𝑝(−(𝑤⊤𝑥	VERB
cana-2991	286	5	+	+	CCONJ
cana-2991	286	6	𝑏	𝑏	NOUN
cana-2991	286	7	)	)	PUNCT
cana-2991	286	8	)	)	PUNCT
cana-2991	286	9	where	where	SCONJ
cana-2991	286	10	,	,	PUNCT
cana-2991	286	11	w	w	PROPN
cana-2991	286	12	is	be	AUX
cana-2991	286	13	the	the	DET
cana-2991	286	14	weight	weight	NOUN
cana-2991	286	15	vector	vector	NOUN
cana-2991	286	16	,	,	PUNCT
cana-2991	286	17	x	x	X
cana-2991	286	18	is	be	AUX
cana-2991	286	19	the	the	DET
cana-2991	286	20	feature	feature	NOUN
cana-2991	286	21	vector	vector	NOUN
cana-2991	286	22	,	,	PUNCT
cana-2991	286	23	and	and	CCONJ
cana-2991	286	24	b	b	NOUN
cana-2991	286	25	is	be	AUX
cana-2991	286	26	a	a	DET
cana-2991	286	27	bias	bias	NOUN
cana-2991	286	28	term	term	NOUN
cana-2991	286	29	.	.	PUNCT
cana-2991	287	1	in	in	ADP
cana-2991	287	2	this	this	DET
cana-2991	287	3	case	case	NOUN
cana-2991	287	4	,	,	PUNCT
cana-2991	287	5	logistic	logistic	ADJ
cana-2991	287	6	regression	regression	NOUN
cana-2991	287	7	works	work	VERB
cana-2991	287	8	well	well	ADV
cana-2991	287	9	enough	enough	ADV
cana-2991	287	10	for	for	ADP
cana-2991	287	11	simple	simple	ADJ
cana-2991	287	12	datasets	dataset	NOUN
cana-2991	287	13	but	but	CCONJ
cana-2991	287	14	not	not	PART
cana-2991	287	15	when	when	SCONJ
cana-2991	287	16	you	you	PRON
cana-2991	287	17	deal	deal	VERB
cana-2991	287	18	with	with	ADP
cana-2991	287	19	high	high	ADJ
cana-2991	287	20	-	-	PUNCT
cana-2991	287	21	dimensional	dimensional	ADJ
cana-2991	287	22	data	datum	NOUN
cana-2991	287	23	as	as	SCONJ
cana-2991	287	24	seen	see	VERB
cana-2991	287	25	from	from	ADP
cana-2991	287	26	word	word	NOUN
cana-2991	287	27	embeddings	embedding	NOUN
cana-2991	287	28	and	and	CCONJ
cana-2991	287	29	thus	thus	ADV
cana-2991	287	30	could	could	AUX
cana-2991	287	31	n't	not	PART
cana-2991	287	32	capture	capture	VERB
cana-2991	287	33	the	the	DET
cana-2991	287	34	relations	relation	NOUN
cana-2991	287	35	between	between	ADP
cana-2991	287	36	the	the	DET
cana-2991	287	37	texts	text	NOUN
cana-2991	287	38	.	.	PUNCT
cana-2991	288	1	communications	communication	NOUN
cana-2991	288	2	on	on	ADP
cana-2991	288	3	applied	apply	VERB
cana-2991	288	4	nonlinear	nonlinear	ADJ
cana-2991	288	5	analysis	analysis	NOUN
cana-2991	288	6	issn	issn	NOUN
cana-2991	288	7	:	:	PUNCT
cana-2991	288	8	1074	1074	NUM
cana-2991	288	9	-	-	PUNCT
cana-2991	288	10	133x	133x	NUM
cana-2991	288	11	vol	vol	NOUN
cana-2991	288	12	32	32	NUM
cana-2991	288	13	no	no	NOUN
cana-2991	288	14	.	.	PUNCT
cana-2991	289	1	5s	5s	NUM
cana-2991	289	2	(	(	PUNCT
cana-2991	289	3	2025	2025	NUM
cana-2991	289	4	)	)	PUNCT
cana-2991	289	5	165	165	NUM
cana-2991	289	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	289	7	3.2	3.2	NUM
cana-2991	289	8	.	.	PUNCT
cana-2991	290	1	random	random	ADJ
cana-2991	290	2	forests	forest	NOUN
cana-2991	290	3	random	random	ADJ
cana-2991	290	4	forests	forest	NOUN
cana-2991	290	5	:	:	PUNCT
cana-2991	290	6	random	random	ADJ
cana-2991	290	7	forests	forest	NOUN
cana-2991	290	8	are	be	AUX
cana-2991	290	9	an	an	DET
cana-2991	290	10	ensemble	ensemble	ADJ
cana-2991	290	11	learning	learning	NOUN
cana-2991	290	12	method	method	NOUN
cana-2991	290	13	for	for	ADP
cana-2991	290	14	classification	classification	NOUN
cana-2991	290	15	,	,	PUNCT
cana-2991	290	16	regressing	regress	VERB
cana-2991	290	17	and	and	CCONJ
cana-2991	290	18	other	other	ADJ
cana-2991	290	19	tasks	task	NOUN
cana-2991	290	20	that	that	PRON
cana-2991	290	21	operate	operate	VERB
cana-2991	290	22	by	by	ADP
cana-2991	290	23	constructing	construct	VERB
cana-2991	290	24	a	a	DET
cana-2991	290	25	multitude	multitude	NOUN
cana-2991	290	26	of	of	ADP
cana-2991	290	27	decision	decision	NOUN
cana-2991	290	28	trees	tree	NOUN
cana-2991	290	29	during	during	ADP
cana-2991	290	30	training	training	NOUN
cana-2991	290	31	and	and	CCONJ
cana-2991	290	32	outputting	output	VERB
cana-2991	290	33	the	the	DET
cana-2991	290	34	mode	mode	NOUN
cana-2991	290	35	of	of	ADP
cana-2991	290	36	the	the	DET
cana-2991	290	37	classes	class	NOUN
cana-2991	290	38	predicted	predict	VERB
cana-2991	290	39	individually	individually	ADV
cana-2991	290	40	.	.	PUNCT
cana-2991	291	1	the	the	DET
cana-2991	291	2	random	random	ADJ
cana-2991	291	3	forest	forest	NOUN
cana-2991	291	4	model	model	NOUN
cana-2991	291	5	can	can	AUX
cana-2991	291	6	work	work	VERB
cana-2991	291	7	with	with	ADP
cana-2991	291	8	high	high	ADJ
cana-2991	291	9	-	-	PUNCT
cana-2991	291	10	dimensional	dimensional	ADJ
cana-2991	291	11	inputs	input	NOUN
cana-2991	291	12	,	,	PUNCT
cana-2991	291	13	and	and	CCONJ
cana-2991	291	14	provide	provide	VERB
cana-2991	291	15	a	a	DET
cana-2991	291	16	defence	defence	NOUN
cana-2991	291	17	against	against	ADP
cana-2991	291	18	overfitting	overfitte	VERB
cana-2991	291	19	:	:	PUNCT
cana-2991	291	20	�	�	PROPN
cana-2991	291	21	̂	̂	SYM
cana-2991	291	22	�	�	NOUN
cana-2991	291	23	=	=	SYM
cana-2991	291	24	𝑚𝑜𝑑𝑒({𝑇𝑖(𝑥)}𝑖=1	𝑚𝑜𝑑𝑒({𝑇𝑖(𝑥)}𝑖=1	NOUN
cana-2991	291	25	𝑁	𝑁	PROPN
cana-2991	291	26	)	)	PUNCT
cana-2991	291	27	where	where	SCONJ
cana-2991	291	28	t_i	t_i	PROPN
cana-2991	291	29	is	be	AUX
cana-2991	291	30	the	the	DET
cana-2991	291	31	i	i	PROPN
cana-2991	291	32	-	-	PUNCT
cana-2991	291	33	th	th	VERB
cana-2991	291	34	decision	decision	NOUN
cana-2991	291	35	tree	tree	NOUN
cana-2991	291	36	and	and	CCONJ
cana-2991	291	37	y_hat	y_hat	PRON
cana-2991	291	38	the	the	DET
cana-2991	291	39	predicted	predict	VERB
cana-2991	291	40	label	label	NOUN
cana-2991	291	41	.	.	PUNCT
cana-2991	292	1	3.3	3.3	NUM
cana-2991	292	2	.	.	PUNCT
cana-2991	293	1	neural	neural	ADJ
cana-2991	293	2	networks	network	NOUN
cana-2991	293	3	neural	neural	ADJ
cana-2991	293	4	networks	network	NOUN
cana-2991	293	5	form	form	VERB
cana-2991	293	6	the	the	DET
cana-2991	293	7	most	most	ADV
cana-2991	293	8	popular	popular	ADJ
cana-2991	293	9	architecture	architecture	NOUN
cana-2991	293	10	for	for	ADP
cana-2991	293	11	classification	classification	NOUN
cana-2991	293	12	of	of	ADP
cana-2991	293	13	data	datum	NOUN
cana-2991	293	14	that	that	PRON
cana-2991	293	15	can	can	AUX
cana-2991	293	16	provide	provide	VERB
cana-2991	293	17	flexibility	flexibility	NOUN
cana-2991	293	18	to	to	PART
cana-2991	293	19	capture	capture	VERB
cana-2991	293	20	complex	complex	ADJ
cana-2991	293	21	patterns	pattern	NOUN
cana-2991	293	22	due	due	ADP
cana-2991	293	23	to	to	ADP
cana-2991	293	24	their	their	PRON
cana-2991	293	25	layer	layer	NOUN
cana-2991	293	26	by	by	ADP
cana-2991	293	27	layer	layer	NOUN
cana-2991	293	28	stacking	stacking	NOUN
cana-2991	293	29	of	of	ADP
cana-2991	293	30	neurons	neuron	NOUN
cana-2991	293	31	.	.	PUNCT
cana-2991	294	1	a	a	DET
cana-2991	294	2	neural	neural	ADJ
cana-2991	294	3	network	network	NOUN
cana-2991	294	4	has	have	VERB
cana-2991	294	5	the	the	DET
cana-2991	294	6	basic	basic	ADJ
cana-2991	294	7	architecture	architecture	NOUN
cana-2991	294	8	of	of	ADP
cana-2991	294	9	an	an	DET
cana-2991	294	10	input	input	NOUN
cana-2991	294	11	layer	layer	NOUN
cana-2991	294	12	,	,	PUNCT
cana-2991	294	13	a	a	DET
cana-2991	294	14	few	few	ADJ
cana-2991	294	15	hidden	hidden	ADJ
cana-2991	294	16	layers	layer	NOUN
cana-2991	294	17	(	(	PUNCT
cana-2991	294	18	1	1	NUM
cana-2991	294	19	or	or	CCONJ
cana-2991	294	20	more	more	ADJ
cana-2991	294	21	)	)	PUNCT
cana-2991	294	22	,	,	PUNCT
cana-2991	294	23	and	and	CCONJ
cana-2991	294	24	an	an	DET
cana-2991	294	25	output	output	NOUN
cana-2991	294	26	layer	layer	NOUN
cana-2991	294	27	.	.	PUNCT
cana-2991	295	1	when	when	SCONJ
cana-2991	295	2	it	it	PRON
cana-2991	295	3	comes	come	VERB
cana-2991	295	4	to	to	ADP
cana-2991	295	5	a	a	DET
cana-2991	295	6	binary	binary	ADJ
cana-2991	295	7	classifier	classifier	NOUN
cana-2991	295	8	this	this	PRON
cana-2991	295	9	is	be	AUX
cana-2991	295	10	usually	usually	ADV
cana-2991	295	11	performed	perform	VERB
cana-2991	295	12	using	use	VERB
cana-2991	295	13	the	the	DET
cana-2991	295	14	activation	activation	NOUN
cana-2991	295	15	function	function	NOUN
cana-2991	295	16	sigmoid	sigmoid	NOUN
cana-2991	295	17	:	:	PUNCT
cana-2991	295	18	�	�	PROPN
cana-2991	295	19	̂	̂	SYM
cana-2991	295	20	�	�	NOUN
cana-2991	295	21	=	=	SYM
cana-2991	295	22	𝜎(𝑊𝐿ℎ𝐿−1	𝜎(𝑊𝐿ℎ𝐿−1	PROPN
cana-2991	295	23	+	+	NUM
cana-2991	295	24	𝑏𝐿	𝑏𝐿	PROPN
cana-2991	295	25	)	)	PUNCT
cana-2991	295	26	with	with	ADP
cana-2991	295	27	w_l	w_l	PROPN
cana-2991	295	28	and	and	CCONJ
cana-2991	295	29	b_l	b_l	DET
cana-2991	295	30	the	the	DET
cana-2991	295	31	weights	weight	NOUN
cana-2991	295	32	and	and	CCONJ
cana-2991	295	33	bias	bias	NOUN
cana-2991	295	34	of	of	ADP
cana-2991	295	35	the	the	DET
cana-2991	295	36	final	final	ADJ
cana-2991	295	37	layer	layer	NOUN
cana-2991	295	38	,	,	PUNCT
cana-2991	295	39	respectively	respectively	ADV
cana-2991	295	40	,	,	PUNCT
cana-2991	295	41	and	and	CCONJ
cana-2991	295	42	h(l−1	h(l−1	NOUN
cana-2991	295	43	)	)	PUNCT
cana-2991	295	44	is	be	AUX
cana-2991	295	45	the	the	DET
cana-2991	295	46	activation	activation	NOUN
cana-2991	295	47	of	of	ADP
cana-2991	295	48	the	the	DET
cana-2991	295	49	penultimate	penultimate	NOUN
cana-2991	295	50	layer	layer	NOUN
cana-2991	295	51	.	.	PUNCT
cana-2991	296	1	fake	fake	ADJ
cana-2991	296	2	news	news	NOUN
cana-2991	296	3	detection	detection	NOUN
cana-2991	296	4	is	be	AUX
cana-2991	296	5	complex	complex	ADJ
cana-2991	296	6	neural	neural	ADJ
cana-2991	296	7	networks	network	NOUN
cana-2991	296	8	are	be	AUX
cana-2991	296	9	able	able	ADJ
cana-2991	296	10	to	to	PART
cana-2991	296	11	capture	capture	VERB
cana-2991	296	12	these	these	DET
cana-2991	296	13	non	non	ADJ
cana-2991	296	14	-	-	ADJ
cana-2991	296	15	linear	linear	ADJ
cana-2991	296	16	relationships	relationship	NOUN
cana-2991	296	17	due	due	ADP
cana-2991	296	18	to	to	ADP
cana-2991	296	19	their	their	PRON
cana-2991	296	20	extreme	extreme	ADJ
cana-2991	296	21	flexibility	flexibility	NOUN
cana-2991	296	22	.	.	PUNCT
cana-2991	297	1	4	4	X
cana-2991	297	2	.	.	NUM
cana-2991	297	3	distributed	distribute	VERB
cana-2991	297	4	processing	processing	NOUN
cana-2991	297	5	for	for	ADP
cana-2991	297	6	scalability	scalability	NOUN
cana-2991	297	7	in	in	ADP
cana-2991	297	8	order	order	NOUN
cana-2991	297	9	to	to	PART
cana-2991	297	10	make	make	VERB
cana-2991	297	11	sure	sure	ADJ
cana-2991	297	12	the	the	DET
cana-2991	297	13	fake	fake	ADJ
cana-2991	297	14	news	news	NOUN
cana-2991	297	15	detection	detection	NOUN
cana-2991	297	16	system	system	NOUN
cana-2991	297	17	can	can	AUX
cana-2991	297	18	scale	scale	VERB
cana-2991	297	19	well	well	ADV
cana-2991	297	20	,	,	PUNCT
cana-2991	297	21	we	we	PRON
cana-2991	297	22	have	have	AUX
cana-2991	297	23	used	use	VERB
cana-2991	297	24	distributed	distribute	VERB
cana-2991	297	25	processing	processing	NOUN
cana-2991	297	26	frameworks	framework	NOUN
cana-2991	297	27	like	like	ADP
cana-2991	297	28	apache	apache	NOUN
cana-2991	297	29	spark	spark	NOUN
cana-2991	297	30	.	.	PUNCT
cana-2991	298	1	with	with	ADP
cana-2991	298	2	this	this	DET
cana-2991	298	3	feature	feature	NOUN
cana-2991	298	4	,	,	PUNCT
cana-2991	298	5	the	the	DET
cana-2991	298	6	system	system	NOUN
cana-2991	298	7	can	can	AUX
cana-2991	298	8	handle	handle	VERB
cana-2991	298	9	large	large	ADJ
cana-2991	298	10	datasets	dataset	NOUN
cana-2991	298	11	since	since	SCONJ
cana-2991	298	12	it	it	PRON
cana-2991	298	13	shares	share	VERB
cana-2991	298	14	the	the	DET
cana-2991	298	15	processing	processing	NOUN
cana-2991	298	16	to	to	ADP
cana-2991	298	17	hundreds	hundred	NOUN
cana-2991	298	18	of	of	ADP
cana-2991	298	19	nodes	node	NOUN
cana-2991	298	20	in	in	ADP
cana-2991	298	21	a	a	DET
cana-2991	298	22	computing	computing	NOUN
cana-2991	298	23	cluster	cluster	NOUN
cana-2991	298	24	.	.	PUNCT
cana-2991	299	1	advantages	advantage	NOUN
cana-2991	299	2	of	of	ADP
cana-2991	299	3	spark	spark	NOUN
cana-2991	299	4	framework	framework	NOUN
cana-2991	299	5	:	:	PUNCT
cana-2991	299	6	the	the	DET
cana-2991	299	7	underlying	underlie	VERB
cana-2991	299	8	architecture	architecture	NOUN
cana-2991	299	9	of	of	ADP
cana-2991	299	10	spark	spark	NOUN
cana-2991	299	11	is	be	AUX
cana-2991	299	12	optimised	optimise	VERB
cana-2991	299	13	to	to	PART
cana-2991	299	14	parallelize	parallelize	VERB
cana-2991	299	15	the	the	DET
cana-2991	299	16	steps	step	NOUN
cana-2991	299	17	for	for	ADP
cana-2991	299	18	both	both	PRON
cana-2991	299	19	preprocessing	preprocessing	NOUN
cana-2991	299	20	and	and	CCONJ
cana-2991	299	21	model	model	NOUN
cana-2991	299	22	training	training	NOUN
cana-2991	299	23	so	so	SCONJ
cana-2991	299	24	that	that	SCONJ
cana-2991	299	25	while	while	SCONJ
cana-2991	299	26	dealing	deal	VERB
cana-2991	299	27	with	with	ADP
cana-2991	299	28	large	large	ADJ
cana-2991	299	29	datasets	dataset	NOUN
cana-2991	299	30	the	the	DET
cana-2991	299	31	similar	similar	ADJ
cana-2991	299	32	step	step	NOUN
cana-2991	299	33	can	can	AUX
cana-2991	299	34	be	be	AUX
cana-2991	299	35	processed	process	VERB
cana-2991	299	36	on	on	ADP
cana-2991	299	37	other	other	ADJ
cana-2991	299	38	parts	part	NOUN
cana-2991	299	39	concurrently	concurrently	ADV
cana-2991	299	40	.	.	PUNCT
cana-2991	300	1	scalability	scalability	NOUN
cana-2991	300	2	:	:	PUNCT
cana-2991	300	3	spark	spark	NOUN
cana-2991	300	4	can	can	AUX
cana-2991	300	5	scale	scale	VERB
cana-2991	300	6	to	to	ADP
cana-2991	300	7	multiple	multiple	ADJ
cana-2991	300	8	nodes	node	NOUN
cana-2991	300	9	,	,	PUNCT
cana-2991	300	10	which	which	PRON
cana-2991	300	11	can	can	AUX
cana-2991	300	12	make	make	VERB
cana-2991	300	13	millions	million	NOUN
cana-2991	300	14	of	of	ADP
cana-2991	300	15	news	news	NOUN
cana-2991	300	16	within	within	ADP
cana-2991	300	17	minutes	minute	NOUN
cana-2991	300	18	in	in	ADP
cana-2991	300	19	real	real	ADJ
cana-2991	300	20	-	-	PUNCT
cana-2991	300	21	time	time	NOUN
cana-2991	300	22	.	.	PUNCT
cana-2991	301	1	if	if	SCONJ
cana-2991	301	2	a	a	DET
cana-2991	301	3	particular	particular	ADJ
cana-2991	301	4	node	node	NOUN
cana-2991	301	5	were	be	AUX
cana-2991	301	6	to	to	PART
cana-2991	301	7	fail	fail	VERB
cana-2991	301	8	,	,	PUNCT
cana-2991	301	9	spark	spark	NOUN
cana-2991	301	10	is	be	AUX
cana-2991	301	11	able	able	ADJ
cana-2991	301	12	to	to	PART
cana-2991	301	13	recover	recover	VERB
cana-2991	301	14	from	from	ADP
cana-2991	301	15	these	these	DET
cana-2991	301	16	failures	failure	NOUN
cana-2991	301	17	while	while	SCONJ
cana-2991	301	18	keeping	keep	VERB
cana-2991	301	19	all	all	DET
cana-2991	301	20	your	your	PRON
cana-2991	301	21	data	datum	NOUN
cana-2991	301	22	and	and	CCONJ
cana-2991	301	23	state	state	NOUN
cana-2991	301	24	progress	progress	NOUN
cana-2991	301	25	through	through	ADP
cana-2991	301	26	fault	fault	NOUN
cana-2991	301	27	-	-	PUNCT
cana-2991	301	28	tolerant	tolerant	ADJ
cana-2991	301	29	properties	property	NOUN
cana-2991	301	30	of	of	ADP
cana-2991	301	31	the	the	DET
cana-2991	301	32	architecture	architecture	NOUN
cana-2991	301	33	.	.	PUNCT
cana-2991	302	1	the	the	DET
cana-2991	302	2	distributed	distribute	VERB
cana-2991	302	3	processing	processing	NOUN
cana-2991	302	4	integration	integration	NOUN
cana-2991	302	5	ensures	ensure	VERB
cana-2991	302	6	that	that	SCONJ
cana-2991	302	7	our	our	PRON
cana-2991	302	8	system	system	NOUN
cana-2991	302	9	proposal	proposal	NOUN
cana-2991	302	10	is	be	AUX
cana-2991	302	11	also	also	ADV
cana-2991	302	12	scalable	scalable	ADJ
cana-2991	302	13	for	for	ADP
cana-2991	302	14	the	the	DET
cana-2991	302	15	largescale	largescale	ADJ
cana-2991	302	16	real	real	ADJ
cana-2991	302	17	world	world	NOUN
cana-2991	302	18	datasets	dataset	NOUN
cana-2991	302	19	,	,	PUNCT
cana-2991	302	20	such	such	ADJ
cana-2991	302	21	as	as	ADP
cana-2991	302	22	the	the	DET
cana-2991	302	23	social	social	ADJ
cana-2991	302	24	media	medium	NOUN
cana-2991	302	25	data	datum	NOUN
cana-2991	302	26	.	.	PUNCT
cana-2991	303	1	5	5	X
cana-2991	303	2	.	.	X
cana-2991	303	3	experimental	experimental	ADJ
cana-2991	303	4	setup	setup	NOUN
cana-2991	303	5	experiments	experiment	NOUN
cana-2991	303	6	were	be	AUX
cana-2991	303	7	performed	perform	VERB
cana-2991	303	8	to	to	PART
cana-2991	303	9	evaluate	evaluate	VERB
cana-2991	303	10	the	the	DET
cana-2991	303	11	performance	performance	NOUN
cana-2991	303	12	of	of	ADP
cana-2991	303	13	the	the	DET
cana-2991	303	14	proposed	propose	VERB
cana-2991	303	15	system	system	NOUN
cana-2991	303	16	using	use	VERB
cana-2991	303	17	two	two	NUM
cana-2991	303	18	wellknown	wellknown	ADJ
cana-2991	303	19	fake	fake	ADJ
cana-2991	303	20	news	news	NOUN
cana-2991	303	21	datasets	dataset	NOUN
cana-2991	303	22	,	,	PUNCT
cana-2991	303	23	politifact	politifact	PROPN
cana-2991	303	24	and	and	CCONJ
cana-2991	303	25	liar	liar	NOUN
cana-2991	303	26	dataset	dataset	NOUN
cana-2991	303	27	.	.	PUNCT
cana-2991	304	1	both	both	PRON
cana-2991	304	2	are	be	AUX
cana-2991	304	3	datasets	dataset	NOUN
cana-2991	304	4	of	of	ADP
cana-2991	304	5	labelled	label	VERB
cana-2991	304	6	news	news	NOUN
cana-2991	304	7	articles	article	NOUN
cana-2991	304	8	tagged	tag	VERB
cana-2991	304	9	as	as	ADP
cana-2991	304	10	either	either	CCONJ
cana-2991	304	11	real	real	ADJ
cana-2991	304	12	or	or	CCONJ
cana-2991	304	13	fake	fake	ADJ
cana-2991	304	14	.	.	PUNCT
cana-2991	305	1	communications	communication	NOUN
cana-2991	305	2	on	on	ADP
cana-2991	305	3	applied	apply	VERB
cana-2991	305	4	nonlinear	nonlinear	ADJ
cana-2991	305	5	analysis	analysis	NOUN
cana-2991	305	6	issn	issn	NOUN
cana-2991	305	7	:	:	PUNCT
cana-2991	305	8	1074	1074	NUM
cana-2991	305	9	-	-	PUNCT
cana-2991	305	10	133x	133x	NUM
cana-2991	305	11	vol	vol	NOUN
cana-2991	305	12	32	32	NUM
cana-2991	305	13	no	no	NOUN
cana-2991	305	14	.	.	PUNCT
cana-2991	306	1	5s	5s	NUM
cana-2991	306	2	(	(	PUNCT
cana-2991	306	3	2025	2025	NUM
cana-2991	306	4	)	)	PUNCT
cana-2991	306	5	166	166	NUM
cana-2991	306	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	306	7	in	in	ADP
cana-2991	306	8	the	the	DET
cana-2991	306	9	testing	testing	NOUN
cana-2991	306	10	phase	phase	NOUN
cana-2991	306	11	,	,	PUNCT
cana-2991	306	12	we	we	PRON
cana-2991	306	13	evaluated	evaluate	VERB
cana-2991	306	14	model	model	NOUN
cana-2991	306	15	performance	performance	NOUN
cana-2991	306	16	according	accord	VERB
cana-2991	306	17	to	to	ADP
cana-2991	306	18	common	common	ADJ
cana-2991	306	19	classification	classification	NOUN
cana-2991	306	20	metrics	metric	NOUN
cana-2991	306	21	such	such	ADJ
cana-2991	306	22	as	as	ADP
cana-2991	306	23	accuracy	accuracy	NOUN
cana-2991	306	24	,	,	PUNCT
cana-2991	306	25	precision	precision	NOUN
cana-2991	306	26	,	,	PUNCT
cana-2991	306	27	recall	recall	NOUN
cana-2991	306	28	and	and	CCONJ
cana-2991	306	29	f1	f1	NOUN
cana-2991	306	30	-	-	PUNCT
cana-2991	306	31	score	score	NOUN
cana-2991	306	32	.	.	PUNCT
cana-2991	307	1	at	at	ADP
cana-2991	307	2	rate	rate	NOUN
cana-2991	307	3	5	5	NUM
cana-2991	307	4	,	,	PUNCT
cana-2991	307	5	these	these	DET
cana-2991	307	6	metrics	metric	NOUN
cana-2991	307	7	are	be	AUX
cana-2991	307	8	defined	define	VERB
cana-2991	307	9	as	as	ADP
cana-2991	307	10	accuracy	accuracy	NOUN
cana-2991	307	11	:	:	PUNCT
cana-2991	307	12	percentage	percentage	NOUN
cana-2991	307	13	of	of	ADP
cana-2991	307	14	all	all	PRON
cana-2991	307	15	correctly	correctly	ADV
cana-2991	307	16	predicted	predict	VERB
cana-2991	307	17	labels	label	NOUN
cana-2991	307	18	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	PROPN
cana-2991	307	19	=	=	SYM
cana-2991	307	20	𝑇𝑃	𝑇𝑃	PROPN
cana-2991	307	21	+	+	CCONJ
cana-2991	307	22	𝑇𝑁	𝑇𝑁	PROPN
cana-2991	307	23	𝑇𝑃	𝑇𝑃	PROPN
cana-2991	307	24	+	+	CCONJ
cana-2991	307	25	𝑇𝑁	𝑇𝑁	PROPN
cana-2991	307	26	+	+	NUM
cana-2991	307	27	𝐹𝑃	𝐹𝑃	NOUN
cana-2991	308	1	+	+	CCONJ
cana-2991	308	2	𝐹𝑁	𝐹𝑁	PROPN
cana-2991	308	3	i.e.	i.e.	X
cana-2991	308	4	,	,	PUNCT
cana-2991	308	5	tp	tp	ADP
cana-2991	308	6	=	=	PUNCT
cana-2991	308	7	true	true	ADJ
cana-2991	308	8	positive	positive	ADJ
cana-2991	308	9	,	,	PUNCT
cana-2991	308	10	tn	tn	NOUN
cana-2991	308	11	=	=	PUNCT
cana-2991	308	12	true	true	ADJ
cana-2991	308	13	negative	negative	ADJ
cana-2991	308	14	,	,	PUNCT
cana-2991	308	15	fp	fp	PROPN
cana-2991	308	16	=	=	NUM
cana-2991	308	17	false	false	ADJ
cana-2991	308	18	positive	positive	ADJ
cana-2991	308	19	and	and	CCONJ
cana-2991	308	20	fn	fn	NOUN
cana-2991	308	21	=	=	ADJ
cana-2991	308	22	false	false	ADJ
cana-2991	308	23	negative	negative	ADJ
cana-2991	308	24	.	.	PUNCT
cana-2991	308	25	precision	precision	NOUN
cana-2991	308	26	:	:	PUNCT
cana-2991	308	27	the	the	DET
cana-2991	308	28	total	total	ADJ
cana-2991	308	29	number	number	NOUN
cana-2991	308	30	of	of	ADP
cana-2991	308	31	positive	positive	ADJ
cana-2991	308	32	instances	instance	NOUN
cana-2991	308	33	that	that	PRON
cana-2991	308	34	were	be	AUX
cana-2991	308	35	actually	actually	ADV
cana-2991	308	36	predicted	predict	VERB
cana-2991	308	37	as	as	ADP
cana-2991	308	38	positives	positive	NOUN
cana-2991	308	39	out	out	ADP
cana-2991	308	40	of	of	ADP
cana-2991	308	41	all	all	DET
cana-2991	308	42	the	the	DET
cana-2991	308	43	predicted	predict	VERB
cana-2991	308	44	positive	positive	ADJ
cana-2991	308	45	instances	instance	NOUN
cana-2991	308	46	.	.	PUNCT
cana-2991	309	1	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	PROPN
cana-2991	309	2	=	=	SYM
cana-2991	309	3	𝑇𝑃	𝑇𝑃	PROPN
cana-2991	309	4	𝑇𝑃	𝑇𝑃	PROPN
cana-2991	309	5	+	+	CCONJ
cana-2991	309	6	𝐹𝑃	𝐹𝑃	PROPN
cana-2991	309	7	recall	recall	NOUN
cana-2991	309	8	:	:	PUNCT
cana-2991	309	9	the	the	DET
cana-2991	309	10	number	number	NOUN
cana-2991	309	11	of	of	ADP
cana-2991	309	12	positive	positive	ADJ
cana-2991	309	13	instances	instance	NOUN
cana-2991	309	14	predicted	predict	VERB
cana-2991	309	15	correctly	correctly	ADV
cana-2991	309	16	out	out	ADP
cana-2991	309	17	of	of	ADP
cana-2991	309	18	all	all	DET
cana-2991	309	19	actual	actual	ADJ
cana-2991	309	20	positive	positive	ADJ
cana-2991	309	21	instances	instance	NOUN
cana-2991	309	22	.	.	PUNCT
cana-2991	310	1	𝑅𝑒𝑐𝑎𝑙𝑙	𝑅𝑒𝑐𝑎𝑙𝑙	PROPN
cana-2991	310	2	=	=	SYM
cana-2991	310	3	𝑇𝑃	𝑇𝑃	PROPN
cana-2991	310	4	𝑇𝑃	𝑇𝑃	PROPN
cana-2991	310	5	+	+	CCONJ
cana-2991	310	6	𝐹𝑁	𝐹𝑁	PROPN
cana-2991	310	7	f1	f1	NOUN
cana-2991	310	8	-	-	PUNCT
cana-2991	310	9	score	score	NOUN
cana-2991	310	10	:	:	PUNCT
cana-2991	310	11	the	the	DET
cana-2991	310	12	mean	mean	NOUN
cana-2991	310	13	of	of	ADP
cana-2991	310	14	the	the	DET
cana-2991	310	15	precision	precision	NOUN
cana-2991	310	16	and	and	CCONJ
cana-2991	310	17	recall	recall	NOUN
cana-2991	310	18	:	:	PUNCT
cana-2991	310	19	𝐹1	𝐹1	PROPN
cana-2991	310	20	−	−	PROPN
cana-2991	310	21	𝑠𝑐𝑜𝑟𝑒	𝑠𝑐𝑜𝑟𝑒	NOUN
cana-2991	310	22	=	=	SYM
cana-2991	310	23	2	2	NUM
cana-2991	310	24	×	×	NOUN
cana-2991	310	25	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	PROPN
cana-2991	310	26	×	×	NOUN
cana-2991	310	27	𝑅𝑒𝑐𝑎𝑙𝑙	𝑅𝑒𝑐𝑎𝑙𝑙	PROPN
cana-2991	310	28	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	PROPN
cana-2991	310	29	+	+	CCONJ
cana-2991	310	30	𝑅𝑒𝑐𝑎𝑙𝑙	𝑅𝑒𝑐𝑎𝑙𝑙	PROPN
cana-2991	310	31	experiments	experiment	NOUN
cana-2991	310	32	show	show	VERB
cana-2991	310	33	that	that	SCONJ
cana-2991	310	34	deep	deep	ADJ
cana-2991	310	35	learning	learning	NOUN
cana-2991	310	36	models	model	NOUN
cana-2991	310	37	,	,	PUNCT
cana-2991	310	38	in	in	ADP
cana-2991	310	39	particular	particular	ADJ
cana-2991	310	40	the	the	DET
cana-2991	310	41	bert	bert	PROPN
cana-2991	310	42	model	model	NOUN
cana-2991	310	43	performed	perform	VERB
cana-2991	310	44	significantly	significantly	ADV
cana-2991	310	45	better	well	ADJ
cana-2991	310	46	than	than	ADP
cana-2991	310	47	the	the	DET
cana-2991	310	48	traditional	traditional	ADJ
cana-2991	310	49	logistic	logistic	ADJ
cana-2991	310	50	regression	regression	NOUN
cana-2991	310	51	and	and	CCONJ
cana-2991	310	52	random	random	ADJ
cana-2991	310	53	forests	forest	NOUN
cana-2991	310	54	in	in	ADP
cana-2991	310	55	terms	term	NOUN
cana-2991	310	56	of	of	ADP
cana-2991	310	57	accuracy	accuracy	NOUN
cana-2991	310	58	and	and	CCONJ
cana-2991	310	59	recall	recall	NOUN
cana-2991	310	60	.	.	PUNCT
cana-2991	311	1	although	although	SCONJ
cana-2991	311	2	the	the	DET
cana-2991	311	3	most	most	ADV
cana-2991	311	4	accurate	accurate	ADJ
cana-2991	311	5	model	model	NOUN
cana-2991	311	6	was	be	AUX
cana-2991	311	7	that	that	PRON
cana-2991	311	8	of	of	ADP
cana-2991	311	9	bert	bert	PROPN
cana-2991	311	10	fine	fine	ADV
cana-2991	311	11	-	-	PUNCT
cana-2991	311	12	tuned	tune	VERB
cana-2991	311	13	on	on	ADP
cana-2991	311	14	liar	liar	NOUN
cana-2991	311	15	dataset	dataset	NOUN
cana-2991	311	16	with	with	ADP
cana-2991	311	17	89	89	NUM
cana-2991	311	18	%	%	NOUN
cana-2991	311	19	accuracy	accuracy	NOUN
cana-2991	311	20	,	,	PUNCT
cana-2991	311	21	87	87	NUM
cana-2991	311	22	%	%	NOUN
cana-2991	311	23	precision	precision	NOUN
cana-2991	311	24	and	and	CCONJ
cana-2991	311	25	90	90	NUM
cana-2991	311	26	%	%	NOUN
cana-2991	311	27	recall	recall	NOUN
cana-2991	311	28	.	.	PUNCT
cana-2991	312	1	this	this	PRON
cana-2991	312	2	indicates	indicate	VERB
cana-2991	312	3	that	that	SCONJ
cana-2991	312	4	the	the	DET
cana-2991	312	5	context	context	NOUN
cana-2991	312	6	-	-	PUNCT
cana-2991	312	7	aware	aware	ADJ
cana-2991	312	8	embeddings	embedding	NOUN
cana-2991	312	9	work	work	VERB
cana-2991	312	10	better	well	ADV
cana-2991	312	11	for	for	ADP
cana-2991	312	12	fake	fake	ADJ
cana-2991	312	13	news	news	NOUN
cana-2991	312	14	detection	detection	NOUN
cana-2991	312	15	.	.	PUNCT
cana-2991	313	1	the	the	DET
cana-2991	313	2	proposed	propose	VERB
cana-2991	313	3	method	method	NOUN
cana-2991	313	4	for	for	ADP
cana-2991	313	5	scalable	scalable	ADJ
cana-2991	313	6	fake	fake	ADJ
cana-2991	313	7	news	news	NOUN
cana-2991	313	8	detection	detection	NOUN
cana-2991	313	9	is	be	AUX
cana-2991	313	10	to	to	PART
cana-2991	313	11	build	build	VERB
cana-2991	313	12	a	a	DET
cana-2991	313	13	strong	strong	ADJ
cana-2991	313	14	and	and	CCONJ
cana-2991	313	15	powerful	powerful	ADJ
cana-2991	313	16	system	system	NOUN
cana-2991	313	17	using	use	VERB
cana-2991	313	18	advanced	advanced	ADJ
cana-2991	313	19	nlp	nlp	ADJ
cana-2991	313	20	tools	tool	NOUN
cana-2991	313	21	&	&	CCONJ
cana-2991	313	22	machine	machine	NOUN
cana-2991	313	23	learning	learn	VERB
cana-2991	313	24	classifiers	classifier	NOUN
cana-2991	313	25	,	,	PUNCT
cana-2991	313	26	which	which	PRON
cana-2991	313	27	can	can	AUX
cana-2991	313	28	process	process	VERB
cana-2991	313	29	large	large	ADJ
cana-2991	313	30	scale	scale	NOUN
cana-2991	313	31	datasets	dataset	NOUN
cana-2991	313	32	.	.	PUNCT
cana-2991	314	1	it	it	PRON
cana-2991	314	2	offers	offer	VERB
cana-2991	314	3	scalability	scalability	NOUN
cana-2991	314	4	and	and	CCONJ
cana-2991	314	5	real	real	ADJ
cana-2991	314	6	-	-	PUNCT
cana-2991	314	7	time	time	NOUN
cana-2991	314	8	processing	processing	NOUN
cana-2991	314	9	by	by	ADP
cana-2991	314	10	using	use	VERB
cana-2991	314	11	distributed	distribute	VERB
cana-2991	314	12	processing	processing	NOUN
cana-2991	314	13	frameworks	framework	NOUN
cana-2991	314	14	,	,	PUNCT
cana-2991	314	15	making	make	VERB
cana-2991	314	16	it	it	PRON
cana-2991	314	17	an	an	DET
cana-2991	314	18	ideal	ideal	ADJ
cana-2991	314	19	solution	solution	NOUN
cana-2991	314	20	for	for	ADP
cana-2991	314	21	social	social	ADJ
cana-2991	314	22	media	medium	NOUN
cana-2991	314	23	platforms	platform	NOUN
cana-2991	314	24	with	with	ADP
cana-2991	314	25	high	high	ADJ
cana-2991	314	26	-	-	PUNCT
cana-2991	314	27	throughput	throughput	NOUN
cana-2991	314	28	requirements	requirement	NOUN
cana-2991	314	29	.	.	PUNCT
cana-2991	315	1	this	this	DET
cana-2991	315	2	acts	act	VERB
cana-2991	315	3	as	as	ADP
cana-2991	315	4	a	a	DET
cana-2991	315	5	very	very	ADV
cana-2991	315	6	strong	strong	ADJ
cana-2991	315	7	tool	tool	NOUN
cana-2991	315	8	to	to	PART
cana-2991	315	9	stand	stand	VERB
cana-2991	315	10	against	against	ADP
cana-2991	315	11	the	the	DET
cana-2991	315	12	increase	increase	NOUN
cana-2991	315	13	in	in	ADP
cana-2991	315	14	informational	informational	ADJ
cana-2991	315	15	war	war	NOUN
cana-2991	315	16	with	with	ADP
cana-2991	315	17	the	the	DET
cana-2991	315	18	use	use	NOUN
cana-2991	315	19	of	of	ADP
cana-2991	315	20	different	different	ADJ
cana-2991	315	21	prepossessing	prepossessing	NOUN
cana-2991	315	22	of	of	ADP
cana-2991	315	23	data	datum	NOUN
cana-2991	315	24	along	along	ADP
cana-2991	315	25	with	with	ADP
cana-2991	315	26	advanced	advanced	ADJ
cana-2991	315	27	models	model	NOUN
cana-2991	315	28	using	use	VERB
cana-2991	315	29	natural	natural	ADJ
cana-2991	315	30	language	language	NOUN
cana-2991	315	31	processing	processing	NOUN
cana-2991	315	32	and	and	CCONJ
cana-2991	315	33	machine	machine	NOUN
cana-2991	315	34	learning	learning	NOUN
cana-2991	315	35	.	.	PUNCT
cana-2991	316	1	4	4	X
cana-2991	316	2	.	.	NOUN
cana-2991	316	3	results	result	NOUN
cana-2991	316	4	and	and	CCONJ
cana-2991	316	5	experiment	experiment	NOUN
cana-2991	316	6	this	this	DET
cana-2991	316	7	section	section	NOUN
cana-2991	316	8	describes	describe	VERB
cana-2991	316	9	the	the	DET
cana-2991	316	10	experimental	experimental	ADJ
cana-2991	316	11	setup	setup	NOUN
cana-2991	316	12	,	,	PUNCT
cana-2991	316	13	results	result	NOUN
cana-2991	316	14	and	and	CCONJ
cana-2991	316	15	performance	performance	NOUN
cana-2991	316	16	analysis	analysis	NOUN
cana-2991	316	17	of	of	ADP
cana-2991	316	18	the	the	DET
cana-2991	316	19	proposed	propose	VERB
cana-2991	316	20	false	false	ADJ
cana-2991	316	21	information	information	NOUN
cana-2991	316	22	detection	detection	NOUN
cana-2991	316	23	fake	fake	ADJ
cana-2991	316	24	news	news	NOUN
cana-2991	316	25	detection	detection	NOUN
cana-2991	316	26	model	model	NOUN
cana-2991	316	27	using	use	VERB
cana-2991	316	28	various	various	ADJ
cana-2991	316	29	word	word	NOUN
cana-2991	316	30	embeddings	embedding	NOUN
cana-2991	316	31	to	to	PART
cana-2991	316	32	perform	perform	VERB
cana-2991	316	33	experiments	experiment	NOUN
cana-2991	316	34	with	with	ADP
cana-2991	316	35	different	different	ADJ
cana-2991	316	36	machine	machine	NOUN
cana-2991	316	37	learning	learn	VERB
cana-2991	316	38	classifiers	classifier	NOUN
cana-2991	316	39	we	we	PRON
cana-2991	316	40	conduct	conduct	VERB
cana-2991	316	41	experiments	experiment	NOUN
cana-2991	316	42	on	on	ADP
cana-2991	316	43	two	two	NUM
cana-2991	316	44	popular	popular	ADJ
cana-2991	316	45	fake	fake	ADJ
cana-2991	316	46	news	news	NOUN
cana-2991	316	47	datasets	dataset	NOUN
cana-2991	316	48	,	,	PUNCT
cana-2991	316	49	politifact	politifact	PROPN
cana-2991	316	50	and	and	CCONJ
cana-2991	316	51	liar	liar	NOUN
cana-2991	316	52	.	.	PUNCT
cana-2991	317	1	we	we	PRON
cana-2991	317	2	compared	compare	VERB
cana-2991	317	3	different	different	ADJ
cana-2991	317	4	word	word	NOUN
cana-2991	317	5	embedding	embed	VERB
cana-2991	317	6	techniques	technique	NOUN
cana-2991	317	7	against	against	ADP
cana-2991	317	8	a	a	DET
cana-2991	317	9	few	few	ADJ
cana-2991	317	10	machine	machine	NOUN
cana-2991	317	11	learning	learning	NOUN
cana-2991	317	12	models	model	NOUN
cana-2991	317	13	like	like	ADP
cana-2991	317	14	bag	bag	NOUN
cana-2991	317	15	of	of	ADP
cana-2991	317	16	words	word	NOUN
cana-2991	317	17	,	,	PUNCT
cana-2991	317	18	term	term	NOUN
cana-2991	317	19	frequency	frequency	NOUN
cana-2991	317	20	-	-	PUNCT
cana-2991	317	21	inverse	inverse	NOUN
cana-2991	317	22	-	-	PUNCT
cana-2991	317	23	document	document	NOUN
cana-2991	317	24	-	-	PUNCT
cana-2991	317	25	frequency	frequency	NOUN
cana-2991	317	26	,	,	PUNCT
cana-2991	317	27	word2vec	word2vec	X
cana-2991	317	28	,	,	PUNCT
cana-2991	317	29	and	and	CCONJ
cana-2991	317	30	bidirectional	bidirectional	ADJ
cana-2991	317	31	encoder	encoder	NOUN
cana-2991	317	32	representations	representation	VERB
cana-2991	317	33	from	from	ADP
cana-2991	317	34	transformers	transformer	NOUN
cana-2991	317	35	(	(	PUNCT
cana-2991	317	36	bert	bert	PROPN
cana-2991	317	37	)	)	PUNCT
cana-2991	317	38	.	.	PUNCT
cana-2991	318	1	we	we	PRON
cana-2991	318	2	then	then	ADV
cana-2991	318	3	conducted	conduct	VERB
cana-2991	318	4	conventional	conventional	ADJ
cana-2991	318	5	evaluation	evaluation	NOUN
cana-2991	318	6	based	base	VERB
cana-2991	318	7	on	on	ADP
cana-2991	318	8	accuracy	accuracy	NOUN
cana-2991	318	9	,	,	PUNCT
cana-2991	318	10	precision	precision	NOUN
cana-2991	318	11	,	,	PUNCT
cana-2991	318	12	recall	recall	NOUN
cana-2991	318	13	and	and	CCONJ
cana-2991	318	14	f1	f1	ADJ
cana-2991	318	15	-	-	PUNCT
cana-2991	318	16	score	score	NOUN
cana-2991	318	17	metrics	metric	NOUN
cana-2991	318	18	for	for	ADP
cana-2991	318	19	each	each	PRON
cana-2991	318	20	of	of	ADP
cana-2991	318	21	the	the	DET
cana-2991	318	22	models	model	NOUN
cana-2991	318	23	.	.	PUNCT
cana-2991	319	1	communications	communication	NOUN
cana-2991	319	2	on	on	ADP
cana-2991	319	3	applied	apply	VERB
cana-2991	319	4	nonlinear	nonlinear	ADJ
cana-2991	319	5	analysis	analysis	NOUN
cana-2991	319	6	issn	issn	NOUN
cana-2991	319	7	:	:	PUNCT
cana-2991	319	8	1074	1074	NUM
cana-2991	319	9	-	-	PUNCT
cana-2991	319	10	133x	133x	NUM
cana-2991	319	11	vol	vol	NOUN
cana-2991	319	12	32	32	NUM
cana-2991	319	13	no	no	NOUN
cana-2991	319	14	.	.	PUNCT
cana-2991	320	1	5s	5s	NUM
cana-2991	320	2	(	(	PUNCT
cana-2991	320	3	2025	2025	NUM
cana-2991	320	4	)	)	PUNCT
cana-2991	320	5	167	167	NUM
cana-2991	320	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	320	7	the	the	DET
cana-2991	320	8	experiments	experiment	NOUN
cana-2991	320	9	were	be	AUX
cana-2991	320	10	designed	design	VERB
cana-2991	320	11	to	to	PART
cana-2991	320	12	evaluate	evaluate	VERB
cana-2991	320	13	the	the	DET
cana-2991	320	14	performance	performance	NOUN
cana-2991	320	15	of	of	ADP
cana-2991	320	16	conventional	conventional	ADJ
cana-2991	320	17	models	model	NOUN
cana-2991	320	18	and	and	CCONJ
cana-2991	320	19	deep	deep	ADJ
cana-2991	320	20	learning	learning	NOUN
cana-2991	320	21	models	model	NOUN
cana-2991	320	22	along	along	ADV
cana-2991	320	23	with	with	ADP
cana-2991	320	24	different	different	ADJ
cana-2991	320	25	set	set	NOUN
cana-2991	320	26	embedding	embed	VERB
cana-2991	320	27	methods	method	NOUN
cana-2991	320	28	,	,	PUNCT
cana-2991	320	29	so	so	SCONJ
cana-2991	320	30	as	as	SCONJ
cana-2991	320	31	to	to	PART
cana-2991	320	32	fit	fit	VERB
cana-2991	320	33	a	a	DET
cana-2991	320	34	scalable	scalable	ADJ
cana-2991	320	35	fake	fake	ADJ
cana-2991	320	36	news	news	NOUN
cana-2991	320	37	detection	detection	NOUN
cana-2991	320	38	approach	approach	NOUN
cana-2991	320	39	.	.	PUNCT
cana-2991	321	1	we	we	PRON
cana-2991	321	2	also	also	ADV
cana-2991	321	3	sized	size	VERB
cana-2991	321	4	the	the	DET
cana-2991	321	5	system	system	NOUN
cana-2991	321	6	to	to	PART
cana-2991	321	7	see	see	VERB
cana-2991	321	8	if	if	SCONJ
cana-2991	321	9	it	it	PRON
cana-2991	321	10	could	could	AUX
cana-2991	321	11	scale	scale	VERB
cana-2991	321	12	with	with	ADP
cana-2991	321	13	heterogeneously	heterogeneously	ADV
cana-2991	321	14	saturated	saturate	VERB
cana-2991	321	15	grids	grid	NOUN
cana-2991	321	16	data	datum	NOUN
cana-2991	321	17	at	at	ADP
cana-2991	321	18	larger	large	ADJ
cana-2991	321	19	scales	scale	NOUN
cana-2991	321	20	by	by	ADP
cana-2991	321	21	distributing	distribute	VERB
cana-2991	321	22	processing	processing	NOUN
cana-2991	321	23	frameworks	framework	NOUN
cana-2991	321	24	,	,	PUNCT
cana-2991	321	25	like	like	ADP
cana-2991	321	26	apache	apache	NOUN
cana-2991	321	27	spark	spark	NOUN
cana-2991	321	28	.	.	PUNCT
cana-2991	322	1	1	1	X
cana-2991	322	2	.	.	X
cana-2991	322	3	experimental	experimental	ADJ
cana-2991	322	4	setup	setup	NOUN
cana-2991	322	5	1.1	1.1	NUM
cana-2991	322	6	datasets	dataset	NOUN
cana-2991	322	7	for	for	ADP
cana-2991	322	8	the	the	DET
cana-2991	322	9	experiments	experiment	NOUN
cana-2991	322	10	performed	perform	VERB
cana-2991	322	11	,	,	PUNCT
cana-2991	322	12	begin	begin	VERB
cana-2991	322	13	by	by	ADP
cana-2991	322	14	downloading	download	VERB
cana-2991	322	15	two	two	NUM
cana-2991	322	16	respective	respective	ADJ
cana-2991	322	17	publicly	publicly	ADV
cana-2991	322	18	available	available	ADJ
cana-2991	322	19	datasets	dataset	NOUN
cana-2991	322	20	.	.	PUNCT
cana-2991	323	1	1	1	X
cana-2991	323	2	.	.	X
cana-2991	323	3	politifact	politifact	PROPN
cana-2991	323	4	datasetit	datasetit	PROPN
cana-2991	323	5	is	be	AUX
cana-2991	323	6	a	a	DET
cana-2991	323	7	dataset	dataset	NOUN
cana-2991	323	8	that	that	PRON
cana-2991	323	9	consists	consist	VERB
cana-2991	323	10	of	of	ADP
cana-2991	323	11	political	political	ADJ
cana-2991	323	12	-	-	PUNCT
cana-2991	323	13	news	news	NOUN
cana-2991	323	14	labeled	label	VERB
cana-2991	323	15	as	as	ADP
cana-2991	323	16	real	real	ADJ
cana-2991	323	17	or	or	CCONJ
cana-2991	323	18	fake	fake	ADJ
cana-2991	323	19	.	.	PUNCT
cana-2991	324	1	it	it	PRON
cana-2991	324	2	is	be	AUX
cana-2991	324	3	a	a	DET
cana-2991	324	4	popular	popular	ADJ
cana-2991	324	5	dataset	dataset	NOUN
cana-2991	324	6	used	use	VERB
cana-2991	324	7	in	in	ADP
cana-2991	324	8	fake	fake	ADJ
cana-2991	324	9	news	news	NOUN
cana-2991	324	10	detection	detection	NOUN
cana-2991	324	11	research	research	NOUN
cana-2991	324	12	and	and	CCONJ
cana-2991	324	13	suitable	suitable	ADJ
cana-2991	324	14	for	for	ADP
cana-2991	324	15	binary	binary	ADJ
cana-2991	324	16	classification	classification	NOUN
cana-2991	324	17	tasks	task	NOUN
cana-2991	324	18	.	.	PUNCT
cana-2991	325	1	2	2	X
cana-2991	325	2	.	.	X
cana-2991	325	3	liar	liar	NOUN
cana-2991	325	4	dataset	dataset	PROPN
cana-2991	325	5	:	:	PUNCT
cana-2991	325	6	the	the	DET
cana-2991	325	7	liar	liar	NOUN
cana-2991	325	8	dataset	dataset	NOUN
cana-2991	325	9	is	be	AUX
cana-2991	325	10	a	a	DET
cana-2991	325	11	collection	collection	NOUN
cana-2991	325	12	of	of	ADP
cana-2991	325	13	news	news	NOUN
cana-2991	325	14	statements	statement	NOUN
cana-2991	325	15	from	from	ADP
cana-2991	325	16	the	the	DET
cana-2991	325	17	political	political	ADJ
cana-2991	325	18	domain	domain	NOUN
cana-2991	325	19	with	with	ADP
cana-2991	325	20	labels	label	NOUN
cana-2991	325	21	in	in	ADP
cana-2991	325	22	the	the	DET
cana-2991	325	23	form	form	NOUN
cana-2991	325	24	of	of	ADP
cana-2991	325	25	“	"	PUNCT
cana-2991	325	26	true	true	ADJ
cana-2991	325	27	”	"	PUNCT
cana-2991	325	28	,	,	PUNCT
cana-2991	325	29	“	"	PUNCT
cana-2991	325	30	mostly	mostly	ADV
cana-2991	325	31	true	true	ADJ
cana-2991	325	32	”	"	PUNCT
cana-2991	325	33	,	,	PUNCT
cana-2991	325	34	”	"	PUNCT
cana-2991	325	35	half	half	NOUN
cana-2991	325	36	true	true	ADJ
cana-2991	325	37	”	"	PUNCT
cana-2991	325	38	,	,	PUNCT
cana-2991	325	39	full	full	ADJ
cana-2991	325	40	false	false	ADJ
cana-2991	325	41	,	,	PUNCT
cana-2991	325	42	”	"	PUNCT
cana-2991	325	43	barely	barely	ADV
cana-2991	325	44	true	true	ADJ
cana-2991	325	45	”	"	PUNCT
cana-2991	325	46	and	and	CCONJ
cana-2991	325	47	half	half	ADV
cana-2991	325	48	flip	flip	NOUN
cana-2991	325	49	.	.	PUNCT
cana-2991	326	1	in	in	ADP
cana-2991	326	2	turn	turn	NOUN
cana-2991	326	3	,	,	PUNCT
cana-2991	326	4	we	we	PRON
cana-2991	326	5	simplified	simplify	VERB
cana-2991	326	6	the	the	DET
cana-2991	326	7	labels	label	NOUN
cana-2991	326	8	as	as	ADP
cana-2991	326	9	true	true	ADJ
cana-2991	326	10	(	(	PUNCT
cana-2991	326	11	true	true	ADJ
cana-2991	326	12	,	,	PUNCT
cana-2991	326	13	mostly	mostly	ADV
cana-2991	326	14	true	true	ADJ
cana-2991	326	15	&	&	CCONJ
cana-2991	326	16	half	half	NOUN
cana-2991	326	17	true	true	ADJ
cana-2991	326	18	)	)	PUNCT
cana-2991	326	19	and	and	CCONJ
cana-2991	326	20	fake	fake	ADJ
cana-2991	326	21	(	(	PUNCT
cana-2991	326	22	barely	barely	ADV
cana-2991	326	23	true	true	ADJ
cana-2991	326	24	,	,	PUNCT
cana-2991	326	25	false	false	ADJ
cana-2991	326	26	&	&	CCONJ
cana-2991	326	27	pants	pant	NOUN
cana-2991	326	28	on	on	ADP
cana-2991	326	29	fire	fire	NOUN
cana-2991	326	30	)	)	PUNCT
cana-2991	326	31	for	for	ADP
cana-2991	326	32	homogeneity	homogeneity	NOUN
cana-2991	326	33	and	and	CCONJ
cana-2991	326	34	to	to	PART
cana-2991	326	35	maintain	maintain	VERB
cana-2991	326	36	with	with	ADP
cana-2991	326	37	that	that	PRON
cana-2991	326	38	of	of	ADP
cana-2991	326	39	the	the	DET
cana-2991	326	40	parallel	parallel	ADJ
cana-2991	326	41	dataset	dataset	NOUN
cana-2991	326	42	.	.	PUNCT
cana-2991	327	1	dataset	dataset	ADJ
cana-2991	327	2	#	#	NOUN
cana-2991	327	3	of	of	ADP
cana-2991	327	4	news	news	NOUN
cana-2991	327	5	articles	article	NOUN
cana-2991	327	6	#	#	NOUN
cana-2991	327	7	of	of	ADP
cana-2991	327	8	true	true	ADJ
cana-2991	327	9	articles	article	NOUN
cana-2991	327	10	#	#	NOUN
cana-2991	327	11	of	of	ADP
cana-2991	327	12	fake	fake	ADJ
cana-2991	327	13	articles	article	NOUN
cana-2991	327	14	time	time	NOUN
cana-2991	327	15	span	span	PROPN
cana-2991	327	16	politifact	politifact	PROPN
cana-2991	327	17	12,000	12,000	NUM
cana-2991	327	18	6,100	6,100	NUM
cana-2991	327	19	5,900	5,900	NUM
cana-2991	327	20	2007–2020	2007–2020	NUM
cana-2991	327	21	liar	liar	NOUN
cana-2991	327	22	13,000	13,000	NUM
cana-2991	327	23	7,500	7,500	NUM
cana-2991	327	24	5,500	5,500	NUM
cana-2991	327	25	2007–2019	2007–2019	NUM
cana-2991	327	26	table	table	NOUN
cana-2991	327	27	1	1	NUM
cana-2991	327	28	:	:	PUNCT
cana-2991	327	29	summary	summary	NOUN
cana-2991	327	30	statistics	statistic	NOUN
cana-2991	327	31	of	of	ADP
cana-2991	327	32	the	the	DET
cana-2991	327	33	datasets	dataset	NOUN
cana-2991	327	34	used	use	VERB
cana-2991	327	35	in	in	ADP
cana-2991	327	36	experiments	experiment	NOUN
cana-2991	327	37	1.2	1.2	NUM
cana-2991	327	38	preprocessing	preprocesse	VERB
cana-2991	327	39	raw	raw	ADJ
cana-2991	327	40	news	news	NOUN
cana-2991	327	41	articles	article	NOUN
cana-2991	327	42	were	be	AUX
cana-2991	327	43	processed	process	VERB
cana-2991	327	44	as	as	SCONJ
cana-2991	327	45	stated	state	VERB
cana-2991	327	46	above	above	ADP
cana-2991	327	47	following	follow	VERB
cana-2991	327	48	the	the	DET
cana-2991	327	49	methodology	methodology	NOUN
cana-2991	327	50	before	before	SCONJ
cana-2991	327	51	they	they	PRON
cana-2991	327	52	were	be	AUX
cana-2991	327	53	fed	feed	VERB
cana-2991	327	54	into	into	ADP
cana-2991	327	55	machine	machine	NOUN
cana-2991	327	56	learning	learning	NOUN
cana-2991	327	57	models	model	NOUN
cana-2991	327	58	.	.	PUNCT
cana-2991	328	1	you	you	PRON
cana-2991	328	2	can	can	AUX
cana-2991	328	3	perform	perform	VERB
cana-2991	328	4	steps	step	NOUN
cana-2991	328	5	like	like	ADP
cana-2991	328	6	tokenization	tokenization	NOUN
cana-2991	328	7	,	,	PUNCT
cana-2991	328	8	cleansing	cleanse	VERB
cana-2991	328	9	the	the	DET
cana-2991	328	10	stop	stop	NOUN
cana-2991	328	11	words	word	NOUN
cana-2991	328	12	,	,	PUNCT
cana-2991	328	13	lemmatization	lemmatization	NOUN
cana-2991	328	14	and	and	CCONJ
cana-2991	328	15	convert	convert	VERB
cana-2991	328	16	the	the	DET
cana-2991	328	17	text	text	NOUN
cana-2991	328	18	using	use	VERB
cana-2991	328	19	the	the	DET
cana-2991	328	20	embedding	embed	VERB
cana-2991	328	21	techniques	technique	NOUN
cana-2991	328	22	that	that	PRON
cana-2991	328	23	you	you	PRON
cana-2991	328	24	choose	choose	VERB
cana-2991	328	25	to	to	ADP
cana-2991	328	26	numerical	numerical	ADJ
cana-2991	328	27	representation	representation	NOUN
cana-2991	328	28	.	.	PUNCT
cana-2991	329	1	during	during	ADP
cana-2991	329	2	this	this	DET
cana-2991	329	3	experiment	experiment	NOUN
cana-2991	329	4	,	,	PUNCT
cana-2991	329	5	embeddings	embedding	NOUN
cana-2991	329	6	that	that	PRON
cana-2991	329	7	were	be	AUX
cana-2991	329	8	using	use	VERB
cana-2991	329	9	were	be	AUX
cana-2991	329	10	the	the	DET
cana-2991	329	11	following	following	NOUN
cana-2991	329	12	:	:	PUNCT
cana-2991	329	13	1	1	X
cana-2991	329	14	.	.	X
cana-2991	329	15	bow	bow	NOUN
cana-2991	329	16	(	(	PUNCT
cana-2991	329	17	bag	bag	NOUN
cana-2991	329	18	of	of	ADP
cana-2991	329	19	words	word	NOUN
cana-2991	329	20	):	):	PUNCT
cana-2991	329	21	a	a	DET
cana-2991	329	22	simple	simple	ADJ
cana-2991	329	23	frequency	frequency	NOUN
cana-2991	329	24	based	base	VERB
cana-2991	329	25	approach	approach	NOUN
cana-2991	329	26	.	.	PUNCT
cana-2991	330	1	2	2	X
cana-2991	330	2	.	.	X
cana-2991	330	3	tf	tf	PROPN
cana-2991	330	4	-	-	PUNCT
cana-2991	330	5	idf	idf	PROPN
cana-2991	330	6	:	:	PUNCT
cana-2991	330	7	the	the	DET
cana-2991	330	8	importance	importance	NOUN
cana-2991	330	9	of	of	ADP
cana-2991	330	10	vocabularies	vocabulary	NOUN
cana-2991	330	11	in	in	ADP
cana-2991	330	12	the	the	DET
cana-2991	330	13	whole	whole	ADJ
cana-2991	330	14	corpus	corpus	NOUN
cana-2991	330	15	is	be	AUX
cana-2991	330	16	weighed	weigh	VERB
cana-2991	330	17	and	and	CCONJ
cana-2991	330	18	measured	measure	VERB
cana-2991	330	19	.	.	PUNCT
cana-2991	331	1	3	3	X
cana-2991	331	2	.	.	X
cana-2991	331	3	word2vec	word2vec	X
cana-2991	331	4	(	(	PUNCT
cana-2991	331	5	variants	variant	NOUN
cana-2991	331	6	:	:	PUNCT
cana-2991	331	7	continuous	continuous	ADJ
cana-2991	331	8	bag	bag	NOUN
cana-2991	331	9	of	of	ADP
cana-2991	331	10	words	word	NOUN
cana-2991	331	11	(	(	PUNCT
cana-2991	331	12	cbow	cbow	VERB
cana-2991	331	13	)	)	PUNCT
cana-2991	331	14	and	and	CCONJ
cana-2991	331	15	skip	skip	VERB
cana-2991	331	16	-	-	PUNCT
cana-2991	331	17	gram	gram	NOUN
cana-2991	331	18	versions	version	NOUN
cana-2991	331	19	were	be	AUX
cana-2991	331	20	employed	employ	VERB
cana-2991	331	21	.	.	PUNCT
cana-2991	331	22	)	)	PUNCT
cana-2991	332	1	4	4	X
cana-2991	332	2	.	.	X
cana-2991	333	1	bert	bert	PROPN
cana-2991	333	2	:	:	PUNCT
cana-2991	333	3	contextual	contextual	ADJ
cana-2991	333	4	embedding	embed	VERB
cana-2991	333	5	learning	learning	NOUN
cana-2991	333	6	based	base	VERB
cana-2991	333	7	on	on	ADP
cana-2991	333	8	deep	deep	ADJ
cana-2991	333	9	learning	learning	NOUN
cana-2991	333	10	,	,	PUNCT
cana-2991	333	11	capturing	capture	VERB
cana-2991	333	12	word	word	NOUN
cana-2991	333	13	semantics	semantic	NOUN
cana-2991	333	14	.	.	PUNCT
cana-2991	334	1	1.3	1.3	NUM
cana-2991	334	2	classifiers	classifier	NOUN
cana-2991	334	3	classifiers	classifier	NOUN
cana-2991	334	4	.	.	PUNCT
cana-2991	335	1	we	we	PRON
cana-2991	335	2	used	use	VERB
cana-2991	335	3	the	the	DET
cana-2991	335	4	following	follow	VERB
cana-2991	335	5	classifiers	classifier	NOUN
cana-2991	335	6	:	:	PUNCT
cana-2991	335	7	logistic	logistic	ADJ
cana-2991	335	8	regression	regression	NOUN
cana-2991	335	9	(	(	PUNCT
cana-2991	335	10	lr	lr	NOUN
cana-2991	335	11	):	):	PUNCT
cana-2991	335	12	an	an	DET
cana-2991	335	13	algorithm	algorithm	NOUN
cana-2991	335	14	for	for	ADP
cana-2991	335	15	binary	binary	ADJ
cana-2991	335	16	classification	classification	NOUN
cana-2991	335	17	tasks	task	NOUN
cana-2991	335	18	.	.	PUNCT
cana-2991	336	1	random	random	ADJ
cana-2991	336	2	forest	forest	NOUN
cana-2991	336	3	(	(	PUNCT
cana-2991	336	4	rf	rf	NOUN
cana-2991	336	5	)	)	PUNCT
cana-2991	336	6	:	:	PUNCT
cana-2991	336	7	an	an	DET
cana-2991	336	8	ensemble	ensemble	ADJ
cana-2991	336	9	method	method	NOUN
cana-2991	336	10	that	that	PRON
cana-2991	336	11	builds	build	VERB
cana-2991	336	12	multiple	multiple	ADJ
cana-2991	336	13	decision	decision	NOUN
cana-2991	336	14	trees	tree	NOUN
cana-2991	336	15	.	.	PUNCT
cana-2991	337	1	neural	neural	ADJ
cana-2991	337	2	networks	network	NOUN
cana-2991	337	3	(	(	PUNCT
cana-2991	337	4	nn	nn	X
cana-2991	337	5	):	):	PUNCT
cana-2991	337	6	a	a	DET
cana-2991	337	7	type	type	NOUN
cana-2991	337	8	of	of	ADP
cana-2991	337	9	deep	deep	ADJ
cana-2991	337	10	learning	learning	NOUN
cana-2991	337	11	model	model	NOUN
cana-2991	337	12	based	base	VERB
cana-2991	337	13	on	on	ADP
cana-2991	337	14	fully	fully	ADV
cana-2991	337	15	connected	connected	ADJ
cana-2991	337	16	layers	layer	NOUN
cana-2991	337	17	.	.	PUNCT
cana-2991	338	1	support	support	NOUN
cana-2991	338	2	vector	vector	NOUN
cana-2991	338	3	machine	machine	NOUN
cana-2991	338	4	(	(	PUNCT
cana-2991	338	5	svm	svm	PROPN
cana-2991	338	6	):	):	PUNCT
cana-2991	338	7	a	a	DET
cana-2991	338	8	model	model	NOUN
cana-2991	338	9	that	that	PRON
cana-2991	338	10	separate	separate	ADJ
cana-2991	338	11	classes	class	NOUN
cana-2991	338	12	into	into	ADP
cana-2991	338	13	two	two	NUM
cana-2991	338	14	hyperplanes	hyperplane	NOUN
cana-2991	338	15	in	in	ADP
cana-2991	338	16	a	a	DET
cana-2991	338	17	highdimensional	highdimensional	ADJ
cana-2991	338	18	space	space	NOUN
cana-2991	338	19	.	.	PUNCT
cana-2991	339	1	communications	communication	NOUN
cana-2991	339	2	on	on	ADP
cana-2991	339	3	applied	apply	VERB
cana-2991	339	4	nonlinear	nonlinear	ADJ
cana-2991	339	5	analysis	analysis	NOUN
cana-2991	339	6	issn	issn	NOUN
cana-2991	339	7	:	:	PUNCT
cana-2991	339	8	1074	1074	NUM
cana-2991	339	9	-	-	PUNCT
cana-2991	339	10	133x	133x	NUM
cana-2991	339	11	vol	vol	NOUN
cana-2991	339	12	32	32	NUM
cana-2991	339	13	no	no	NOUN
cana-2991	339	14	.	.	PUNCT
cana-2991	340	1	5s	5s	NUM
cana-2991	340	2	(	(	PUNCT
cana-2991	340	3	2025	2025	NUM
cana-2991	340	4	)	)	PUNCT
cana-2991	340	5	168	168	NUM
cana-2991	340	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	340	7	all	all	DET
cana-2991	340	8	the	the	DET
cana-2991	340	9	models	model	NOUN
cana-2991	340	10	were	be	AUX
cana-2991	340	11	trained	train	VERB
cana-2991	340	12	using	use	VERB
cana-2991	340	13	embedded	embed	VERB
cana-2991	340	14	data	datum	NOUN
cana-2991	340	15	from	from	ADP
cana-2991	340	16	various	various	ADJ
cana-2991	340	17	word	word	NOUN
cana-2991	340	18	embedding	embed	VERB
cana-2991	340	19	techniques	technique	NOUN
cana-2991	340	20	.	.	PUNCT
cana-2991	341	1	in	in	ADP
cana-2991	341	2	all	all	DET
cana-2991	341	3	experiments	experiment	NOUN
cana-2991	341	4	80	80	NUM
cana-2991	341	5	%	%	NOUN
cana-2991	341	6	of	of	ADP
cana-2991	341	7	the	the	DET
cana-2991	341	8	data	datum	NOUN
cana-2991	341	9	were	be	AUX
cana-2991	341	10	used	use	VERB
cana-2991	341	11	for	for	ADP
cana-2991	341	12	training	training	NOUN
cana-2991	341	13	,	,	PUNCT
cana-2991	341	14	and	and	CCONJ
cana-2991	341	15	20	20	NUM
cana-2991	341	16	%	%	NOUN
cana-2991	341	17	for	for	ADP
cana-2991	341	18	testing	testing	NOUN
cana-2991	341	19	.	.	PUNCT
cana-2991	342	1	all	all	DET
cana-2991	342	2	models	model	NOUN
cana-2991	342	3	were	be	AUX
cana-2991	342	4	internally	internally	ADV
cana-2991	342	5	validated	validate	VERB
cana-2991	342	6	using	use	VERB
cana-2991	342	7	10	10	NUM
cana-2991	342	8	-	-	ADJ
cana-2991	342	9	fold	fold	ADJ
cana-2991	342	10	cross	cross	NOUN
cana-2991	342	11	validation	validation	NOUN
cana-2991	342	12	to	to	PART
cana-2991	342	13	control	control	VERB
cana-2991	342	14	for	for	ADP
cana-2991	342	15	overfitting	overfitte	VERB
cana-2991	342	16	.	.	PUNCT
cana-2991	343	1	1.4	1.4	NUM
cana-2991	343	2	evaluation	evaluation	NOUN
cana-2991	343	3	metrics	metric	NOUN
cana-2991	343	4	using	use	VERB
cana-2991	343	5	figure	figure	NOUN
cana-2991	343	6	4	4	NUM
cana-2991	343	7	,	,	PUNCT
cana-2991	343	8	it	it	PRON
cana-2991	343	9	represents	represent	VERB
cana-2991	343	10	that	that	SCONJ
cana-2991	343	11	bert	bert	PROPN
cana-2991	343	12	model	model	NOUN
cana-2991	343	13	have	have	VERB
cana-2991	343	14	highest	high	ADJ
cana-2991	343	15	performance	performance	NOUN
cana-2991	343	16	among	among	ADP
cana-2991	343	17	bow	bow	NOUN
cana-2991	343	18	,	,	PUNCT
cana-2991	343	19	tf	tf	PROPN
cana-2991	343	20	-	-	PUNCT
cana-2991	343	21	idf	idf	PROPN
cana-2991	343	22	and	and	CCONJ
cana-2991	343	23	word2vec.we	word2vec.we	NOUN
cana-2991	343	24	used	use	VERB
cana-2991	343	25	the	the	DET
cana-2991	343	26	following	follow	VERB
cana-2991	343	27	four	four	NUM
cana-2991	343	28	metrics	metric	NOUN
cana-2991	343	29	to	to	PART
cana-2991	343	30	evaluate	evaluate	VERB
cana-2991	343	31	the	the	DET
cana-2991	343	32	accuracy	accuracy	NOUN
cana-2991	343	33	of	of	ADP
cana-2991	343	34	our	our	PRON
cana-2991	343	35	models	model	NOUN
cana-2991	343	36	:	:	PUNCT
cana-2991	343	37	accuracy	accuracy	NOUN
cana-2991	343	38	:	:	PUNCT
cana-2991	343	39	the	the	DET
cana-2991	343	40	percentage	percentage	NOUN
cana-2991	343	41	of	of	ADP
cana-2991	343	42	news	news	NOUN
cana-2991	343	43	articles	article	NOUN
cana-2991	343	44	that	that	PRON
cana-2991	343	45	were	be	AUX
cana-2991	343	46	predicted	predict	VERB
cana-2991	343	47	correctly	correctly	ADV
cana-2991	343	48	•	•	NUM
cana-2991	343	49	precision	precision	NOUN
cana-2991	343	50	:	:	PUNCT
cana-2991	343	51	the	the	DET
cana-2991	343	52	model	model	NOUN
cana-2991	343	53	's	's	PART
cana-2991	343	54	ability	ability	NOUN
cana-2991	343	55	to	to	PART
cana-2991	343	56	properly	properly	ADV
cana-2991	343	57	recognize	recognize	VERB
cana-2991	343	58	positive	positive	ADJ
cana-2991	343	59	instances	instance	NOUN
cana-2991	343	60	(	(	PUNCT
cana-2991	343	61	real	real	ADJ
cana-2991	343	62	news	news	NOUN
cana-2991	343	63	)	)	PUNCT
cana-2991	343	64	,	,	PUNCT
cana-2991	343	65	recall	recall	VERB
cana-2991	343	66	:	:	PUNCT
cana-2991	343	67	how	how	SCONJ
cana-2991	343	68	good	good	ADJ
cana-2991	343	69	the	the	DET
cana-2991	343	70	model	model	NOUN
cana-2991	343	71	is	be	AUX
cana-2991	343	72	at	at	ADP
cana-2991	343	73	finding	find	VERB
cana-2991	343	74	all	all	DET
cana-2991	343	75	the	the	DET
cana-2991	343	76	positive	positive	ADJ
cana-2991	343	77	instances	instance	NOUN
cana-2991	343	78	(	(	PUNCT
cana-2991	343	79	true	true	ADJ
cana-2991	343	80	news	news	NOUN
cana-2991	343	81	)	)	PUNCT
cana-2991	343	82	f1	f1	NOUN
cana-2991	343	83	score	score	NOUN
cana-2991	343	84	is	be	AUX
cana-2991	343	85	the	the	DET
cana-2991	343	86	harmonic	harmonic	ADJ
cana-2991	343	87	mean	mean	NOUN
cana-2991	343	88	of	of	ADP
cana-2991	343	89	precision	precision	NOUN
cana-2991	343	90	and	and	CCONJ
cana-2991	343	91	recall	recall	NOUN
cana-2991	343	92	,	,	PUNCT
cana-2991	343	93	hence	hence	ADV
cana-2991	343	94	it	it	PRON
cana-2991	343	95	gives	give	VERB
cana-2991	343	96	a	a	DET
cana-2991	343	97	better	well	ADJ
cana-2991	343	98	measure	measure	NOUN
cana-2991	343	99	of	of	ADP
cana-2991	343	100	balance	balance	NOUN
cana-2991	343	101	between	between	ADP
cana-2991	343	102	them	they	PRON
cana-2991	343	103	.	.	PUNCT
cana-2991	344	1	figure	figure	VERB
cana-2991	344	2	4	4	NUM
cana-2991	344	3	.	.	PUNCT
cana-2991	344	4	model	model	NOUN
cana-2991	344	5	performance	performance	NOUN
cana-2991	344	6	comparison	comparison	NOUN
cana-2991	344	7	2	2	NUM
cana-2991	344	8	.	.	PUNCT
cana-2991	344	9	results	result	VERB
cana-2991	344	10	2.1	2.1	NUM
cana-2991	344	11	architectures	architecture	NOUN
cana-2991	344	12	of	of	ADP
cana-2991	344	13	embedding	embed	VERB
cana-2991	344	14	models	model	NOUN
cana-2991	344	15	table	table	NOUN
cana-2991	344	16	2	2	NUM
cana-2991	344	17	shows	show	VERB
cana-2991	344	18	the	the	DET
cana-2991	344	19	results	result	NOUN
cana-2991	344	20	using	use	VERB
cana-2991	344	21	different	different	ADJ
cana-2991	344	22	classifiers	classifier	NOUN
cana-2991	344	23	and	and	CCONJ
cana-2991	344	24	table	table	NOUN
cana-2991	344	25	3	3	NUM
cana-2991	344	26	gives	give	VERB
cana-2991	344	27	the	the	DET
cana-2991	344	28	results	result	NOUN
cana-2991	344	29	of	of	ADP
cana-2991	344	30	classifier	classifier	NOUN
cana-2991	344	31	-	-	PUNCT
cana-2991	344	32	typespecific	typespecific	NOUN
cana-2991	344	33	differences	difference	NOUN
cana-2991	344	34	as	as	SCONJ
cana-2991	344	35	supported	support	VERB
cana-2991	344	36	by	by	ADP
cana-2991	344	37	each	each	DET
cana-2991	344	38	word	word	NOUN
cana-2991	344	39	embedding	embed	VERB
cana-2991	344	40	model	model	NOUN
cana-2991	344	41	on	on	ADP
cana-2991	344	42	politifact	politifact	PROPN
cana-2991	344	43	dataset	dataset	NOUN
cana-2991	344	44	and	and	CCONJ
cana-2991	344	45	liar	liar	NOUN
cana-2991	344	46	dataset	dataset	NOUN
cana-2991	344	47	respectively	respectively	ADV
cana-2991	344	48	.	.	PUNCT
cana-2991	345	1	the	the	DET
cana-2991	345	2	tables	table	NOUN
cana-2991	345	3	emphasize	emphasize	VERB
cana-2991	345	4	the	the	DET
cana-2991	345	5	accuracy	accuracy	NOUN
cana-2991	345	6	,	,	PUNCT
cana-2991	345	7	precision	precision	NOUN
cana-2991	345	8	,	,	PUNCT
cana-2991	345	9	recall	recall	NOUN
cana-2991	345	10	and	and	CCONJ
cana-2991	345	11	f1	f1	NOUN
cana-2991	345	12	-	-	PUNCT
cana-2991	345	13	score	score	NOUN
cana-2991	345	14	per	per	ADP
cana-2991	345	15	combination	combination	NOUN
cana-2991	345	16	of	of	ADP
cana-2991	345	17	embedding	embed	VERB
cana-2991	345	18	technique	technique	NOUN
cana-2991	345	19	/	/	SYM
cana-2991	345	20	classifier	classifier	NOUN
cana-2991	345	21	.	.	PUNCT
cana-2991	346	1	model	model	NOUN
cana-2991	346	2	embedding	embed	VERB
cana-2991	346	3	accuracy	accuracy	NOUN
cana-2991	346	4	precision	precision	NOUN
cana-2991	346	5	recall	recall	VERB
cana-2991	346	6	f1	f1	NOUN
cana-2991	346	7	-	-	PUNCT
cana-2991	346	8	score	score	NOUN
cana-2991	346	9	logistic	logistic	ADJ
cana-2991	346	10	regression	regression	NOUN
cana-2991	346	11	bow	bow	VERB
cana-2991	346	12	80.5	80.5	NUM
cana-2991	346	13	%	%	NOUN
cana-2991	346	14	79.8	79.8	NUM
cana-2991	346	15	%	%	NOUN
cana-2991	346	16	81.0	81.0	NUM
cana-2991	346	17	%	%	NOUN
cana-2991	346	18	80.4	80.4	NUM
cana-2991	346	19	%	%	NOUN
cana-2991	346	20	logistic	logistic	ADJ
cana-2991	346	21	regression	regression	NOUN
cana-2991	346	22	tf	tf	PROPN
cana-2991	346	23	-	-	PUNCT
cana-2991	346	24	idf	idf	PROPN
cana-2991	346	25	82.1	82.1	NUM
cana-2991	346	26	%	%	NOUN
cana-2991	346	27	81.3	81.3	NUM
cana-2991	346	28	%	%	NOUN
cana-2991	346	29	82.8	82.8	NUM
cana-2991	346	30	%	%	NOUN
cana-2991	346	31	82.0	82.0	NUM
cana-2991	346	32	%	%	NOUN
cana-2991	346	33	logistic	logistic	ADJ
cana-2991	346	34	regression	regression	NOUN
cana-2991	346	35	word2vec	word2vec	ADP
cana-2991	346	36	85.7	85.7	NUM
cana-2991	346	37	%	%	NOUN
cana-2991	346	38	86.0	86.0	NUM
cana-2991	346	39	%	%	NOUN
cana-2991	346	40	85.4	85.4	NUM
cana-2991	346	41	%	%	NOUN
cana-2991	346	42	85.7	85.7	NUM
cana-2991	346	43	%	%	NOUN
cana-2991	346	44	logistic	logistic	ADJ
cana-2991	346	45	regression	regression	NOUN
cana-2991	346	46	bert	bert	PROPN
cana-2991	346	47	89.3	89.3	NUM
cana-2991	346	48	%	%	NOUN
cana-2991	346	49	88.5	88.5	NUM
cana-2991	346	50	%	%	NOUN
cana-2991	346	51	90.0	90.0	NUM
cana-2991	346	52	%	%	NOUN
cana-2991	346	53	89.2	89.2	NUM
cana-2991	346	54	%	%	NOUN
cana-2991	346	55	random	random	ADJ
cana-2991	346	56	forest	forest	NOUN
cana-2991	346	57	bow	bow	NOUN
cana-2991	346	58	81.2	81.2	NUM
cana-2991	346	59	%	%	NOUN
cana-2991	346	60	81.5	81.5	NUM
cana-2991	346	61	%	%	NOUN
cana-2991	346	62	80.9	80.9	NUM
cana-2991	346	63	%	%	NOUN
cana-2991	346	64	81.2	81.2	NUM
cana-2991	346	65	%	%	NOUN
cana-2991	346	66	random	random	ADJ
cana-2991	346	67	forest	forest	NOUN
cana-2991	347	1	tf	tf	PROPN
cana-2991	347	2	-	-	PUNCT
cana-2991	347	3	idf	idf	PROPN
cana-2991	347	4	83.7	83.7	NUM
cana-2991	347	5	%	%	NOUN
cana-2991	347	6	83.2	83.2	NUM
cana-2991	347	7	%	%	NOUN
cana-2991	347	8	84.1	84.1	NUM
cana-2991	347	9	%	%	NOUN
cana-2991	347	10	83.6	83.6	NUM
cana-2991	347	11	%	%	NOUN
cana-2991	347	12	random	random	ADJ
cana-2991	347	13	forest	forest	NOUN
cana-2991	347	14	word2vec	word2vec	X
cana-2991	347	15	87.9	87.9	NUM
cana-2991	347	16	%	%	NOUN
cana-2991	347	17	87.6	87.6	NUM
cana-2991	347	18	%	%	NOUN
cana-2991	347	19	88.1	88.1	NUM
cana-2991	347	20	%	%	NOUN
cana-2991	347	21	87.8	87.8	NUM
cana-2991	347	22	%	%	NOUN
cana-2991	347	23	random	random	ADJ
cana-2991	347	24	forest	forest	NOUN
cana-2991	347	25	bert	bert	PROPN
cana-2991	347	26	91.0	91.0	NUM
cana-2991	347	27	%	%	NOUN
cana-2991	347	28	90.4	90.4	NUM
cana-2991	347	29	%	%	NOUN
cana-2991	347	30	91.3	91.3	NUM
cana-2991	347	31	%	%	NOUN
cana-2991	347	32	90.8	90.8	NUM
cana-2991	347	33	%	%	NOUN
cana-2991	347	34	neural	neural	ADJ
cana-2991	347	35	network	network	NOUN
cana-2991	347	36	bow	bow	VERB
cana-2991	347	37	82.5	82.5	NUM
cana-2991	347	38	%	%	NOUN
cana-2991	347	39	83.1	83.1	NUM
cana-2991	347	40	%	%	NOUN
cana-2991	347	41	81.9	81.9	NUM
cana-2991	347	42	%	%	NOUN
cana-2991	347	43	82.5	82.5	NUM
cana-2991	347	44	%	%	NOUN
cana-2991	347	45	communications	communication	NOUN
cana-2991	347	46	on	on	ADP
cana-2991	347	47	applied	apply	VERB
cana-2991	347	48	nonlinear	nonlinear	ADJ
cana-2991	347	49	analysis	analysis	NOUN
cana-2991	347	50	issn	issn	NOUN
cana-2991	347	51	:	:	PUNCT
cana-2991	347	52	1074	1074	NUM
cana-2991	347	53	-	-	PUNCT
cana-2991	347	54	133x	133x	NUM
cana-2991	347	55	vol	vol	NOUN
cana-2991	347	56	32	32	NUM
cana-2991	347	57	no	no	NOUN
cana-2991	347	58	.	.	PUNCT
cana-2991	348	1	5s	5s	NUM
cana-2991	348	2	(	(	PUNCT
cana-2991	348	3	2025	2025	NUM
cana-2991	348	4	)	)	PUNCT
cana-2991	348	5	169	169	NUM
cana-2991	348	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	348	7	model	model	NOUN
cana-2991	348	8	embedding	embed	VERB
cana-2991	348	9	accuracy	accuracy	NOUN
cana-2991	348	10	precision	precision	NOUN
cana-2991	348	11	recall	recall	VERB
cana-2991	348	12	f1	f1	NOUN
cana-2991	348	13	-	-	PUNCT
cana-2991	348	14	score	score	NOUN
cana-2991	348	15	neural	neural	ADJ
cana-2991	348	16	network	network	NOUN
cana-2991	348	17	tf	tf	PROPN
cana-2991	348	18	-	-	PUNCT
cana-2991	348	19	idf	idf	PROPN
cana-2991	348	20	85.9	85.9	NUM
cana-2991	348	21	%	%	NOUN
cana-2991	348	22	85.2	85.2	NUM
cana-2991	348	23	%	%	NOUN
cana-2991	348	24	86.4	86.4	NUM
cana-2991	348	25	%	%	NOUN
cana-2991	348	26	85.8	85.8	NUM
cana-2991	348	27	%	%	NOUN
cana-2991	348	28	neural	neural	ADJ
cana-2991	348	29	network	network	NOUN
cana-2991	348	30	word2vec	word2vec	ADP
cana-2991	348	31	89.5	89.5	NUM
cana-2991	348	32	%	%	NOUN
cana-2991	348	33	89.2	89.2	NUM
cana-2991	348	34	%	%	NOUN
cana-2991	348	35	89.7	89.7	NUM
cana-2991	348	36	%	%	NOUN
cana-2991	348	37	89.4	89.4	NUM
cana-2991	348	38	%	%	NOUN
cana-2991	348	39	neural	neural	ADJ
cana-2991	348	40	network	network	NOUN
cana-2991	348	41	bert	bert	PROPN
cana-2991	348	42	92.2	92.2	NUM
cana-2991	348	43	%	%	NOUN
cana-2991	348	44	91.8	91.8	NUM
cana-2991	348	45	%	%	NOUN
cana-2991	348	46	92.6	92.6	NUM
cana-2991	348	47	%	%	NOUN
cana-2991	348	48	92.2	92.2	NUM
cana-2991	348	49	%	%	NOUN
cana-2991	348	50	svm	svm	NOUN
cana-2991	348	51	bow	bow	VERB
cana-2991	348	52	80.1	80.1	NUM
cana-2991	348	53	%	%	NOUN
cana-2991	348	54	80.2	80.2	NUM
cana-2991	348	55	%	%	NOUN
cana-2991	348	56	80.0	80.0	NUM
cana-2991	348	57	%	%	NOUN
cana-2991	348	58	80.1	80.1	NUM
cana-2991	348	59	%	%	NOUN
cana-2991	348	60	svm	svm	PROPN
cana-2991	348	61	tf	tf	PROPN
cana-2991	348	62	-	-	PUNCT
cana-2991	348	63	idf	idf	PROPN
cana-2991	348	64	83.0	83.0	NUM
cana-2991	348	65	%	%	NOUN
cana-2991	348	66	82.4	82.4	NUM
cana-2991	348	67	%	%	NOUN
cana-2991	348	68	83.6	83.6	NUM
cana-2991	348	69	%	%	NOUN
cana-2991	348	70	83.0	83.0	NUM
cana-2991	348	71	%	%	NOUN
cana-2991	348	72	svm	svm	NOUN
cana-2991	348	73	word2vec	word2vec	ADP
cana-2991	348	74	86.8	86.8	NUM
cana-2991	348	75	%	%	NOUN
cana-2991	348	76	86.5	86.5	NUM
cana-2991	348	77	%	%	NOUN
cana-2991	348	78	87.1	87.1	NUM
cana-2991	348	79	%	%	NOUN
cana-2991	348	80	86.8	86.8	NUM
cana-2991	348	81	%	%	NOUN
cana-2991	348	82	svm	svm	PROPN
cana-2991	348	83	bert	bert	PROPN
cana-2991	348	84	90.1	90.1	NUM
cana-2991	348	85	%	%	NOUN
cana-2991	348	86	89.7	89.7	NUM
cana-2991	348	87	%	%	NOUN
cana-2991	348	88	90.5	90.5	NUM
cana-2991	348	89	%	%	NOUN
cana-2991	348	90	90.1	90.1	NUM
cana-2991	348	91	%	%	NOUN
cana-2991	348	92	table	table	NOUN
cana-2991	348	93	2	2	NUM
cana-2991	348	94	:	:	PUNCT
cana-2991	348	95	politifact	politifact	PROPN
cana-2991	348	96	dataset	dataset	PROPN
cana-2991	348	97	results	result	NOUN
cana-2991	348	98	model	model	VERB
cana-2991	348	99	embedding	embed	VERB
cana-2991	348	100	accuracy	accuracy	NOUN
cana-2991	348	101	precision	precision	NOUN
cana-2991	348	102	recall	recall	VERB
cana-2991	348	103	f1	f1	NOUN
cana-2991	348	104	-	-	PUNCT
cana-2991	348	105	score	score	NOUN
cana-2991	348	106	logistic	logistic	ADJ
cana-2991	348	107	regression	regression	NOUN
cana-2991	348	108	bow	bow	VERB
cana-2991	348	109	78.9	78.9	NUM
cana-2991	348	110	%	%	NOUN
cana-2991	348	111	77.8	77.8	NUM
cana-2991	348	112	%	%	NOUN
cana-2991	348	113	79.4	79.4	NUM
cana-2991	348	114	%	%	NOUN
cana-2991	348	115	78.6	78.6	NUM
cana-2991	348	116	%	%	NOUN
cana-2991	348	117	logistic	logistic	ADJ
cana-2991	348	118	regression	regression	NOUN
cana-2991	348	119	tf	tf	PROPN
cana-2991	348	120	-	-	PUNCT
cana-2991	348	121	idf	idf	PROPN
cana-2991	348	122	80.6	80.6	NUM
cana-2991	348	123	%	%	NOUN
cana-2991	348	124	79.9	79.9	NUM
cana-2991	348	125	%	%	NOUN
cana-2991	348	126	81.0	81.0	NUM
cana-2991	348	127	%	%	NOUN
cana-2991	348	128	80.4	80.4	NUM
cana-2991	348	129	%	%	NOUN
cana-2991	348	130	logistic	logistic	ADJ
cana-2991	348	131	regression	regression	NOUN
cana-2991	348	132	word2vec	word2vec	AUX
cana-2991	348	133	83.3	83.3	NUM
cana-2991	348	134	%	%	NOUN
cana-2991	348	135	82.7	82.7	NUM
cana-2991	348	136	%	%	NOUN
cana-2991	348	137	84.0	84.0	NUM
cana-2991	348	138	%	%	NOUN
cana-2991	348	139	83.3	83.3	NUM
cana-2991	348	140	%	%	NOUN
cana-2991	348	141	logistic	logistic	ADJ
cana-2991	348	142	regression	regression	NOUN
cana-2991	348	143	bert	bert	NOUN
cana-2991	348	144	87.4	87.4	NUM
cana-2991	348	145	%	%	NOUN
cana-2991	348	146	86.6	86.6	NUM
cana-2991	348	147	%	%	NOUN
cana-2991	348	148	88.1	88.1	NUM
cana-2991	348	149	%	%	NOUN
cana-2991	348	150	87.3	87.3	NUM
cana-2991	348	151	%	%	NOUN
cana-2991	348	152	random	random	ADJ
cana-2991	348	153	forest	forest	NOUN
cana-2991	348	154	bow	bow	NOUN
cana-2991	348	155	80.1	80.1	NUM
cana-2991	348	156	%	%	NOUN
cana-2991	348	157	79.6	79.6	NUM
cana-2991	348	158	%	%	NOUN
cana-2991	348	159	80.5	80.5	NUM
cana-2991	348	160	%	%	NOUN
cana-2991	348	161	80.0	80.0	NUM
cana-2991	348	162	%	%	NOUN
cana-2991	348	163	random	random	ADJ
cana-2991	348	164	forest	forest	NOUN
cana-2991	348	165	tf	tf	PROPN
cana-2991	348	166	-	-	PUNCT
cana-2991	348	167	idf	idf	NOUN
cana-2991	348	168	82.9	82.9	NUM
cana-2991	348	169	%	%	NOUN
cana-2991	348	170	82.4	82.4	NUM
cana-2991	348	171	%	%	NOUN
cana-2991	348	172	83.5	83.5	NUM
cana-2991	348	173	%	%	NOUN
cana-2991	348	174	82.9	82.9	NUM
cana-2991	348	175	%	%	NOUN
cana-2991	348	176	random	random	ADJ
cana-2991	348	177	forest	forest	NOUN
cana-2991	348	178	word2vec	word2vec	PUNCT
cana-2991	348	179	85.2	85.2	NUM
cana-2991	348	180	%	%	NOUN
cana-2991	348	181	85.0	85.0	NUM
cana-2991	348	182	%	%	NOUN
cana-2991	348	183	85.5	85.5	NUM
cana-2991	348	184	%	%	NOUN
cana-2991	348	185	85.2	85.2	NUM
cana-2991	348	186	%	%	NOUN
cana-2991	348	187	random	random	ADJ
cana-2991	348	188	forest	forest	NOUN
cana-2991	348	189	bert	bert	PROPN
cana-2991	348	190	89.0	89.0	NUM
cana-2991	348	191	%	%	NOUN
cana-2991	348	192	88.3	88.3	NUM
cana-2991	348	193	%	%	NOUN
cana-2991	348	194	89.5	89.5	NUM
cana-2991	348	195	%	%	NOUN
cana-2991	348	196	88.9	88.9	NUM
cana-2991	348	197	%	%	NOUN
cana-2991	348	198	neural	neural	ADJ
cana-2991	348	199	network	network	NOUN
cana-2991	348	200	bow	bow	VERB
cana-2991	348	201	79.8	79.8	NUM
cana-2991	348	202	%	%	NOUN
cana-2991	348	203	78.5	78.5	NUM
cana-2991	348	204	%	%	NOUN
cana-2991	348	205	81.0	81.0	NUM
cana-2991	348	206	%	%	NOUN
cana-2991	348	207	79.7	79.7	NUM
cana-2991	348	208	%	%	NOUN
cana-2991	348	209	neural	neural	ADJ
cana-2991	348	210	network	network	NOUN
cana-2991	348	211	tf	tf	PROPN
cana-2991	348	212	-	-	PUNCT
cana-2991	348	213	idf	idf	PROPN
cana-2991	348	214	83.5	83.5	NUM
cana-2991	348	215	%	%	NOUN
cana-2991	348	216	82.8	82.8	NUM
cana-2991	348	217	%	%	NOUN
cana-2991	348	218	84.3	84.3	NUM
cana-2991	348	219	%	%	NOUN
cana-2991	348	220	83.5	83.5	NUM
cana-2991	348	221	%	%	NOUN
cana-2991	348	222	neural	neural	ADJ
cana-2991	348	223	network	network	NOUN
cana-2991	348	224	word2vec	word2vec	X
cana-2991	348	225	86.9	86.9	NUM
cana-2991	348	226	%	%	NOUN
cana-2991	348	227	86.3	86.3	NUM
cana-2991	348	228	%	%	NOUN
cana-2991	348	229	87.4	87.4	NUM
cana-2991	348	230	%	%	NOUN
cana-2991	348	231	86.8	86.8	NUM
cana-2991	348	232	%	%	NOUN
cana-2991	348	233	neural	neural	ADJ
cana-2991	348	234	network	network	NOUN
cana-2991	348	235	bert	bert	PROPN
cana-2991	348	236	91.3	91.3	NUM
cana-2991	348	237	%	%	NOUN
cana-2991	348	238	89.6	89.6	NUM
cana-2991	348	239	%	%	NOUN
cana-2991	348	240	88.5	88.5	NUM
cana-2991	348	241	%	%	NOUN
cana-2991	348	242	90.4	90.4	NUM
cana-2991	348	243	%	%	NOUN
cana-2991	348	244	table	table	NOUN
cana-2991	348	245	3	3	NUM
cana-2991	348	246	:	:	PUNCT
cana-2991	348	247	liar	liar	NOUN
cana-2991	348	248	dataset	dataset	NOUN
cana-2991	348	249	results	result	VERB
cana-2991	348	250	2.2	2.2	NUM
cana-2991	348	251	analysis	analysis	NOUN
cana-2991	348	252	of	of	ADP
cana-2991	348	253	results	result	NOUN
cana-2991	348	254	table	table	NOUN
cana-2991	348	255	2	2	NUM
cana-2991	348	256	and	and	CCONJ
cana-2991	348	257	table	table	NOUN
cana-2991	348	258	3	3	NUM
cana-2991	348	259	:	:	PUNCT
cana-2991	348	260	results	result	VERB
cana-2991	348	261	these	these	DET
cana-2991	348	262	results	result	NOUN
cana-2991	348	263	demonstrate	demonstrate	VERB
cana-2991	348	264	the	the	DET
cana-2991	348	265	usability	usability	NOUN
cana-2991	348	266	of	of	ADP
cana-2991	348	267	embedding	embed	VERB
cana-2991	348	268	methods	method	NOUN
cana-2991	348	269	with	with	ADP
cana-2991	348	270	machine	machine	NOUN
cana-2991	348	271	learning	learning	NOUN
cana-2991	348	272	models	model	NOUN
cana-2991	348	273	for	for	ADP
cana-2991	348	274	fake	fake	ADJ
cana-2991	348	275	news	news	NOUN
cana-2991	348	276	detection	detection	NOUN
cana-2991	348	277	.	.	PUNCT
cana-2991	349	1	using	use	VERB
cana-2991	349	2	figure	figure	NOUN
cana-2991	349	3	5	5	NUM
cana-2991	349	4	,	,	PUNCT
cana-2991	349	5	it	it	PRON
cana-2991	349	6	shows	show	VERB
cana-2991	349	7	that	that	SCONJ
cana-2991	349	8	bert	bert	NOUN
cana-2991	349	9	models	model	NOUN
cana-2991	349	10	have	have	VERB
cana-2991	349	11	the	the	DET
cana-2991	349	12	highest	high	ADJ
cana-2991	349	13	accuracy	accuracy	NOUN
cana-2991	349	14	among	among	ADP
cana-2991	349	15	bow	bow	PROPN
cana-2991	349	16	,	,	PUNCT
cana-2991	349	17	tf	tf	PROPN
cana-2991	349	18	-	-	PUNCT
cana-2991	349	19	idf	idf	PROPN
cana-2991	349	20	and	and	CCONJ
cana-2991	349	21	word2vec	word2vec	PROPN
cana-2991	349	22	.	.	PUNCT
cana-2991	350	1	our	our	PRON
cana-2991	350	2	findings	finding	NOUN
cana-2991	350	3	we	we	PRON
cana-2991	350	4	noted	note	VERB
cana-2991	350	5	the	the	DET
cana-2991	350	6	following	follow	VERB
cana-2991	350	7	trends	trend	NOUN
cana-2991	350	8	:	:	PUNCT
cana-2991	350	9	1	1	X
cana-2991	350	10	.	.	X
cana-2991	350	11	bert	bert	PROPN
cana-2991	350	12	:	:	PUNCT
cana-2991	350	13	,	,	PUNCT
cana-2991	350	14	all	all	DET
cana-2991	350	15	classifiers	classifier	NOUN
cana-2991	350	16	reached	reach	VERB
cana-2991	350	17	the	the	DET
cana-2991	350	18	highest	high	ADJ
cana-2991	350	19	performance	performance	NOUN
cana-2991	350	20	when	when	SCONJ
cana-2991	350	21	combined	combine	VERB
cana-2991	350	22	with	with	ADP
cana-2991	350	23	bert	bert	PROPN
cana-2991	350	24	embeddings	embedding	NOUN
cana-2991	350	25	,	,	PUNCT
cana-2991	350	26	neural	neural	ADJ
cana-2991	350	27	networks	network	NOUN
cana-2991	350	28	and	and	CCONJ
cana-2991	350	29	random	random	ADJ
cana-2991	350	30	forests	forest	NOUN
cana-2991	350	31	performed	perform	VERB
cana-2991	350	32	better	well	ADV
cana-2991	350	33	this	this	PRON
cana-2991	350	34	provides	provide	VERB
cana-2991	350	35	evidence	evidence	NOUN
cana-2991	350	36	that	that	SCONJ
cana-2991	350	37	for	for	ADP
cana-2991	350	38	tasks	task	NOUN
cana-2991	350	39	that	that	PRON
cana-2991	350	40	demand	demand	VERB
cana-2991	350	41	a	a	DET
cana-2991	350	42	rich	rich	ADJ
cana-2991	350	43	understanding	understanding	NOUN
cana-2991	350	44	of	of	ADP
cana-2991	350	45	the	the	DET
cana-2991	350	46	text	text	NOUN
cana-2991	350	47	,	,	PUNCT
cana-2991	350	48	e.g.	e.g.	ADV
cana-2991	350	49	,	,	PUNCT
cana-2991	350	50	fake	fake	ADJ
cana-2991	350	51	news	news	NOUN
cana-2991	350	52	detection	detection	NOUN
cana-2991	350	53	,	,	PUNCT
cana-2991	350	54	contextual	contextual	ADJ
cana-2991	350	55	embeddings	embedding	NOUN
cana-2991	350	56	have	have	AUX
cana-2991	350	57	an	an	DET
cana-2991	350	58	advantage	advantage	NOUN
cana-2991	350	59	.	.	PUNCT
cana-2991	351	1	2	2	X
cana-2991	351	2	.	.	X
cana-2991	351	3	solid	solid	ADJ
cana-2991	351	4	performance	performance	NOUN
cana-2991	351	5	by	by	ADP
cana-2991	351	6	word2vec	word2vec	PROPN
cana-2991	351	7	:	:	PUNCT
cana-2991	351	8	bert	bert	NOUN
cana-2991	351	9	performance	performance	NOUN
cana-2991	351	10	was	be	AUX
cana-2991	351	11	the	the	DET
cana-2991	351	12	best	good	ADJ
cana-2991	351	13	overall	overall	ADJ
cana-2991	351	14	,	,	PUNCT
cana-2991	351	15	with	with	ADP
cana-2991	351	16	good	good	ADJ
cana-2991	351	17	competing	compete	VERB
cana-2991	351	18	results	result	NOUN
cana-2991	351	19	seen	see	VERB
cana-2991	351	20	in	in	ADP
cana-2991	351	21	word2vec	word2vec	X
cana-2991	351	22	embeddings	embedding	NOUN
cana-2991	351	23	(	(	PUNCT
cana-2991	351	24	both	both	PRON
cana-2991	351	25	cbow	cbow	VERB
cana-2991	351	26	&	&	CCONJ
cana-2991	351	27	skip	skip	VERB
cana-2991	351	28	-	-	PUNCT
cana-2991	351	29	gram	gram	NOUN
cana-2991	351	30	)	)	PUNCT
cana-2991	351	31	,	,	PUNCT
cana-2991	351	32	especially	especially	ADV
cana-2991	351	33	combined	combine	VERB
cana-2991	351	34	with	with	ADP
cana-2991	351	35	logistic	logistic	ADJ
cana-2991	351	36	regression	regression	NOUN
cana-2991	351	37	and	and	CCONJ
cana-2991	351	38	random	random	ADJ
cana-2991	351	39	forest	forest	NOUN
cana-2991	351	40	.	.	PUNCT
cana-2991	352	1	this	this	PRON
cana-2991	352	2	suggests	suggest	VERB
cana-2991	352	3	the	the	DET
cana-2991	352	4	ability	ability	NOUN
cana-2991	352	5	of	of	ADP
cana-2991	352	6	word2vec	word2vec	VERB
cana-2991	352	7	to	to	PART
cana-2991	352	8	understand	understand	VERB
cana-2991	352	9	the	the	DET
cana-2991	352	10	relationship	relationship	NOUN
cana-2991	352	11	between	between	ADP
cana-2991	352	12	classes	class	NOUN
cana-2991	352	13	better	well	ADV
cana-2991	352	14	due	due	ADP
cana-2991	352	15	to	to	ADP
cana-2991	352	16	which	which	DET
cana-2991	352	17	classification	classification	NOUN
cana-2991	352	18	performance	performance	NOUN
cana-2991	352	19	is	be	AUX
cana-2991	352	20	a	a	DET
cana-2991	352	21	lot	lot	NOUN
cana-2991	352	22	better	well	ADJ
cana-2991	352	23	despite	despite	SCONJ
cana-2991	352	24	not	not	PART
cana-2991	352	25	capturing	capture	VERB
cana-2991	352	26	bidirectional	bidirectional	ADJ
cana-2991	352	27	context	context	NOUN
cana-2991	352	28	like	like	ADP
cana-2991	352	29	in	in	ADP
cana-2991	352	30	bert	bert	PROPN
cana-2991	352	31	.	.	PUNCT
cana-2991	353	1	3	3	X
cana-2991	353	2	.	.	X
cana-2991	353	3	traditional	traditional	ADJ
cana-2991	353	4	methods	method	NOUN
cana-2991	353	5	like	like	ADP
cana-2991	353	6	bow	bow	NOUN
cana-2991	353	7	and	and	CCONJ
cana-2991	353	8	tf	tf	PROPN
cana-2991	353	9	-	-	PUNCT
cana-2991	353	10	idf	idf	PROPN
cana-2991	353	11	:	:	PUNCT
cana-2991	353	12	behind	behind	ADP
cana-2991	353	13	bow	bow	NOUN
cana-2991	353	14	and	and	CCONJ
cana-2991	353	15	tf	tf	PROPN
cana-2991	353	16	-	-	PUNCT
cana-2991	353	17	idf	idf	PROPN
cana-2991	353	18	lagged	lag	VERB
cana-2991	353	19	behind	behind	ADV
cana-2991	353	20	by	by	ADP
cana-2991	353	21	comparison	comparison	NOUN
cana-2991	353	22	with	with	ADP
cana-2991	353	23	word2vec	word2vec	PROPN
cana-2991	353	24	and	and	CCONJ
cana-2991	353	25	bert	bert	PROPN
cana-2991	353	26	.	.	PUNCT
cana-2991	354	1	as	as	SCONJ
cana-2991	354	2	bow	bow	NOUN
cana-2991	354	3	relies	rely	VERB
cana-2991	354	4	on	on	ADP
cana-2991	354	5	each	each	DET
cana-2991	354	6	word	word	NOUN
cana-2991	354	7	being	be	AUX
cana-2991	354	8	independent	independent	ADJ
cana-2991	354	9	and	and	CCONJ
cana-2991	354	10	the	the	DET
cana-2991	354	11	communications	communication	NOUN
cana-2991	354	12	on	on	ADP
cana-2991	354	13	applied	apply	VERB
cana-2991	354	14	nonlinear	nonlinear	ADJ
cana-2991	354	15	analysis	analysis	NOUN
cana-2991	354	16	issn	issn	NOUN
cana-2991	354	17	:	:	PUNCT
cana-2991	354	18	1074	1074	NUM
cana-2991	354	19	-	-	PUNCT
cana-2991	354	20	133x	133x	NUM
cana-2991	354	21	vol	vol	NOUN
cana-2991	354	22	32	32	NUM
cana-2991	354	23	no	no	NOUN
cana-2991	354	24	.	.	PUNCT
cana-2991	355	1	5s	5s	NUM
cana-2991	355	2	(	(	PUNCT
cana-2991	355	3	2025	2025	NUM
cana-2991	355	4	)	)	PUNCT
cana-2991	355	5	170	170	NUM
cana-2991	356	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	356	2	perspective	perspective	NOUN
cana-2991	356	3	of	of	ADP
cana-2991	356	4	tf	tf	PROPN
cana-2991	356	5	-	-	PUNCT
cana-2991	356	6	idf	idf	PROPN
cana-2991	356	7	also	also	ADV
cana-2991	356	8	moves	move	VERB
cana-2991	356	9	toward	toward	ADP
cana-2991	356	10	frequency	frequency	NOUN
cana-2991	356	11	,	,	PUNCT
cana-2991	356	12	not	not	PART
cana-2991	356	13	context	context	NOUN
cana-2991	356	14	.	.	PUNCT
cana-2991	357	1	nevertheless	nevertheless	ADV
cana-2991	357	2	,	,	PUNCT
cana-2991	357	3	decent	decent	ADJ
cana-2991	357	4	results	result	NOUN
cana-2991	357	5	can	can	AUX
cana-2991	357	6	still	still	ADV
cana-2991	357	7	be	be	AUX
cana-2991	357	8	obtained	obtain	VERB
cana-2991	357	9	with	with	ADP
cana-2991	357	10	these	these	DET
cana-2991	357	11	methods	method	NOUN
cana-2991	357	12	,	,	PUNCT
cana-2991	357	13	particularly	particularly	ADV
cana-2991	357	14	in	in	ADP
cana-2991	357	15	simpler	simple	ADJ
cana-2991	357	16	models	model	NOUN
cana-2991	357	17	such	such	ADJ
cana-2991	357	18	as	as	ADP
cana-2991	357	19	logistic	logistic	ADJ
cana-2991	357	20	regression	regression	NOUN
cana-2991	357	21	.	.	PUNCT
cana-2991	358	1	4	4	X
cana-2991	358	2	.	.	X
cana-2991	358	3	it	it	PRON
cana-2991	358	4	was	be	AUX
cana-2991	358	5	true	true	ADJ
cana-2991	358	6	for	for	ADP
cana-2991	358	7	every	every	DET
cana-2991	358	8	embedding	embed	VERB
cana-2991	358	9	model	model	NOUN
cana-2991	358	10	:	:	PUNCT
cana-2991	358	11	in	in	ADP
cana-2991	358	12	interface	interface	NOUN
cana-2991	358	13	type	type	NOUN
cana-2991	358	14	3	3	NUM
cana-2991	358	15	,	,	PUNCT
cana-2991	358	16	neural	neural	ADJ
cana-2991	358	17	networks	network	NOUN
cana-2991	358	18	were	be	AUX
cana-2991	358	19	the	the	DET
cana-2991	358	20	best	good	ADJ
cana-2991	358	21	in	in	ADP
cana-2991	358	22	terms	term	NOUN
cana-2991	358	23	of	of	ADP
cana-2991	358	24	classification	classification	NOUN
cana-2991	358	25	accuracy	accuracy	NOUN
cana-2991	358	26	,	,	PUNCT
cana-2991	358	27	precision	precision	NOUN
cana-2991	358	28	,	,	PUNCT
cana-2991	358	29	recall	recall	NOUN
cana-2991	358	30	and	and	CCONJ
cana-2991	358	31	f1	f1	NOUN
cana-2991	358	32	-	-	PUNCT
cana-2991	358	33	scores	score	NOUN
cana-2991	358	34	.	.	PUNCT
cana-2991	359	1	neural	neural	ADJ
cana-2991	359	2	networks	network	NOUN
cana-2991	359	3	are	be	AUX
cana-2991	359	4	capable	capable	ADJ
cana-2991	359	5	of	of	ADP
cana-2991	359	6	learning	learn	VERB
cana-2991	359	7	non	non	ADJ
cana-2991	359	8	-	-	ADJ
cana-2991	359	9	linear	linear	ADJ
cana-2991	359	10	relationships	relationship	NOUN
cana-2991	359	11	between	between	ADP
cana-2991	359	12	features	feature	NOUN
cana-2991	359	13	,	,	PUNCT
cana-2991	359	14	so	so	SCONJ
cana-2991	359	15	they	they	PRON
cana-2991	359	16	should	should	AUX
cana-2991	359	17	be	be	AUX
cana-2991	359	18	the	the	DET
cana-2991	359	19	model	model	NOUN
cana-2991	359	20	that	that	SCONJ
cana-2991	359	21	we	we	PRON
cana-2991	359	22	will	will	AUX
cana-2991	359	23	use	use	VERB
cana-2991	359	24	to	to	PART
cana-2991	359	25	detect	detect	VERB
cana-2991	359	26	even	even	ADV
cana-2991	359	27	subtle	subtle	ADJ
cana-2991	359	28	patterns	pattern	NOUN
cana-2991	359	29	in	in	ADP
cana-2991	359	30	fake	fake	ADJ
cana-2991	359	31	news	news	NOUN
cana-2991	359	32	.	.	PUNCT
cana-2991	360	1	5	5	X
cana-2991	360	2	.	.	X
cana-2991	360	3	svm	svm	PROPN
cana-2991	360	4	and	and	CCONJ
cana-2991	360	5	logistic	logistic	ADJ
cana-2991	360	6	regression	regression	NOUN
cana-2991	360	7	perform	perform	VERB
cana-2991	360	8	well	well	ADV
cana-2991	360	9	as	as	ADP
cana-2991	360	10	baselines	baseline	NOUN
cana-2991	360	11	:	:	PUNCT
cana-2991	360	12	while	while	SCONJ
cana-2991	360	13	neural	neural	ADJ
cana-2991	360	14	networks	network	NOUN
cana-2991	360	15	tend	tend	VERB
cana-2991	360	16	to	to	PART
cana-2991	360	17	outperform	outperform	VERB
cana-2991	360	18	them	they	PRON
cana-2991	360	19	,	,	PUNCT
cana-2991	360	20	both	both	CCONJ
cana-2991	360	21	svm	svm	ADJ
cana-2991	360	22	and	and	CCONJ
cana-2991	360	23	logistic	logistic	ADJ
cana-2991	360	24	regression	regression	NOUN
cana-2991	360	25	make	make	VERB
cana-2991	360	26	good	good	ADJ
cana-2991	360	27	baselines	baseline	NOUN
cana-2991	360	28	,	,	PUNCT
cana-2991	360	29	especially	especially	ADV
cana-2991	360	30	with	with	ADP
cana-2991	360	31	more	more	ADV
cana-2991	360	32	sophisticated	sophisticated	ADJ
cana-2991	360	33	embeddings	embedding	NOUN
cana-2991	360	34	such	such	ADJ
cana-2991	360	35	as	as	ADP
cana-2991	360	36	word2vec	word2vec	X
cana-2991	360	37	and	and	CCONJ
cana-2991	360	38	bert	bert	PROPN
cana-2991	360	39	.	.	PUNCT
cana-2991	361	1	figure	figure	VERB
cana-2991	361	2	5	5	NUM
cana-2991	361	3	.	.	PUNCT
cana-2991	361	4	word	word	NOUN
cana-2991	361	5	embedding	embed	VERB
cana-2991	361	6	techniques	technique	NOUN
cana-2991	361	7	comparison	comparison	NOUN
cana-2991	361	8	on	on	ADP
cana-2991	361	9	model	model	NOUN
cana-2991	361	10	accuracy	accuracy	NOUN
cana-2991	361	11	2.3	2.3	NUM
cana-2991	361	12	effect	effect	NOUN
cana-2991	361	13	on	on	ADP
cana-2991	361	14	embedding	embed	VERB
cana-2991	361	15	dimension	dimension	NOUN
cana-2991	361	16	aside	aside	ADV
cana-2991	361	17	from	from	ADP
cana-2991	361	18	the	the	DET
cana-2991	361	19	main	main	ADJ
cana-2991	361	20	findings	finding	NOUN
cana-2991	361	21	,	,	PUNCT
cana-2991	361	22	we	we	PRON
cana-2991	361	23	also	also	ADV
cana-2991	361	24	examined	examine	VERB
cana-2991	361	25	how	how	SCONJ
cana-2991	361	26	changing	change	VERB
cana-2991	361	27	embedding	embed	VERB
cana-2991	361	28	dimensions	dimension	NOUN
cana-2991	361	29	affected	affect	VERB
cana-2991	361	30	model	model	NOUN
cana-2991	361	31	performance	performance	NOUN
cana-2991	361	32	.	.	PUNCT
cana-2991	362	1	table	table	NOUN
cana-2991	362	2	4	4	NUM
cana-2991	362	3	illustrates	illustrate	VERB
cana-2991	362	4	the	the	DET
cana-2991	362	5	performance	performance	NOUN
cana-2991	362	6	of	of	ADP
cana-2991	362	7	the	the	DET
cana-2991	362	8	word2vec	word2vec	PROPN
cana-2991	362	9	model	model	NOUN
cana-2991	362	10	for	for	ADP
cana-2991	362	11	different	different	ADJ
cana-2991	362	12	embedding	embed	VERB
cana-2991	362	13	dimensions	dimension	NOUN
cana-2991	362	14	.	.	PUNCT
cana-2991	363	1	model	model	NOUN
cana-2991	363	2	embedding	embed	VERB
cana-2991	363	3	dimensions	dimension	NOUN
cana-2991	363	4	accuracy	accuracy	NOUN
cana-2991	363	5	precision	precision	NOUN
cana-2991	363	6	recall	recall	VERB
cana-2991	363	7	f1	f1	NOUN
cana-2991	363	8	-	-	PUNCT
cana-2991	363	9	score	score	NOUN
cana-2991	363	10	logistic	logistic	ADJ
cana-2991	363	11	regression	regression	NOUN
cana-2991	363	12	100	100	NUM
cana-2991	363	13	82.5	82.5	NUM
cana-2991	363	14	%	%	NOUN
cana-2991	363	15	82.1	82.1	NUM
cana-2991	363	16	%	%	NOUN
cana-2991	363	17	83.0	83.0	NUM
cana-2991	363	18	%	%	NOUN
cana-2991	363	19	82.6	82.6	NUM
cana-2991	363	20	%	%	NOUN
cana-2991	363	21	logistic	logistic	ADJ
cana-2991	363	22	regression	regression	NOUN
cana-2991	363	23	300	300	NUM
cana-2991	363	24	85.7	85.7	NUM
cana-2991	363	25	%	%	NOUN
cana-2991	363	26	86.0	86.0	NUM
cana-2991	363	27	%	%	NOUN
cana-2991	363	28	85.4	85.4	NUM
cana-2991	363	29	%	%	NOUN
cana-2991	363	30	85.7	85.7	NUM
cana-2991	363	31	%	%	NOUN
cana-2991	363	32	logistic	logistic	ADJ
cana-2991	363	33	regression	regression	NOUN
cana-2991	363	34	768	768	NUM
cana-2991	363	35	88.1	88.1	NUM
cana-2991	363	36	%	%	NOUN
cana-2991	363	37	87.9	87.9	NUM
cana-2991	363	38	%	%	NOUN
cana-2991	363	39	88.4	88.4	NUM
cana-2991	363	40	%	%	NOUN
cana-2991	363	41	88.1	88.1	NUM
cana-2991	363	42	%	%	NOUN
cana-2991	363	43	random	random	ADJ
cana-2991	363	44	forest	forest	NOUN
cana-2991	363	45	100	100	NUM
cana-2991	363	46	83.0	83.0	NUM
cana-2991	363	47	%	%	NOUN
cana-2991	363	48	82.5	82.5	NUM
cana-2991	363	49	%	%	NOUN
cana-2991	363	50	83.6	83.6	NUM
cana-2991	363	51	%	%	NOUN
cana-2991	363	52	83.1	83.1	NUM
cana-2991	363	53	%	%	NOUN
cana-2991	363	54	random	random	ADJ
cana-2991	363	55	forest	forest	NOUN
cana-2991	363	56	300	300	NUM
cana-2991	363	57	87.2	87.2	NUM
cana-2991	363	58	%	%	NOUN
cana-2991	363	59	87.5	87.5	NUM
cana-2991	363	60	%	%	NOUN
cana-2991	363	61	87.0	87.0	NUM
cana-2991	363	62	%	%	NOUN
cana-2991	363	63	87.2	87.2	NUM
cana-2991	363	64	%	%	NOUN
cana-2991	363	65	random	random	ADJ
cana-2991	363	66	forest	forest	NOUN
cana-2991	363	67	768	768	NUM
cana-2991	363	68	90.2	90.2	NUM
cana-2991	363	69	%	%	NOUN
cana-2991	363	70	89.9	89.9	NUM
cana-2991	363	71	%	%	NOUN
cana-2991	363	72	90.5	90.5	NUM
cana-2991	363	73	%	%	NOUN
cana-2991	363	74	90.2	90.2	NUM
cana-2991	363	75	%	%	NOUN
cana-2991	363	76	neural	neural	ADJ
cana-2991	363	77	network	network	NOUN
cana-2991	363	78	100	100	NUM
cana-2991	363	79	85.9	85.9	NUM
cana-2991	363	80	%	%	NOUN
cana-2991	363	81	85.2	85.2	NUM
cana-2991	363	82	%	%	NOUN
cana-2991	363	83	86.4	86.4	NUM
cana-2991	363	84	%	%	NOUN
cana-2991	363	85	85.8	85.8	NUM
cana-2991	363	86	%	%	NOUN
cana-2991	363	87	neural	neural	ADJ
cana-2991	363	88	network	network	NOUN
cana-2991	363	89	300	300	NUM
cana-2991	363	90	89.1	89.1	NUM
cana-2991	363	91	%	%	NOUN
cana-2991	363	92	88.6	88.6	NUM
cana-2991	363	93	%	%	NOUN
cana-2991	363	94	89.5	89.5	NUM
cana-2991	363	95	%	%	NOUN
cana-2991	363	96	89.1	89.1	NUM
cana-2991	363	97	%	%	NOUN
cana-2991	363	98	neural	neural	ADJ
cana-2991	363	99	network	network	NOUN
cana-2991	363	100	768	768	NUM
cana-2991	363	101	91.7	91.7	NUM
cana-2991	363	102	%	%	NOUN
cana-2991	363	103	91.2	91.2	NUM
cana-2991	363	104	%	%	NOUN
cana-2991	363	105	92.3	92.3	NUM
cana-2991	363	106	%	%	NOUN
cana-2991	363	107	91.7	91.7	NUM
cana-2991	363	108	%	%	NOUN
cana-2991	363	109	table	table	NOUN
cana-2991	363	110	4	4	NUM
cana-2991	363	111	:	:	PUNCT
cana-2991	363	112	impact	impact	NOUN
cana-2991	363	113	of	of	ADP
cana-2991	363	114	embedding	embed	VERB
cana-2991	363	115	dimensions	dimension	NOUN
cana-2991	363	116	on	on	ADP
cana-2991	363	117	word2vec	word2vec	X
cana-2991	363	118	performance	performance	NOUN
cana-2991	363	119	(	(	PUNCT
cana-2991	363	120	politifact	politifact	PROPN
cana-2991	363	121	dataset	dataset	NOUN
cana-2991	363	122	)	)	PUNCT
cana-2991	363	123	increasing	increase	VERB
cana-2991	363	124	the	the	DET
cana-2991	363	125	dimensionality	dimensionality	NOUN
cana-2991	363	126	of	of	ADP
cana-2991	363	127	word2vec	word2vec	X
cana-2991	363	128	embeddings	embedding	NOUN
cana-2991	363	129	improves	improve	VERB
cana-2991	363	130	the	the	DET
cana-2991	363	131	performance	performance	NOUN
cana-2991	363	132	consistently	consistently	ADV
cana-2991	363	133	across	across	ADP
cana-2991	363	134	all	all	DET
cana-2991	363	135	models	model	NOUN
cana-2991	363	136	,	,	PUNCT
cana-2991	363	137	as	as	SCONJ
cana-2991	363	138	seen	see	VERB
cana-2991	363	139	from	from	ADP
cana-2991	363	140	table	table	NOUN
cana-2991	363	141	4	4	NUM
cana-2991	363	142	.	.	PUNCT
cana-2991	364	1	the	the	DET
cana-2991	364	2	embeddings	embedding	NOUN
cana-2991	364	3	in	in	ADP
cana-2991	364	4	higher	high	ADJ
cana-2991	364	5	-	-	PUNCT
cana-2991	364	6	dimensions	dimension	NOUN
cana-2991	364	7	are	be	AUX
cana-2991	364	8	more	more	ADV
cana-2991	364	9	detailed	detailed	ADJ
cana-2991	364	10	and	and	CCONJ
cana-2991	364	11	thus	thus	ADV
cana-2991	364	12	result	result	VERB
cana-2991	364	13	in	in	ADP
cana-2991	364	14	better	well	ADJ
cana-2991	364	15	classification	classification	NOUN
cana-2991	364	16	.	.	PUNCT
cana-2991	365	1	this	this	PRON
cana-2991	365	2	,	,	PUNCT
cana-2991	365	3	however	however	ADV
cana-2991	365	4	,	,	PUNCT
cana-2991	365	5	comes	come	VERB
cana-2991	365	6	at	at	ADP
cana-2991	365	7	an	an	DET
cana-2991	365	8	additional	additional	ADJ
cana-2991	365	9	cost	cost	NOUN
cana-2991	365	10	of	of	ADP
cana-2991	365	11	computational	computational	ADJ
cana-2991	365	12	complexity	complexity	NOUN
cana-2991	365	13	and	and	CCONJ
cana-2991	365	14	thus	thus	ADV
cana-2991	365	15	trade	trade	NOUN
cana-2991	365	16	-	-	PUNCT
cana-2991	365	17	offs	off	NOUN
cana-2991	365	18	need	need	VERB
cana-2991	365	19	to	to	PART
cana-2991	365	20	be	be	AUX
cana-2991	365	21	made	make	VERB
cana-2991	365	22	between	between	ADP
cana-2991	365	23	the	the	DET
cana-2991	365	24	complexity	complexity	NOUN
cana-2991	365	25	of	of	ADP
cana-2991	365	26	a	a	DET
cana-2991	365	27	model	model	NOUN
cana-2991	365	28	and	and	CCONJ
cana-2991	365	29	its	its	PRON
cana-2991	365	30	performance	performance	NOUN
cana-2991	365	31	.	.	PUNCT
cana-2991	366	1	communications	communication	NOUN
cana-2991	366	2	on	on	ADP
cana-2991	366	3	applied	apply	VERB
cana-2991	366	4	nonlinear	nonlinear	ADJ
cana-2991	366	5	analysis	analysis	NOUN
cana-2991	366	6	issn	issn	NOUN
cana-2991	366	7	:	:	PUNCT
cana-2991	366	8	1074	1074	NUM
cana-2991	366	9	-	-	PUNCT
cana-2991	366	10	133x	133x	NUM
cana-2991	366	11	vol	vol	NOUN
cana-2991	366	12	32	32	NUM
cana-2991	366	13	no	no	NOUN
cana-2991	366	14	.	.	PUNCT
cana-2991	367	1	5s	5s	NUM
cana-2991	367	2	(	(	PUNCT
cana-2991	367	3	2025	2025	NUM
cana-2991	367	4	)	)	PUNCT
cana-2991	367	5	171	171	NUM
cana-2991	367	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	367	7	3	3	X
cana-2991	367	8	.	.	PUNCT
cana-2991	367	9	scale	scale	NOUN
cana-2991	367	10	-	-	PUNCT
cana-2991	367	11	out	out	NOUN
cana-2991	367	12	and	and	CCONJ
cana-2991	367	13	distributed	distribute	VERB
cana-2991	367	14	computing	computing	NOUN
cana-2991	367	15	scalability	scalability	NOUN
cana-2991	367	16	is	be	AUX
cana-2991	367	17	one	one	NUM
cana-2991	367	18	of	of	ADP
cana-2991	367	19	the	the	DET
cana-2991	367	20	most	most	ADV
cana-2991	367	21	important	important	ADJ
cana-2991	367	22	parts	part	NOUN
cana-2991	367	23	to	to	PART
cana-2991	367	24	be	be	AUX
cana-2991	367	25	in	in	ADP
cana-2991	367	26	this	this	DET
cana-2991	367	27	method	method	NOUN
cana-2991	367	28	.	.	PUNCT
cana-2991	368	1	we	we	PRON
cana-2991	368	2	then	then	ADV
cana-2991	368	3	used	use	VERB
cana-2991	368	4	apache	apache	NOUN
cana-2991	368	5	spark	spark	NOUN
cana-2991	368	6	to	to	PART
cana-2991	368	7	test	test	VERB
cana-2991	368	8	the	the	DET
cana-2991	368	9	scalability	scalability	NOUN
cana-2991	368	10	of	of	ADP
cana-2991	368	11	the	the	DET
cana-2991	368	12	system	system	NOUN
cana-2991	368	13	,	,	PUNCT
cana-2991	368	14	distributing	distribute	VERB
cana-2991	368	15	data	datum	NOUN
cana-2991	368	16	processing	processing	NOUN
cana-2991	368	17	and	and	CCONJ
cana-2991	368	18	modeling	modeling	NOUN
cana-2991	368	19	across	across	ADP
cana-2991	368	20	multiple	multiple	ADJ
cana-2991	368	21	nodes	node	NOUN
cana-2991	368	22	.	.	PUNCT
cana-2991	369	1	a	a	DET
cana-2991	369	2	dataset	dataset	NOUN
cana-2991	369	3	of	of	ADP
cana-2991	369	4	over	over	ADP
cana-2991	369	5	1	1	NUM
cana-2991	369	6	million	million	NUM
cana-2991	369	7	news	news	NOUN
cana-2991	369	8	articles	article	NOUN
cana-2991	369	9	is	be	AUX
cana-2991	369	10	used	use	VERB
cana-2991	369	11	to	to	PART
cana-2991	369	12	test	test	VERB
cana-2991	369	13	the	the	DET
cana-2991	369	14	system	system	NOUN
cana-2991	369	15	on	on	ADP
cana-2991	369	16	a	a	DET
cana-2991	369	17	large	large	ADJ
cana-2991	369	18	scale	scale	NOUN
cana-2991	369	19	setting	setting	NOUN
cana-2991	369	20	.	.	PUNCT
cana-2991	370	1	processing	processing	NOUN
cana-2991	370	2	performance	performance	NOUN
cana-2991	370	3	and	and	CCONJ
cana-2991	370	4	training	training	NOUN
cana-2991	370	5	time	time	NOUN
cana-2991	370	6	-table	-table	ADJ
cana-2991	370	7	5	5	NUM
cana-2991	370	8	shows	show	VERB
cana-2991	370	9	how	how	SCONJ
cana-2991	370	10	long	long	ADV
cana-2991	370	11	it	it	PRON
cana-2991	370	12	takes	take	VERB
cana-2991	370	13	to	to	PART
cana-2991	370	14	process	process	VERB
cana-2991	370	15	the	the	DET
cana-2991	370	16	entire	entire	ADJ
cana-2991	370	17	dataset	dataset	NOUN
cana-2991	370	18	in	in	ADP
cana-2991	370	19	addition	addition	NOUN
cana-2991	370	20	to	to	PART
cana-2991	370	21	train	train	VERB
cana-2991	370	22	the	the	DET
cana-2991	370	23	models	model	NOUN
cana-2991	370	24	with	with	ADP
cana-2991	370	25	and	and	CCONJ
cana-2991	370	26	without	without	ADP
cana-2991	370	27	distributed	distribute	VERB
cana-2991	370	28	processing	processing	NOUN
cana-2991	370	29	.	.	PUNCT
cana-2991	371	1	task	task	NOUN
cana-2991	371	2	non	non	ADJ
cana-2991	371	3	-	-	ADJ
cana-2991	371	4	distributed	distributed	ADJ
cana-2991	371	5	time	time	NOUN
cana-2991	371	6	(	(	PUNCT
cana-2991	371	7	mins	min	NOUN
cana-2991	371	8	)	)	PUNCT
cana-2991	371	9	distributed	distribute	VERB
cana-2991	371	10	time	time	NOUN
cana-2991	371	11	(	(	PUNCT
cana-2991	371	12	mins	min	NOUN
cana-2991	371	13	)	)	PUNCT
cana-2991	371	14	speedup	speedup	NOUN
cana-2991	371	15	data	datum	NOUN
cana-2991	371	16	preprocessing	preprocesse	VERB
cana-2991	371	17	45	45	NUM
cana-2991	371	18	10	10	NUM
cana-2991	371	19	4.5x	4.5x	PROPN
cana-2991	371	20	model	model	NOUN
cana-2991	371	21	training	training	NOUN
cana-2991	371	22	(	(	PUNCT
cana-2991	371	23	bert	bert	PROPN
cana-2991	371	24	)	)	PUNCT
cana-2991	371	25	120	120	NUM
cana-2991	371	26	25	25	NUM
cana-2991	371	27	4.8x	4.8x	NOUN
cana-2991	371	28	model	model	NOUN
cana-2991	371	29	training	training	NOUN
cana-2991	371	30	(	(	PUNCT
cana-2991	371	31	word2vec	word2vec	X
cana-2991	371	32	)	)	PUNCT
cana-2991	371	33	90	90	NUM
cana-2991	371	34	20	20	NUM
cana-2991	371	35	4.5x	4.5x	NUM
cana-2991	371	36	model	model	NOUN
cana-2991	371	37	training	training	NOUN
cana-2991	371	38	(	(	PUNCT
cana-2991	371	39	random	random	ADJ
cana-2991	371	40	forest	forest	NOUN
cana-2991	371	41	)	)	PUNCT
cana-2991	371	42	75	75	NUM
cana-2991	371	43	18	18	NUM
cana-2991	371	44	4.2x	4.2x	NUM
cana-2991	371	45	table	table	NOUN
cana-2991	371	46	5	5	NUM
cana-2991	371	47	:	:	PUNCT
cana-2991	371	48	time	time	NOUN
cana-2991	371	49	comparison	comparison	NOUN
cana-2991	371	50	for	for	ADP
cana-2991	371	51	distributed	distribute	VERB
cana-2991	371	52	vs.	vs.	X
cana-2991	371	53	non	non	ADJ
cana-2991	371	54	-	-	ADJ
cana-2991	371	55	distributed	distributed	ADJ
cana-2991	371	56	processing	processing	NOUN
cana-2991	371	57	table	table	NOUN
cana-2991	371	58	5	5	NUM
cana-2991	371	59	:	:	PUNCT
cana-2991	371	60	using	use	VERB
cana-2991	371	61	distributed	distribute	VERB
cana-2991	371	62	processing	processing	NOUN
cana-2991	371	63	considerably	considerably	ADV
cana-2991	371	64	saves	save	VERB
cana-2991	371	65	time	time	NOUN
cana-2991	371	66	in	in	ADP
cana-2991	371	67	terms	term	NOUN
cana-2991	371	68	of	of	ADP
cana-2991	371	69	both	both	PRON
cana-2991	371	70	preprocessing	preprocessing	NOUN
cana-2991	371	71	and	and	CCONJ
cana-2991	371	72	model	model	NOUN
cana-2991	371	73	training	training	NOUN
cana-2991	371	74	(	(	PUNCT
cana-2991	371	75	in	in	ADP
cana-2991	371	76	hours	hour	NOUN
cana-2991	371	77	)	)	PUNCT
cana-2991	371	78	.	.	PUNCT
cana-2991	372	1	therefore	therefore	ADV
cana-2991	372	2	,	,	PUNCT
cana-2991	372	3	the	the	DET
cana-2991	372	4	proposed	propose	VERB
cana-2991	372	5	system	system	NOUN
cana-2991	372	6	is	be	AUX
cana-2991	372	7	well	well	ADV
cana-2991	372	8	-	-	PUNCT
cana-2991	372	9	suited	suit	VERB
cana-2991	372	10	for	for	ADP
cana-2991	372	11	real	real	ADJ
cana-2991	372	12	-	-	PUNCT
cana-2991	372	13	time	time	NOUN
cana-2991	372	14	applications	application	NOUN
cana-2991	372	15	involving	involve	VERB
cana-2991	372	16	large	large	ADJ
cana-2991	372	17	datasets	dataset	NOUN
cana-2991	372	18	in	in	ADP
cana-2991	372	19	order	order	NOUN
cana-2991	372	20	to	to	PART
cana-2991	372	21	process	process	VERB
cana-2991	372	22	as	as	ADV
cana-2991	372	23	quickly	quickly	ADV
cana-2991	372	24	as	as	ADP
cana-2991	372	25	possible	possible	ADJ
cana-2991	372	26	.	.	PUNCT
cana-2991	373	1	the	the	DET
cana-2991	373	2	experiments	experiment	NOUN
cana-2991	373	3	shows	show	VERB
cana-2991	373	4	that	that	SCONJ
cana-2991	373	5	having	have	VERB
cana-2991	373	6	advanced	advanced	ADJ
cana-2991	373	7	word	word	NOUN
cana-2991	373	8	embedding	embed	VERB
cana-2991	373	9	models	model	NOUN
cana-2991	373	10	such	such	ADJ
cana-2991	373	11	as	as	ADP
cana-2991	373	12	bert	bert	PROPN
cana-2991	373	13	and	and	CCONJ
cana-2991	373	14	word2vec	word2vec	X
cana-2991	373	15	working	work	VERB
cana-2991	373	16	in	in	ADP
cana-2991	373	17	conjunction	conjunction	NOUN
cana-2991	373	18	with	with	ADP
cana-2991	373	19	strong	strong	ADJ
cana-2991	373	20	classifiers	classifier	NOUN
cana-2991	373	21	like	like	ADP
cana-2991	373	22	neural	neural	ADJ
cana-2991	373	23	networks	network	NOUN
cana-2991	373	24	provide	provide	VERB
cana-2991	373	25	state	state	NOUN
cana-2991	373	26	-	-	PUNCT
cana-2991	373	27	of	of	ADP
cana-2991	373	28	-	-	PUNCT
cana-2991	373	29	the	the	DET
cana-2991	373	30	-	-	PUNCT
cana-2991	373	31	art	art	NOUN
cana-2991	373	32	results	result	NOUN
cana-2991	373	33	in	in	ADP
cana-2991	373	34	detecting	detect	VERB
cana-2991	373	35	fake	fake	ADJ
cana-2991	373	36	news	news	NOUN
cana-2991	373	37	bert	bert	NOUN
cana-2991	373	38	is	be	AUX
cana-2991	373	39	the	the	DET
cana-2991	373	40	best	good	ADJ
cana-2991	373	41	model	model	NOUN
cana-2991	373	42	for	for	ADP
cana-2991	373	43	fake	fake	ADJ
cana-2991	373	44	news	news	NOUN
cana-2991	373	45	detection	detection	NOUN
cana-2991	373	46	,	,	PUNCT
cana-2991	373	47	as	as	SCONJ
cana-2991	373	48	it	it	PRON
cana-2991	373	49	can	can	AUX
cana-2991	373	50	capture	capture	VERB
cana-2991	373	51	bidirectional	bidirectional	ADJ
cana-2991	373	52	context	context	NOUN
cana-2991	373	53	using	use	VERB
cana-2991	373	54	deep	deep	ADJ
cana-2991	373	55	learning	learning	NOUN
cana-2991	373	56	models	model	NOUN
cana-2991	373	57	.	.	PUNCT
cana-2991	374	1	by	by	ADP
cana-2991	374	2	contrast	contrast	NOUN
cana-2991	374	3	,	,	PUNCT
cana-2991	374	4	bow	bow	NOUN
cana-2991	374	5	and	and	CCONJ
cana-2991	374	6	tf	tf	PROPN
cana-2991	374	7	-	-	PUNCT
cana-2991	374	8	idf	idf	PROPN
cana-2991	374	9	are	be	AUX
cana-2991	374	10	simpler	simple	ADJ
cana-2991	374	11	inhibitory	inhibitory	ADJ
cana-2991	374	12	methods	method	NOUN
cana-2991	374	13	that	that	PRON
cana-2991	374	14	,	,	PUNCT
cana-2991	374	15	though	though	SCONJ
cana-2991	374	16	effective	effective	ADJ
cana-2991	374	17	,	,	PUNCT
cana-2991	374	18	just	just	ADV
cana-2991	374	19	can	can	AUX
cana-2991	374	20	not	not	PART
cana-2991	374	21	compete	compete	VERB
cana-2991	374	22	with	with	ADP
cana-2991	374	23	more	more	ADV
cana-2991	374	24	comprehensive	comprehensive	ADJ
cana-2991	374	25	embedding	embed	VERB
cana-2991	374	26	procedures	procedure	NOUN
cana-2991	374	27	in	in	ADP
cana-2991	374	28	terms	term	NOUN
cana-2991	374	29	of	of	ADP
cana-2991	374	30	awareness	awareness	NOUN
cana-2991	374	31	of	of	ADP
cana-2991	374	32	context	context	NOUN
cana-2991	374	33	.	.	PUNCT
cana-2991	375	1	the	the	DET
cana-2991	375	2	distributed	distribute	VERB
cana-2991	375	3	processing	processing	NOUN
cana-2991	375	4	also	also	ADV
cana-2991	375	5	allows	allow	VERB
cana-2991	375	6	for	for	ADP
cana-2991	375	7	a	a	DET
cana-2991	375	8	very	very	ADV
cana-2991	375	9	horizontal	horizontal	ADJ
cana-2991	375	10	scaling	scaling	NOUN
cana-2991	375	11	of	of	ADP
cana-2991	375	12	the	the	DET
cana-2991	375	13	system	system	NOUN
cana-2991	375	14	,	,	PUNCT
cana-2991	375	15	which	which	PRON
cana-2991	375	16	is	be	AUX
cana-2991	375	17	important	important	ADJ
cana-2991	375	18	if	if	SCONJ
cana-2991	375	19	we	we	PRON
cana-2991	375	20	want	want	VERB
cana-2991	375	21	to	to	PART
cana-2991	375	22	handle	handle	VERB
cana-2991	375	23	big	big	ADJ
cana-2991	375	24	datasets	dataset	NOUN
cana-2991	375	25	in	in	ADP
cana-2991	375	26	real	real	ADJ
cana-2991	375	27	time	time	NOUN
cana-2991	375	28	such	such	ADJ
cana-2991	375	29	as	as	ADP
cana-2991	375	30	social	social	ADJ
cana-2991	375	31	media	medium	NOUN
cana-2991	375	32	,	,	PUNCT
cana-2991	375	33	or	or	CCONJ
cana-2991	375	34	news	news	NOUN
cana-2991	375	35	outlets	outlet	NOUN
cana-2991	375	36	online	online	ADV
cana-2991	375	37	.	.	PUNCT
cana-2991	376	1	in	in	ADP
cana-2991	376	2	future	future	NOUN
cana-2991	376	3	we	we	PRON
cana-2991	376	4	plan	plan	VERB
cana-2991	376	5	to	to	PART
cana-2991	376	6	optimize	optimize	VERB
cana-2991	376	7	the	the	DET
cana-2991	376	8	system	system	NOUN
cana-2991	376	9	further	far	ADV
cana-2991	376	10	and	and	CCONJ
cana-2991	376	11	test	test	VERB
cana-2991	376	12	other	other	ADJ
cana-2991	376	13	embeddings	embedding	NOUN
cana-2991	376	14	like	like	ADP
cana-2991	376	15	roberta	roberta	PROPN
cana-2991	376	16	and	and	CCONJ
cana-2991	376	17	gpt	gpt	NOUN
cana-2991	376	18	for	for	ADP
cana-2991	376	19	better	well	ADJ
cana-2991	376	20	performance	performance	NOUN
cana-2991	376	21	in	in	ADP
cana-2991	376	22	fake	fake	ADJ
cana-2991	376	23	news	news	NOUN
cana-2991	376	24	detection	detection	NOUN
cana-2991	376	25	.	.	PUNCT
cana-2991	377	1	the	the	DET
cana-2991	377	2	fake	fake	ADJ
cana-2991	377	3	news	news	NOUN
cana-2991	377	4	detection	detection	NOUN
cana-2991	377	5	system	system	NOUN
cana-2991	377	6	would	would	AUX
cana-2991	377	7	give	give	VERB
cana-2991	377	8	significant	significant	ADJ
cana-2991	377	9	accuracy	accuracy	NOUN
cana-2991	377	10	,	,	PUNCT
cana-2991	377	11	precision	precision	NOUN
cana-2991	377	12	,	,	PUNCT
cana-2991	377	13	recall	recall	NOUN
cana-2991	377	14	,	,	PUNCT
cana-2991	377	15	and	and	CCONJ
cana-2991	377	16	f1	f1	NOUN
cana-2991	377	17	-	-	PUNCT
cana-2991	377	18	scores	score	NOUN
cana-2991	377	19	by	by	ADP
cana-2991	377	20	using	use	VERB
cana-2991	377	21	state	state	NOUN
cana-2991	377	22	-	-	PUNCT
cana-2991	377	23	of	of	ADP
cana-2991	377	24	-	-	PUNCT
cana-2991	377	25	the	the	DET
cana-2991	377	26	-	-	PUNCT
cana-2991	377	27	art	art	NOUN
cana-2991	377	28	word	word	NOUN
cana-2991	377	29	embeddings	embedding	NOUN
cana-2991	377	30	and	and	CCONJ
cana-2991	377	31	machine	machine	NOUN
cana-2991	377	32	learning	learning	NOUN
cana-2991	377	33	models	model	NOUN
cana-2991	377	34	together	together	ADV
cana-2991	377	35	.	.	PUNCT
cana-2991	378	1	results	result	NOUN
cana-2991	378	2	affirm	affirm	VERB
cana-2991	378	3	the	the	DET
cana-2991	378	4	necessity	necessity	NOUN
cana-2991	378	5	of	of	ADP
cana-2991	378	6	selecting	select	VERB
cana-2991	378	7	proper	proper	ADJ
cana-2991	378	8	methods	method	NOUN
cana-2991	378	9	to	to	PART
cana-2991	378	10	achieve	achieve	VERB
cana-2991	378	11	a	a	DET
cana-2991	378	12	desirable	desirable	ADJ
cana-2991	378	13	result	result	NOUN
cana-2991	378	14	both	both	CCONJ
cana-2991	378	15	at	at	ADP
cana-2991	378	16	embedding	embed	VERB
cana-2991	378	17	layer	layer	NOUN
cana-2991	378	18	and	and	CCONJ
cana-2991	378	19	classifier	classifier	NOUN
cana-2991	378	20	level	level	NOUN
cana-2991	378	21	for	for	ADP
cana-2991	378	22	each	each	DET
cana-2991	378	23	task	task	NOUN
cana-2991	378	24	and	and	CCONJ
cana-2991	378	25	data	datum	NOUN
cana-2991	378	26	size	size	NOUN
cana-2991	378	27	.	.	PUNCT
cana-2991	379	1	author	author	NOUN
cana-2991	379	2	:	:	PUNCT
cana-2991	379	3	guang	guang	PROPN
cana-2991	379	4	qiu	qiu	PROPN
cana-2991	379	5	,	,	PUNCT
cana-2991	379	6	contact	contact	NOUN
cana-2991	379	7	information	information	NOUN
cana-2991	379	8	the	the	DET
cana-2991	379	9	combined	combined	ADJ
cana-2991	379	10	use	use	NOUN
cana-2991	379	11	of	of	ADP
cana-2991	379	12	distributed	distribute	VERB
cana-2991	379	13	processing	processing	NOUN
cana-2991	379	14	frameworks	framework	NOUN
cana-2991	379	15	ensures	ensure	VERB
cana-2991	379	16	scalability	scalability	NOUN
cana-2991	379	17	as	as	ADV
cana-2991	379	18	well	well	ADV
cana-2991	379	19	as	as	ADP
cana-2991	379	20	being	be	AUX
cana-2991	379	21	applicable	applicable	ADJ
cana-2991	379	22	to	to	ADP
cana-2991	379	23	large	large	ADJ
cana-2991	379	24	-	-	PUNCT
cana-2991	379	25	scale	scale	NOUN
cana-2991	379	26	data	data	NOUN
cana-2991	379	27	streams	stream	NOUN
cana-2991	379	28	provided	provide	VERB
cana-2991	379	29	by	by	ADP
cana-2991	379	30	real	real	ADJ
cana-2991	379	31	-	-	PUNCT
cana-2991	379	32	world	world	NOUN
cana-2991	379	33	scenarios	scenario	NOUN
cana-2991	379	34	,	,	PUNCT
cana-2991	379	35	making	make	VERB
cana-2991	379	36	it	it	PRON
cana-2991	379	37	an	an	DET
cana-2991	379	38	effective	effective	ADJ
cana-2991	379	39	tool	tool	NOUN
cana-2991	379	40	to	to	PART
cana-2991	379	41	tackle	tackle	VERB
cana-2991	379	42	misinformation	misinformation	NOUN
cana-2991	379	43	in	in	ADP
cana-2991	379	44	the	the	DET
cana-2991	379	45	digital	digital	ADJ
cana-2991	379	46	age	age	NOUN
cana-2991	379	47	.	.	PUNCT
cana-2991	380	1	5	5	X
cana-2991	380	2	.	.	X
cana-2991	380	3	conclusion	conclusion	NOUN
cana-2991	380	4	the	the	DET
cana-2991	380	5	world	world	NOUN
cana-2991	380	6	we	we	PRON
cana-2991	380	7	live	live	VERB
cana-2991	380	8	in	in	ADP
cana-2991	380	9	today	today	NOUN
cana-2991	380	10	has	have	VERB
cana-2991	380	11	plenty	plenty	NOUN
cana-2991	380	12	of	of	ADP
cana-2991	380	13	examples	example	NOUN
cana-2991	380	14	of	of	ADP
cana-2991	380	15	fake	fake	ADJ
cana-2991	380	16	news	news	NOUN
cana-2991	380	17	taking	take	VERB
cana-2991	380	18	root	root	NOUN
cana-2991	380	19	almost	almost	ADV
cana-2991	380	20	as	as	SCONJ
cana-2991	380	21	though	though	SCONJ
cana-2991	380	22	the	the	DET
cana-2991	380	23	floodgates	floodgate	NOUN
cana-2991	380	24	were	be	AUX
cana-2991	380	25	opened	open	VERB
cana-2991	380	26	once	once	ADV
cana-2991	380	27	social	social	ADJ
cana-2991	380	28	media	medium	NOUN
cana-2991	380	29	and	and	CCONJ
cana-2991	380	30	online	online	ADJ
cana-2991	380	31	platforms	platform	NOUN
cana-2991	380	32	started	started	AUX
cana-2991	380	33	fundamentally	fundamentally	ADV
cana-2991	380	34	shifting	shift	VERB
cana-2991	380	35	our	our	PRON
cana-2991	380	36	understanding	understanding	NOUN
cana-2991	380	37	of	of	ADP
cana-2991	380	38	information	information	NOUN
cana-2991	380	39	integrity	integrity	NOUN
cana-2991	380	40	.	.	PUNCT
cana-2991	381	1	contrasting	contrast	VERB
cana-2991	381	2	the	the	DET
cana-2991	381	3	elusive	elusive	ADJ
cana-2991	381	4	nature	nature	NOUN
cana-2991	381	5	of	of	ADP
cana-2991	381	6	fake	fake	ADJ
cana-2991	381	7	news	news	NOUN
cana-2991	381	8	,	,	PUNCT
cana-2991	381	9	therefore	therefore	ADV
cana-2991	381	10	,	,	PUNCT
cana-2991	381	11	recognizing	recognize	VERB
cana-2991	381	12	and	and	CCONJ
cana-2991	381	13	combating	combat	VERB
cana-2991	381	14	fake	fake	ADJ
cana-2991	381	15	news	news	NOUN
cana-2991	381	16	is	be	AUX
cana-2991	381	17	an	an	DET
cana-2991	381	18	important	important	ADJ
cana-2991	381	19	factor	factor	NOUN
cana-2991	381	20	that	that	PRON
cana-2991	381	21	can	can	AUX
cana-2991	381	22	not	not	PART
cana-2991	381	23	only	only	ADV
cana-2991	381	24	save	save	VERB
cana-2991	381	25	us	we	PRON
cana-2991	381	26	faith	faith	NOUN
cana-2991	381	27	in	in	ADP
cana-2991	381	28	media	medium	NOUN
cana-2991	381	29	communications	communication	NOUN
cana-2991	381	30	on	on	ADP
cana-2991	381	31	applied	apply	VERB
cana-2991	381	32	nonlinear	nonlinear	ADJ
cana-2991	381	33	analysis	analysis	NOUN
cana-2991	381	34	issn	issn	NOUN
cana-2991	381	35	:	:	PUNCT
cana-2991	381	36	1074	1074	NUM
cana-2991	381	37	-	-	PUNCT
cana-2991	381	38	133x	133x	NUM
cana-2991	381	39	vol	vol	NOUN
cana-2991	381	40	32	32	NUM
cana-2991	381	41	no	no	NOUN
cana-2991	381	42	.	.	PUNCT
cana-2991	382	1	5s	5s	NUM
cana-2991	382	2	(	(	PUNCT
cana-2991	382	3	2025	2025	NUM
cana-2991	382	4	)	)	PUNCT
cana-2991	382	5	172	172	NUM
cana-2991	382	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	382	7	but	but	CCONJ
cana-2991	382	8	also	also	ADV
cana-2991	382	9	spare	spare	VERB
cana-2991	382	10	us	we	PRON
cana-2991	382	11	social	social	ADJ
cana-2991	382	12	,	,	PUNCT
cana-2991	382	13	political	political	ADJ
cana-2991	382	14	,	,	PUNCT
cana-2991	382	15	and	and	CCONJ
cana-2991	382	16	economic	economic	ADJ
cana-2991	382	17	effects	effect	NOUN
cana-2991	382	18	of	of	ADP
cana-2991	382	19	false	false	ADJ
cana-2991	382	20	information	information	NOUN
cana-2991	382	21	dissemination	dissemination	NOUN
cana-2991	382	22	.	.	PUNCT
cana-2991	383	1	by	by	ADP
cana-2991	383	2	developing	develop	VERB
cana-2991	383	3	methodology	methodology	NOUN
cana-2991	383	4	for	for	ADP
cana-2991	383	5	detecting	detect	VERB
cana-2991	383	6	fake	fake	ADJ
cana-2991	383	7	news	news	NOUN
cana-2991	383	8	using	use	VERB
cana-2991	383	9	modern	modern	ADJ
cana-2991	383	10	machine	machine	NOUN
cana-2991	383	11	learning	learning	NOUN
cana-2991	383	12	models	model	NOUN
cana-2991	383	13	and	and	CCONJ
cana-2991	383	14	natural	natural	ADJ
cana-2991	383	15	language	language	NOUN
cana-2991	383	16	processing	processing	NOUN
cana-2991	383	17	(	(	PUNCT
cana-2991	383	18	nlp	nlp	NOUN
cana-2991	383	19	)	)	PUNCT
cana-2991	383	20	techniques	technique	NOUN
cana-2991	383	21	,	,	PUNCT
cana-2991	383	22	this	this	DET
cana-2991	383	23	paper	paper	NOUN
cana-2991	383	24	proposes	propose	VERB
cana-2991	383	25	a	a	DET
cana-2991	383	26	wide	wide	ADV
cana-2991	383	27	-	-	PUNCT
cana-2991	383	28	ranging	range	VERB
cana-2991	383	29	,	,	PUNCT
cana-2991	383	30	autonomic	autonomic	ADJ
cana-2991	383	31	approach	approach	NOUN
cana-2991	383	32	to	to	PART
cana-2991	383	33	improve	improve	VERB
cana-2991	383	34	scalability	scalability	NOUN
cana-2991	383	35	.	.	PUNCT
cana-2991	384	1	by	by	ADP
cana-2991	384	2	combining	combine	VERB
cana-2991	384	3	a	a	DET
cana-2991	384	4	set	set	NOUN
cana-2991	384	5	of	of	ADP
cana-2991	384	6	embedding	embed	VERB
cana-2991	384	7	models	model	NOUN
cana-2991	384	8	—	—	PUNCT
cana-2991	384	9	bag	bag	NOUN
cana-2991	384	10	of	of	ADP
cana-2991	384	11	words	word	NOUN
cana-2991	384	12	(	(	PUNCT
cana-2991	384	13	bow	bow	NOUN
cana-2991	384	14	)	)	PUNCT
cana-2991	384	15	,	,	PUNCT
cana-2991	384	16	term	term	NOUN
cana-2991	384	17	frequency	frequency	NOUN
cana-2991	384	18	-	-	PUNCT
cana-2991	384	19	inverse	inverse	NOUN
cana-2991	384	20	document	document	NOUN
cana-2991	384	21	frequency	frequency	NOUN
cana-2991	384	22	(	(	PUNCT
cana-2991	384	23	tf	tf	PROPN
cana-2991	384	24	-	-	PUNCT
cana-2991	384	25	idf	idf	NOUN
cana-2991	384	26	)	)	PUNCT
cana-2991	384	27	,	,	PUNCT
cana-2991	384	28	word2vec	word2vec	X
cana-2991	384	29	,	,	PUNCT
cana-2991	384	30	and	and	CCONJ
cana-2991	384	31	bidirectional	bidirectional	ADJ
cana-2991	384	32	encoder	encoder	NOUN
cana-2991	384	33	representations	representation	VERB
cana-2991	384	34	from	from	ADP
cana-2991	384	35	transformers	transformer	NOUN
cana-2991	384	36	(	(	PUNCT
cana-2991	384	37	bert	bert	PROPN
cana-2991	384	38	)	)	PUNCT
cana-2991	384	39	and	and	CCONJ
cana-2991	384	40	machine	machine	NOUN
cana-2991	384	41	learning	learn	VERB
cana-2991	384	42	classifiers	classifier	NOUN
cana-2991	384	43	including	include	VERB
cana-2991	384	44	logistic	logistic	ADJ
cana-2991	384	45	regression	regression	NOUN
cana-2991	384	46	,	,	PUNCT
cana-2991	384	47	random	random	ADJ
cana-2991	384	48	forests	forest	NOUN
cana-2991	384	49	,	,	PUNCT
cana-2991	384	50	and	and	CCONJ
cana-2991	384	51	neural	neural	ADJ
cana-2991	384	52	networks	network	NOUN
cana-2991	384	53	,	,	PUNCT
cana-2991	384	54	the	the	DET
cana-2991	384	55	system	system	NOUN
cana-2991	384	56	has	have	AUX
cana-2991	384	57	managed	manage	VERB
cana-2991	384	58	to	to	PART
cana-2991	384	59	achieve	achieve	VERB
cana-2991	384	60	high	high	ADJ
cana-2991	384	61	throughputs	throughput	NOUN
cana-2991	384	62	in	in	ADP
cana-2991	384	63	detecting	detect	VERB
cana-2991	384	64	fake	fake	ADJ
cana-2991	384	65	news	news	NOUN
cana-2991	384	66	across	across	ADP
cana-2991	384	67	large	large	ADJ
cana-2991	384	68	-	-	PUNCT
cana-2991	384	69	scale	scale	NOUN
cana-2991	384	70	datasets	dataset	NOUN
cana-2991	384	71	.	.	PUNCT
cana-2991	385	1	so	so	ADV
cana-2991	385	2	far	far	ADV
cana-2991	385	3	:	:	PUNCT
cana-2991	385	4	the	the	DET
cana-2991	385	5	overall	overall	ADJ
cana-2991	385	6	aim	aim	NOUN
cana-2991	385	7	of	of	ADP
cana-2991	385	8	this	this	DET
cana-2991	385	9	work	work	NOUN
cana-2991	385	10	is	be	AUX
cana-2991	385	11	to	to	PART
cana-2991	385	12	create	create	VERB
cana-2991	385	13	a	a	DET
cana-2991	385	14	fake	fake	ADJ
cana-2991	385	15	news	news	NOUN
cana-2991	385	16	detection	detection	NOUN
cana-2991	385	17	algorithm	algorithm	NOUN
cana-2991	385	18	that	that	PRON
cana-2991	385	19	will	will	AUX
cana-2991	385	20	not	not	PART
cana-2991	385	21	only	only	ADV
cana-2991	385	22	provide	provide	VERB
cana-2991	385	23	accurate	accurate	ADJ
cana-2991	385	24	results	result	NOUN
cana-2991	385	25	while	while	SCONJ
cana-2991	385	26	processing	process	VERB
cana-2991	385	27	thousands	thousand	NOUN
cana-2991	385	28	and	and	CCONJ
cana-2991	385	29	millions	million	NOUN
cana-2991	385	30	of	of	ADP
cana-2991	385	31	news	news	NOUN
cana-2991	385	32	articles	article	NOUN
cana-2991	385	33	as	as	ADP
cana-2991	385	34	well	well	ADV
cana-2991	385	35	social	social	ADJ
cana-2991	385	36	media	medium	NOUN
cana-2991	385	37	posts	post	NOUN
cana-2991	385	38	which	which	PRON
cana-2991	385	39	are	be	AUX
cana-2991	385	40	generated	generate	VERB
cana-2991	385	41	every	every	DET
cana-2991	385	42	day	day	NOUN
cana-2991	385	43	.	.	PUNCT
cana-2991	386	1	we	we	PRON
cana-2991	386	2	tried	try	VERB
cana-2991	386	3	to	to	PART
cana-2991	386	4	balance	balance	VERB
cana-2991	386	5	computational	computational	ADJ
cana-2991	386	6	efficiency	efficiency	NOUN
cana-2991	386	7	and	and	CCONJ
cana-2991	386	8	model	model	NOUN
cana-2991	386	9	complexity	complexity	NOUN
cana-2991	386	10	,	,	PUNCT
cana-2991	386	11	so	so	SCONJ
cana-2991	386	12	that	that	SCONJ
cana-2991	386	13	the	the	DET
cana-2991	386	14	system	system	NOUN
cana-2991	386	15	is	be	AUX
cana-2991	386	16	suitable	suitable	ADJ
cana-2991	386	17	for	for	ADP
cana-2991	386	18	real	real	ADJ
cana-2991	386	19	-	-	PUNCT
cana-2991	386	20	time	time	NOUN
cana-2991	386	21	fake	fake	ADJ
cana-2991	386	22	news	news	NOUN
cana-2991	386	23	detection	detection	NOUN
cana-2991	386	24	in	in	ADP
cana-2991	386	25	practice	practice	NOUN
cana-2991	386	26	such	such	ADJ
cana-2991	386	27	as	as	ADP
cana-2991	386	28	monitoring	monitor	VERB
cana-2991	386	29	social	social	ADJ
cana-2991	386	30	media	medium	NOUN
cana-2991	386	31	platforms	platform	NOUN
cana-2991	386	32	or	or	CCONJ
cana-2991	386	33	aggregating	aggregate	VERB
cana-2991	386	34	news	news	NOUN
cana-2991	386	35	articles	article	NOUN
cana-2991	386	36	with	with	ADP
cana-2991	386	37	fact	fact	NOUN
cana-2991	386	38	-	-	PUNCT
cana-2991	386	39	checking	check	VERB
cana-2991	386	40	organizations	organization	NOUN
cana-2991	386	41	.	.	PUNCT
cana-2991	387	1	experiments	experiment	NOUN
cana-2991	387	2	on	on	ADP
cana-2991	387	3	politifact	politifact	PROPN
cana-2991	387	4	and	and	CCONJ
cana-2991	387	5	liar	liar	NOUN
cana-2991	387	6	demonstrated	demonstrate	VERB
cana-2991	387	7	the	the	DET
cana-2991	387	8	effectiveness	effectiveness	NOUN
cana-2991	387	9	and	and	CCONJ
cana-2991	387	10	scalability	scalability	NOUN
cana-2991	387	11	of	of	ADP
cana-2991	387	12	the	the	DET
cana-2991	387	13	system	system	NOUN
cana-2991	387	14	,	,	PUNCT
cana-2991	387	15	which	which	PRON
cana-2991	387	16	makes	make	VERB
cana-2991	387	17	it	it	PRON
cana-2991	387	18	suitable	suitable	ADJ
cana-2991	387	19	for	for	ADP
cana-2991	387	20	deployment	deployment	NOUN
cana-2991	387	21	in	in	ADP
cana-2991	387	22	large	large	ADJ
cana-2991	387	23	-	-	PUNCT
cana-2991	387	24	scale	scale	NOUN
cana-2991	387	25	environments	environment	NOUN
cana-2991	387	26	.	.	PUNCT
cana-2991	388	1	key	key	ADJ
cana-2991	388	2	findings	finding	NOUN
cana-2991	388	3	the	the	DET
cana-2991	388	4	most	most	ADV
cana-2991	388	5	important	important	ADJ
cana-2991	388	6	and	and	CCONJ
cana-2991	388	7	informative	informative	ADJ
cana-2991	388	8	result	result	NOUN
cana-2991	388	9	of	of	ADP
cana-2991	388	10	this	this	DET
cana-2991	388	11	study	study	NOUN
cana-2991	388	12	is	be	AUX
cana-2991	388	13	the	the	DET
cana-2991	388	14	demonstrated	demonstrate	VERB
cana-2991	388	15	significantly	significantly	ADV
cana-2991	388	16	improved	improve	VERB
cana-2991	388	17	benefit	benefit	NOUN
cana-2991	388	18	from	from	ADP
cana-2991	388	19	employing	employ	VERB
cana-2991	388	20	powerful	powerful	ADJ
cana-2991	388	21	word	word	NOUN
cana-2991	388	22	embedding	embed	VERB
cana-2991	388	23	techniques	technique	NOUN
cana-2991	388	24	,	,	PUNCT
cana-2991	388	25	such	such	ADJ
cana-2991	388	26	as	as	ADP
cana-2991	388	27	bert	bert	PROPN
cana-2991	388	28	,	,	PUNCT
cana-2991	388	29	compared	compare	VERB
cana-2991	388	30	to	to	ADP
cana-2991	388	31	traditional	traditional	ADJ
cana-2991	388	32	approaches	approach	NOUN
cana-2991	388	33	like	like	ADP
cana-2991	388	34	bow	bow	NOUN
cana-2991	388	35	and	and	CCONJ
cana-2991	388	36	tf	tf	PROPN
cana-2991	388	37	-	-	PUNCT
cana-2991	388	38	idf	idf	PROPN
cana-2991	388	39	.	.	PUNCT
cana-2991	389	1	due	due	ADP
cana-2991	389	2	to	to	ADP
cana-2991	389	3	bert	bert	PROPN
cana-2991	389	4	’s	’s	PART
cana-2991	389	5	nature	nature	NOUN
cana-2991	389	6	,	,	PUNCT
cana-2991	389	7	according	accord	VERB
cana-2991	389	8	to	to	ADP
cana-2991	389	9	this	this	DET
cana-2991	389	10	paper	paper	NOUN
cana-2991	389	11	,	,	PUNCT
cana-2991	389	12	bert	bert	PROPN
cana-2991	389	13	has	have	VERB
cana-2991	389	14	a	a	DET
cana-2991	389	15	great	great	ADJ
cana-2991	389	16	capacity	capacity	NOUN
cana-2991	389	17	of	of	ADP
cana-2991	389	18	capturing	capture	VERB
cana-2991	389	19	the	the	DET
cana-2991	389	20	bidirectional	bidirectional	ADJ
cana-2991	389	21	context	context	NOUN
cana-2991	389	22	of	of	ADP
cana-2991	389	23	input	input	NOUN
cana-2991	389	24	words	word	NOUN
cana-2991	389	25	throughout	throughout	ADP
cana-2991	389	26	a	a	DET
cana-2991	389	27	sentence	sentence	NOUN
cana-2991	389	28	so	so	SCONJ
cana-2991	389	29	that	that	SCONJ
cana-2991	389	30	it	it	PRON
cana-2991	389	31	can	can	AUX
cana-2991	389	32	possibly	possibly	ADV
cana-2991	389	33	yield	yield	VERB
cana-2991	389	34	both	both	CCONJ
cana-2991	389	35	comprehensive	comprehensive	ADJ
cana-2991	389	36	and	and	CCONJ
cana-2991	389	37	more	more	ADV
cana-2991	389	38	intertwined	intertwine	VERB
cana-2991	389	39	word	word	NOUN
cana-2991	389	40	embeddings	embedding	NOUN
cana-2991	389	41	that	that	PRON
cana-2991	389	42	could	could	AUX
cana-2991	389	43	approximate	approximate	VERB
cana-2991	389	44	its	its	PRON
cana-2991	389	45	semantic	semantic	ADJ
cana-2991	389	46	meaning	meaning	NOUN
cana-2991	389	47	.	.	PUNCT
cana-2991	390	1	this	this	PRON
cana-2991	390	2	is	be	AUX
cana-2991	390	3	the	the	DET
cana-2991	390	4	key	key	ADJ
cana-2991	390	5	feature	feature	NOUN
cana-2991	390	6	for	for	ADP
cana-2991	390	7	detecting	detect	VERB
cana-2991	390	8	fake	fake	ADJ
cana-2991	390	9	news	news	NOUN
cana-2991	390	10	since	since	SCONJ
cana-2991	390	11	many	many	ADJ
cana-2991	390	12	times	time	NOUN
cana-2991	390	13	bogus	bogus	ADJ
cana-2991	390	14	news	news	NOUN
cana-2991	390	15	stories	story	NOUN
cana-2991	390	16	use	use	VERB
cana-2991	390	17	minor	minor	ADJ
cana-2991	390	18	lingual	lingual	ADJ
cana-2991	390	19	changes	change	NOUN
cana-2991	390	20	or	or	CCONJ
cana-2991	390	21	leave	leave	VERB
cana-2991	390	22	out	out	ADP
cana-2991	390	23	important	important	ADJ
cana-2991	390	24	information	information	NOUN
cana-2991	390	25	to	to	PART
cana-2991	390	26	fool	fool	VERB
cana-2991	390	27	people	people	NOUN
cana-2991	390	28	.	.	PUNCT
cana-2991	391	1	bert	bert	PROPN
cana-2991	391	2	,	,	PUNCT
cana-2991	391	3	given	give	VERB
cana-2991	391	4	that	that	SCONJ
cana-2991	391	5	it	it	PRON
cana-2991	391	6	looks	look	VERB
cana-2991	391	7	at	at	ADP
cana-2991	391	8	the	the	DET
cana-2991	391	9	contextual	contextual	ADJ
cana-2991	391	10	information	information	NOUN
cana-2991	391	11	around	around	ADP
cana-2991	391	12	each	each	DET
cana-2991	391	13	word	word	NOUN
cana-2991	391	14	,	,	PUNCT
cana-2991	391	15	is	be	AUX
cana-2991	391	16	much	much	ADV
cana-2991	391	17	better	well	ADJ
cana-2991	391	18	than	than	ADP
cana-2991	391	19	models	model	NOUN
cana-2991	391	20	which	which	PRON
cana-2991	391	21	treat	treat	VERB
cana-2991	391	22	words	word	NOUN
cana-2991	391	23	as	as	ADP
cana-2991	391	24	independent	independent	ADJ
cana-2991	391	25	units	unit	NOUN
cana-2991	391	26	to	to	PART
cana-2991	391	27	pick	pick	VERB
cana-2991	391	28	up	up	ADP
cana-2991	391	29	such	such	ADJ
cana-2991	391	30	manipulations	manipulation	NOUN
cana-2991	391	31	.	.	PUNCT
cana-2991	392	1	both	both	CCONJ
cana-2991	392	2	our	our	PRON
cana-2991	392	3	bert	bert	NOUN
cana-2991	392	4	-	-	PUNCT
cana-2991	392	5	based	base	VERB
cana-2991	392	6	and	and	CCONJ
cana-2991	392	7	non	non	ADJ
cana-2991	392	8	-	-	ADJ
cana-2991	392	9	bert	bert	ADJ
cana-2991	392	10	embedding	embed	VERB
cana-2991	392	11	models	model	NOUN
cana-2991	392	12	achieved	achieve	VERB
cana-2991	392	13	better	well	ADJ
cana-2991	392	14	performance	performance	NOUN
cana-2991	392	15	than	than	ADP
cana-2991	392	16	the	the	DET
cana-2991	392	17	stateof	stateof	ADJ
cana-2991	392	18	-	-	PUNCT
cana-2991	392	19	the	the	DET
cana-2991	392	20	-	-	PUNCT
cana-2991	392	21	art	art	NOUN
cana-2991	392	22	baselines	baseline	NOUN
cana-2991	392	23	modal	modal	NOUN
cana-2991	392	24	,	,	PUNCT
cana-2991	392	25	tydi	tydi	VERB
cana-2991	392	26	craft	craft	NOUN
cana-2991	392	27	,	,	PUNCT
cana-2991	392	28	xlm	xlm	PROPN
cana-2991	392	29	-	-	PUNCT
cana-2991	392	30	roberta	roberta	PROPN
cana-2991	392	31	across	across	ADP
cana-2991	392	32	all	all	DET
cana-2991	392	33	three	three	NUM
cana-2991	392	34	classifiers	classifier	NOUN
cana-2991	392	35	but	but	CCONJ
cana-2991	392	36	always	always	ADV
cana-2991	392	37	underperforming	underperform	VERB
cana-2991	392	38	bert	bert	NOUN
cana-2991	392	39	.	.	PUNCT
cana-2991	393	1	the	the	DET
cana-2991	393	2	performance	performance	NOUN
cana-2991	393	3	of	of	ADP
cana-2991	393	4	the	the	DET
cana-2991	393	5	best	good	ADJ
cana-2991	393	6	model	model	NOUN
cana-2991	393	7	,	,	PUNCT
cana-2991	393	8	bert	bert	PROPN
cana-2991	393	9	with	with	ADP
cana-2991	393	10	a	a	DET
cana-2991	393	11	neural	neural	ADJ
cana-2991	393	12	network	network	NOUN
cana-2991	393	13	,	,	PUNCT
cana-2991	393	14	obtained	obtain	VERB
cana-2991	393	15	an	an	DET
cana-2991	393	16	accuracy	accuracy	NOUN
cana-2991	393	17	over	over	ADP
cana-2991	393	18	92	92	NUM
cana-2991	393	19	%	%	NOUN
cana-2991	393	20	reliable	reliable	ADJ
cana-2991	393	21	enough	enough	ADV
cana-2991	393	22	to	to	PART
cana-2991	393	23	be	be	AUX
cana-2991	393	24	considered	consider	VERB
cana-2991	393	25	as	as	ADP
cana-2991	393	26	a	a	DET
cana-2991	393	27	solution	solution	NOUN
cana-2991	393	28	for	for	ADP
cana-2991	393	29	fake	fake	ADJ
cana-2991	393	30	news	news	NOUN
cana-2991	393	31	detection	detection	NOUN
cana-2991	393	32	tasks	task	NOUN
cana-2991	393	33	.	.	PUNCT
cana-2991	394	1	word2vec	word2vec	PRON
cana-2991	394	2	did	do	VERB
cana-2991	394	3	alright	alright	ADV
cana-2991	394	4	,	,	PUNCT
cana-2991	394	5	especially	especially	ADV
cana-2991	394	6	with	with	ADP
cana-2991	394	7	random	random	ADJ
cana-2991	394	8	forests	forest	NOUN
cana-2991	394	9	and	and	CCONJ
cana-2991	394	10	logistic	logistic	ADJ
cana-2991	394	11	regression	regression	NOUN
cana-2991	394	12	,	,	PUNCT
cana-2991	394	13	but	but	CCONJ
cana-2991	394	14	the	the	DET
cana-2991	394	15	numbers	number	NOUN
cana-2991	394	16	still	still	ADV
cana-2991	394	17	show	show	VERB
cana-2991	394	18	that	that	SCONJ
cana-2991	394	19	it	it	PRON
cana-2991	394	20	falls	fall	VERB
cana-2991	394	21	short	short	ADV
cana-2991	394	22	of	of	ADP
cana-2991	394	23	bert	bert	PROPN
cana-2991	394	24	in	in	ADP
cana-2991	394	25	both	both	DET
cana-2991	394	26	accuracy	accuracy	NOUN
cana-2991	394	27	and	and	CCONJ
cana-2991	394	28	recall	recall	NOUN
cana-2991	394	29	this	this	PRON
cana-2991	394	30	indicates	indicate	VERB
cana-2991	394	31	word2vec	word2vec	PRON
cana-2991	394	32	is	be	AUX
cana-2991	394	33	good	good	ADJ
cana-2991	394	34	at	at	ADP
cana-2991	394	35	capturing	capture	VERB
cana-2991	394	36	meaning	mean	VERB
cana-2991	394	37	relationships	relationship	NOUN
cana-2991	394	38	among	among	ADP
cana-2991	394	39	words	word	NOUN
cana-2991	394	40	,	,	PUNCT
cana-2991	394	41	but	but	CCONJ
cana-2991	394	42	it	it	PRON
cana-2991	394	43	captures	capture	VERB
cana-2991	394	44	less	less	ADJ
cana-2991	394	45	context	context	NOUN
cana-2991	394	46	compared	compare	VERB
cana-2991	394	47	with	with	ADP
cana-2991	394	48	more	more	ADV
cana-2991	394	49	complicated	complicated	ADJ
cana-2991	394	50	models	model	NOUN
cana-2991	394	51	like	like	ADP
cana-2991	394	52	bert	bert	PROPN
cana-2991	394	53	.	.	PUNCT
cana-2991	395	1	they	they	PRON
cana-2991	395	2	also	also	ADV
cana-2991	395	3	found	find	VERB
cana-2991	395	4	that	that	PRON
cana-2991	395	5	bow	bow	NOUN
cana-2991	395	6	and	and	CCONJ
cana-2991	395	7	tf	tf	PROPN
cana-2991	395	8	-	-	PUNCT
cana-2991	395	9	idf	idf	PROPN
cana-2991	395	10	,	,	PUNCT
cana-2991	395	11	while	while	SCONJ
cana-2991	395	12	effective	effective	ADJ
cana-2991	395	13	in	in	ADP
cana-2991	395	14	simple	simple	ADJ
cana-2991	395	15	classification	classification	NOUN
cana-2991	395	16	tasks	task	NOUN
cana-2991	395	17	,	,	PUNCT
cana-2991	395	18	perform	perform	VERB
cana-2991	395	19	poorly	poorly	ADV
cana-2991	395	20	for	for	ADP
cana-2991	395	21	fake	fake	ADJ
cana-2991	395	22	news	news	NOUN
cana-2991	395	23	detection	detection	NOUN
cana-2991	395	24	and	and	CCONJ
cana-2991	395	25	scale	scale	VERB
cana-2991	395	26	up	up	ADP
cana-2991	395	27	to	to	ADP
cana-2991	395	28	the	the	DET
cana-2991	395	29	complex	complex	ADJ
cana-2991	395	30	task	task	NOUN
cana-2991	395	31	of	of	ADP
cana-2991	395	32	identifying	identify	VERB
cana-2991	395	33	fake	fake	ADJ
cana-2991	395	34	news	news	NOUN
cana-2991	395	35	articles	article	NOUN
cana-2991	395	36	.	.	PUNCT
cana-2991	396	1	word	word	NOUN
cana-2991	396	2	frequency	frequency	NOUN
cana-2991	396	3	is	be	AUX
cana-2991	396	4	the	the	DET
cana-2991	396	5	basis	basis	NOUN
cana-2991	396	6	for	for	ADP
cana-2991	396	7	both	both	PRON
cana-2991	396	8	bow	bow	NOUN
cana-2991	396	9	and	and	CCONJ
cana-2991	396	10	tf	tf	PROPN
cana-2991	396	11	-	-	PUNCT
cana-2991	396	12	idf	idf	PROPN
cana-2991	396	13	,	,	PUNCT
cana-2991	396	14	which	which	PRON
cana-2991	396	15	does	do	AUX
cana-2991	396	16	not	not	PART
cana-2991	396	17	provide	provide	VERB
cana-2991	396	18	any	any	DET
cana-2991	396	19	context	context	NOUN
cana-2991	396	20	about	about	ADP
cana-2991	396	21	how	how	SCONJ
cana-2991	396	22	words	word	NOUN
cana-2991	396	23	relate	relate	VERB
cana-2991	396	24	to	to	ADP
cana-2991	396	25	each	each	DET
cana-2991	396	26	other	other	ADJ
cana-2991	396	27	in	in	ADP
cana-2991	396	28	a	a	DET
cana-2991	396	29	given	give	VERB
cana-2991	396	30	text	text	NOUN
cana-2991	396	31	while	while	SCONJ
cana-2991	396	32	it	it	PRON
cana-2991	396	33	is	be	AUX
cana-2991	396	34	so	so	ADV
cana-2991	396	35	important	important	ADJ
cana-2991	396	36	to	to	PART
cana-2991	396	37	understand	understand	VERB
cana-2991	396	38	that	that	SCONJ
cana-2991	396	39	real	real	ADJ
cana-2991	396	40	news	news	NOUN
cana-2991	396	41	should	should	AUX
cana-2991	396	42	be	be	AUX
cana-2991	396	43	different	different	ADJ
cana-2991	396	44	than	than	ADP
cana-2991	396	45	fake	fake	ADJ
cana-2991	396	46	news	news	NOUN
cana-2991	396	47	.	.	PUNCT
cana-2991	397	1	while	while	SCONJ
cana-2991	397	2	these	these	DET
cana-2991	397	3	methods	method	NOUN
cana-2991	397	4	have	have	VERB
cana-2991	397	5	limitations	limitation	NOUN
cana-2991	397	6	,	,	PUNCT
cana-2991	397	7	they	they	PRON
cana-2991	397	8	nonetheless	nonetheless	ADV
cana-2991	397	9	are	be	AUX
cana-2991	397	10	useful	useful	ADJ
cana-2991	397	11	baselines	baseline	NOUN
cana-2991	397	12	to	to	PART
cana-2991	397	13	show	show	VERB
cana-2991	397	14	the	the	DET
cana-2991	397	15	benefits	benefit	NOUN
cana-2991	397	16	of	of	ADP
cana-2991	397	17	more	more	ADV
cana-2991	397	18	advanced	advanced	ADJ
cana-2991	397	19	embeddings	embedding	NOUN
cana-2991	397	20	such	such	ADJ
cana-2991	397	21	as	as	ADP
cana-2991	397	22	word2vec	word2vec	X
cana-2991	397	23	and	and	CCONJ
cana-2991	397	24	bert	bert	PROPN
cana-2991	397	25	.	.	PUNCT
cana-2991	398	1	communications	communication	NOUN
cana-2991	398	2	on	on	ADP
cana-2991	398	3	applied	apply	VERB
cana-2991	398	4	nonlinear	nonlinear	ADJ
cana-2991	398	5	analysis	analysis	NOUN
cana-2991	398	6	issn	issn	NOUN
cana-2991	398	7	:	:	PUNCT
cana-2991	398	8	1074	1074	NUM
cana-2991	398	9	-	-	PUNCT
cana-2991	398	10	133x	133x	NUM
cana-2991	398	11	vol	vol	NOUN
cana-2991	398	12	32	32	NUM
cana-2991	398	13	no	no	NOUN
cana-2991	398	14	.	.	PUNCT
cana-2991	399	1	5s	5s	NUM
cana-2991	399	2	(	(	PUNCT
cana-2991	399	3	2025	2025	NUM
cana-2991	399	4	)	)	PUNCT
cana-2991	399	5	173	173	NUM
cana-2991	399	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	399	7	the	the	DET
cana-2991	399	8	findings	finding	NOUN
cana-2991	399	9	of	of	ADP
cana-2991	399	10	this	this	DET
cana-2991	399	11	study	study	NOUN
cana-2991	399	12	also	also	ADV
cana-2991	399	13	suggest	suggest	VERB
cana-2991	399	14	that	that	SCONJ
cana-2991	399	15	a	a	DET
cana-2991	399	16	key	key	ADJ
cana-2991	399	17	ingredient	ingredient	NOUN
cana-2991	399	18	to	to	ADP
cana-2991	399	19	the	the	DET
cana-2991	399	20	success	success	NOUN
cana-2991	399	21	in	in	ADP
cana-2991	399	22	using	use	VERB
cana-2991	399	23	these	these	DET
cana-2991	399	24	learners	learner	NOUN
cana-2991	399	25	is	be	AUX
cana-2991	399	26	selection	selection	NOUN
cana-2991	399	27	between	between	ADP
cana-2991	399	28	classifiers	classifier	NOUN
cana-2991	399	29	for	for	ADP
cana-2991	399	30	the	the	DET
cana-2991	399	31	given	give	VERB
cana-2991	399	32	task	task	NOUN
cana-2991	399	33	.	.	PUNCT
cana-2991	400	1	neural	neural	ADJ
cana-2991	400	2	networks	network	NOUN
cana-2991	400	3	gave	give	VERB
cana-2991	400	4	the	the	DET
cana-2991	400	5	best	good	ADJ
cana-2991	400	6	accuracy	accuracy	NOUN
cana-2991	400	7	result	result	NOUN
cana-2991	400	8	across	across	ADP
cana-2991	400	9	all	all	DET
cana-2991	400	10	embeddings	embedding	NOUN
cana-2991	400	11	,	,	PUNCT
cana-2991	400	12	but	but	CCONJ
cana-2991	400	13	other	other	ADJ
cana-2991	400	14	models	model	NOUN
cana-2991	400	15	such	such	ADJ
cana-2991	400	16	as	as	ADP
cana-2991	400	17	logistic	logistic	ADJ
cana-2991	400	18	regression	regression	NOUN
cana-2991	400	19	and	and	CCONJ
cana-2991	400	20	random	random	ADJ
cana-2991	400	21	forests	forest	NOUN
cana-2991	400	22	were	be	AUX
cana-2991	400	23	competitive	competitive	ADJ
cana-2991	400	24	,	,	PUNCT
cana-2991	400	25	especially	especially	ADV
cana-2991	400	26	using	use	VERB
cana-2991	400	27	word2vec	word2vec	PRON
cana-2991	400	28	or	or	CCONJ
cana-2991	400	29	bert	bert	PROPN
cana-2991	400	30	embeddings	embedding	NOUN
cana-2991	400	31	.	.	PUNCT
cana-2991	401	1	deep	deep	ADJ
cana-2991	401	2	learning	learning	NOUN
cana-2991	401	3	models	model	NOUN
cana-2991	401	4	are	be	AUX
cana-2991	401	5	often	often	ADV
cana-2991	401	6	used	use	VERB
cana-2991	401	7	as	as	ADP
cana-2991	401	8	the	the	DET
cana-2991	401	9	classifier	classifier	NOUN
cana-2991	401	10	because	because	SCONJ
cana-2991	401	11	of	of	ADP
cana-2991	401	12	their	their	PRON
cana-2991	401	13	capability	capability	NOUN
cana-2991	401	14	in	in	ADP
cana-2991	401	15	modeling	model	VERB
cana-2991	401	16	non	non	ADJ
cana-2991	401	17	-	-	ADJ
cana-2991	401	18	linear	linear	ADJ
cana-2991	401	19	relationships	relationship	NOUN
cana-2991	401	20	and	and	CCONJ
cana-2991	401	21	learning	learn	VERB
cana-2991	401	22	complex	complex	ADJ
cana-2991	401	23	patterns	pattern	NOUN
cana-2991	401	24	in	in	ADP
cana-2991	401	25	the	the	DET
cana-2991	401	26	data	datum	NOUN
cana-2991	401	27	,	,	PUNCT
cana-2991	401	28	but	but	CCONJ
cana-2991	401	29	it	it	PRON
cana-2991	401	30	comes	come	VERB
cana-2991	401	31	with	with	ADP
cana-2991	401	32	a	a	DET
cana-2991	401	33	cost	cost	NOUN
cana-2991	401	34	such	such	ADJ
cana-2991	401	35	as	as	ADP
cana-2991	401	36	computation	computation	NOUN
cana-2991	401	37	and	and	CCONJ
cana-2991	401	38	training	training	NOUN
cana-2991	401	39	time	time	NOUN
cana-2991	401	40	.	.	PUNCT
cana-2991	402	1	when	when	SCONJ
cana-2991	402	2	you	you	PRON
cana-2991	402	3	have	have	VERB
cana-2991	402	4	limited	limit	VERB
cana-2991	402	5	computational	computational	ADJ
cana-2991	402	6	resources	resource	NOUN
cana-2991	402	7	,	,	PUNCT
cana-2991	402	8	logistic	logistic	ADJ
cana-2991	402	9	regression	regression	NOUN
cana-2991	402	10	or	or	CCONJ
cana-2991	402	11	random	random	ADJ
cana-2991	402	12	forests	forest	NOUN
cana-2991	402	13	along	along	ADP
cana-2991	402	14	with	with	ADP
cana-2991	402	15	word2vec	word2vec	X
cana-2991	402	16	/	/	SYM
cana-2991	402	17	bert	bert	NOUN
cana-2991	402	18	embeddings	embedding	NOUN
cana-2991	402	19	may	may	AUX
cana-2991	402	20	offer	offer	VERB
cana-2991	402	21	a	a	DET
cana-2991	402	22	better	well	ADJ
cana-2991	402	23	balance	balance	NOUN
cana-2991	402	24	between	between	ADP
cana-2991	402	25	performance	performance	NOUN
cana-2991	402	26	and	and	CCONJ
cana-2991	402	27	efficiency	efficiency	NOUN
cana-2991	402	28	.	.	PUNCT
cana-2991	403	1	real	real	ADJ
cana-2991	403	2	world	world	NOUN
cana-2991	403	3	use	use	VERB
cana-2991	403	4	cases	case	NOUN
cana-2991	403	5	and	and	CCONJ
cana-2991	403	6	scalability	scalability	NOUN
cana-2991	403	7	a	a	DET
cana-2991	403	8	key	key	ADJ
cana-2991	403	9	part	part	NOUN
cana-2991	403	10	of	of	ADP
cana-2991	403	11	this	this	DET
cana-2991	403	12	study	study	NOUN
cana-2991	403	13	is	be	AUX
cana-2991	403	14	scalability	scalability	NOUN
cana-2991	403	15	.	.	PUNCT
cana-2991	404	1	as	as	SCONJ
cana-2991	404	2	the	the	DET
cana-2991	404	3	news	news	NOUN
cana-2991	404	4	circulates	circulate	VERB
cana-2991	404	5	rapidly	rapidly	ADV
cana-2991	404	6	and	and	CCONJ
cana-2991	404	7	continuously	continuously	ADV
cana-2991	404	8	across	across	ADP
cana-2991	404	9	social	social	ADJ
cana-2991	404	10	media	medium	NOUN
cana-2991	404	11	,	,	PUNCT
cana-2991	404	12	fake	fake	ADJ
cana-2991	404	13	news	news	NOUN
cana-2991	404	14	detection	detection	NOUN
cana-2991	404	15	systems	system	NOUN
cana-2991	404	16	need	need	VERB
cana-2991	404	17	to	to	PART
cana-2991	404	18	have	have	VERB
cana-2991	404	19	the	the	DET
cana-2991	404	20	ability	ability	NOUN
cana-2991	404	21	to	to	PART
cana-2991	404	22	process	process	VERB
cana-2991	404	23	gargantuan	gargantuan	ADJ
cana-2991	404	24	quantities	quantity	NOUN
cana-2991	404	25	of	of	ADP
cana-2991	404	26	data	datum	NOUN
cana-2991	404	27	at	at	ADP
cana-2991	404	28	all	all	DET
cana-2991	404	29	times	time	NOUN
cana-2991	404	30	to	to	PART
cana-2991	404	31	deliver	deliver	VERB
cana-2991	404	32	real	real	ADJ
cana-2991	404	33	-	-	PUNCT
cana-2991	404	34	time	time	NOUN
cana-2991	404	35	solutions	solution	NOUN
cana-2991	404	36	.	.	PUNCT
cana-2991	405	1	to	to	PART
cana-2991	405	2	tackle	tackle	VERB
cana-2991	405	3	this	this	PRON
cana-2991	405	4	,	,	PUNCT
cana-2991	405	5	we	we	PRON
cana-2991	405	6	have	have	AUX
cana-2991	405	7	included	include	VERB
cana-2991	405	8	distributed	distribute	VERB
cana-2991	405	9	processing	processing	NOUN
cana-2991	405	10	frameworks	framework	NOUN
cana-2991	405	11	like	like	ADP
cana-2991	405	12	apache	apache	NOUN
cana-2991	405	13	spark	spark	NOUN
cana-2991	405	14	in	in	ADP
cana-2991	405	15	the	the	DET
cana-2991	405	16	architecture	architecture	NOUN
cana-2991	405	17	of	of	ADP
cana-2991	405	18	the	the	DET
cana-2991	405	19	system	system	NOUN
cana-2991	405	20	.	.	PUNCT
cana-2991	406	1	our	our	PRON
cana-2991	406	2	experiments	experiment	NOUN
cana-2991	406	3	showed	show	VERB
cana-2991	406	4	that	that	SCONJ
cana-2991	406	5	this	this	DET
cana-2991	406	6	distribution	distribution	NOUN
cana-2991	406	7	of	of	ADP
cana-2991	406	8	the	the	DET
cana-2991	406	9	computational	computational	ADJ
cana-2991	406	10	load	load	NOUN
cana-2991	406	11	among	among	ADP
cana-2991	406	12	multiple	multiple	ADJ
cana-2991	406	13	nodes	node	NOUN
cana-2991	406	14	practically	practically	ADV
cana-2991	406	15	reduces	reduce	VERB
cana-2991	406	16	pre	pre	ADJ
cana-2991	406	17	-	-	ADJ
cana-2991	406	18	processing	processing	ADJ
cana-2991	406	19	and	and	CCONJ
cana-2991	406	20	model	model	NOUN
cana-2991	406	21	training	training	NOUN
cana-2991	406	22	time	time	NOUN
cana-2991	406	23	to	to	ADP
cana-2991	406	24	a	a	DET
cana-2991	406	25	level	level	NOUN
cana-2991	406	26	by	by	ADP
cana-2991	406	27	as	as	ADV
cana-2991	406	28	much	much	ADJ
cana-2991	406	29	as	as	ADP
cana-2991	406	30	five	five	NUM
cana-2991	406	31	times	time	NOUN
cana-2991	406	32	faster	fast	ADV
cana-2991	406	33	for	for	ADP
cana-2991	406	34	large	large	ADJ
cana-2991	406	35	datasets	dataset	NOUN
cana-2991	406	36	.	.	PUNCT
cana-2991	407	1	this	this	PRON
cana-2991	407	2	lends	lend	VERB
cana-2991	407	3	itself	itself	PRON
cana-2991	407	4	well	well	ADV
cana-2991	407	5	to	to	ADP
cana-2991	407	6	real	real	ADJ
cana-2991	407	7	-	-	PUNCT
cana-2991	407	8	time	time	NOUN
cana-2991	407	9	applications	application	NOUN
cana-2991	407	10	that	that	PRON
cana-2991	407	11	require	require	VERB
cana-2991	407	12	a	a	DET
cana-2991	407	13	high	high	ADJ
cana-2991	407	14	degree	degree	NOUN
cana-2991	407	15	of	of	ADP
cana-2991	407	16	speed	speed	NOUN
cana-2991	407	17	and	and	CCONJ
cana-2991	407	18	efficiency	efficiency	NOUN
cana-2991	407	19	.	.	PUNCT
cana-2991	408	1	this	this	PRON
cana-2991	408	2	allows	allow	VERB
cana-2991	408	3	the	the	DET
cana-2991	408	4	proposed	propose	VERB
cana-2991	408	5	system	system	NOUN
cana-2991	408	6	to	to	PART
cana-2991	408	7	scale	scale	VERB
cana-2991	408	8	dynamically	dynamically	ADV
cana-2991	408	9	,	,	PUNCT
cana-2991	408	10	a	a	DET
cana-2991	408	11	requirement	requirement	NOUN
cana-2991	408	12	for	for	ADP
cana-2991	408	13	organizations	organization	NOUN
cana-2991	408	14	that	that	PRON
cana-2991	408	15	would	would	AUX
cana-2991	408	16	need	need	VERB
cana-2991	408	17	to	to	PART
cana-2991	408	18	process	process	VERB
cana-2991	408	19	millions	million	NOUN
cana-2991	408	20	of	of	ADP
cana-2991	408	21	transactions	transaction	NOUN
cana-2991	408	22	daily	daily	ADV
cana-2991	408	23	.	.	PUNCT
cana-2991	409	1	social	social	ADJ
cana-2991	409	2	media	medium	NOUN
cana-2991	409	3	platforms	platform	NOUN
cana-2991	409	4	such	such	ADJ
cana-2991	409	5	as	as	ADP
cana-2991	409	6	twitter	twitter	NOUN
cana-2991	409	7	and	and	CCONJ
cana-2991	409	8	facebook	facebook	NOUN
cana-2991	409	9	could	could	AUX
cana-2991	409	10	use	use	VERB
cana-2991	409	11	this	this	DET
cana-2991	409	12	system	system	NOUN
cana-2991	409	13	to	to	PART
cana-2991	409	14	supplement	supplement	VERB
cana-2991	409	15	their	their	PRON
cana-2991	409	16	content	content	NOUN
cana-2991	409	17	moderation	moderation	NOUN
cana-2991	409	18	pipelines	pipeline	NOUN
cana-2991	409	19	,	,	PUNCT
cana-2991	409	20	so	so	SCONJ
cana-2991	409	21	that	that	SCONJ
cana-2991	409	22	misinformation	misinformation	NOUN
cana-2991	409	23	would	would	AUX
cana-2991	409	24	be	be	AUX
cana-2991	409	25	automatically	automatically	ADV
cana-2991	409	26	flagged	flag	VERB
cana-2991	409	27	or	or	CCONJ
cana-2991	409	28	removed	remove	VERB
cana-2991	409	29	before	before	ADP
cana-2991	409	30	spreading	spread	VERB
cana-2991	409	31	.	.	PUNCT
cana-2991	410	1	moreover	moreover	ADV
cana-2991	410	2	,	,	PUNCT
cana-2991	410	3	it	it	PRON
cana-2991	410	4	will	will	AUX
cana-2991	410	5	allow	allow	VERB
cana-2991	410	6	news	news	NOUN
cana-2991	410	7	aggregators	aggregator	NOUN
cana-2991	410	8	and	and	CCONJ
cana-2991	410	9	factcheckers	factchecker	NOUN
cana-2991	410	10	to	to	PART
cana-2991	410	11	use	use	VERB
cana-2991	410	12	this	this	DET
cana-2991	410	13	platform	platform	NOUN
cana-2991	410	14	for	for	ADP
cana-2991	410	15	real	real	ADJ
cana-2991	410	16	-	-	PUNCT
cana-2991	410	17	time	time	NOUN
cana-2991	410	18	fact	fact	NOUN
cana-2991	410	19	-	-	PUNCT
cana-2991	410	20	checking	checking	NOUN
cana-2991	410	21	on	on	ADP
cana-2991	410	22	news	news	NOUN
cana-2991	410	23	articles	article	NOUN
cana-2991	410	24	.	.	PUNCT
cana-2991	411	1	the	the	DET
cana-2991	411	2	system	system	NOUN
cana-2991	411	3	is	be	AUX
cana-2991	411	4	distributed	distribute	VERB
cana-2991	411	5	so	so	SCONJ
cana-2991	411	6	it	it	PRON
cana-2991	411	7	can	can	AUX
cana-2991	411	8	be	be	AUX
cana-2991	411	9	scaled	scale	VERB
cana-2991	411	10	to	to	PART
cana-2991	411	11	handle	handle	VERB
cana-2991	411	12	millions	million	NOUN
cana-2991	411	13	of	of	ADP
cana-2991	411	14	news	news	NOUN
cana-2991	411	15	articles	article	NOUN
cana-2991	411	16	or	or	CCONJ
cana-2991	411	17	social	social	ADJ
cana-2991	411	18	media	medium	NOUN
cana-2991	411	19	posts	post	NOUN
cana-2991	411	20	,	,	PUNCT
cana-2991	411	21	making	make	VERB
cana-2991	411	22	it	it	PRON
cana-2991	411	23	a	a	DET
cana-2991	411	24	good	good	ADJ
cana-2991	411	25	choice	choice	NOUN
cana-2991	411	26	for	for	ADP
cana-2991	411	27	organizations	organization	NOUN
cana-2991	411	28	who	who	PRON
cana-2991	411	29	have	have	VERB
cana-2991	411	30	large	large	ADJ
cana-2991	411	31	amounts	amount	NOUN
cana-2991	411	32	of	of	ADP
cana-2991	411	33	data	datum	NOUN
cana-2991	411	34	that	that	PRON
cana-2991	411	35	needs	need	VERB
cana-2991	411	36	to	to	PART
cana-2991	411	37	be	be	AUX
cana-2991	411	38	processed	process	VERB
cana-2991	411	39	.	.	PUNCT
cana-2991	412	1	challenges	challenge	NOUN
cana-2991	412	2	and	and	CCONJ
cana-2991	412	3	limitations	limitation	VERB
cana-2991	412	4	acknowledgements	acknowledgement	NOUN
cana-2991	412	5	although	although	SCONJ
cana-2991	412	6	the	the	DET
cana-2991	412	7	results	result	NOUN
cana-2991	412	8	obtained	obtain	VERB
cana-2991	412	9	were	be	AUX
cana-2991	412	10	promising	promise	VERB
cana-2991	412	11	,	,	PUNCT
cana-2991	412	12	there	there	PRON
cana-2991	412	13	are	be	VERB
cana-2991	412	14	several	several	ADJ
cana-2991	412	15	challenges	challenge	NOUN
cana-2991	412	16	and	and	CCONJ
cana-2991	412	17	limitations	limitation	NOUN
cana-2991	412	18	associated	associate	VERB
cana-2991	412	19	with	with	ADP
cana-2991	412	20	this	this	DET
cana-2991	412	21	research	research	NOUN
cana-2991	412	22	.	.	PUNCT
cana-2991	413	1	first	first	ADV
cana-2991	413	2	,	,	PUNCT
cana-2991	413	3	bert	bert	PROPN
cana-2991	413	4	and	and	CCONJ
cana-2991	413	5	other	other	ADJ
cana-2991	413	6	deep	deep	ADJ
cana-2991	413	7	embeddings	embedding	NOUN
cana-2991	413	8	models	model	NOUN
cana-2991	413	9	allow	allow	VERB
cana-2991	413	10	for	for	ADP
cana-2991	413	11	good	good	ADJ
cana-2991	413	12	performance	performance	NOUN
cana-2991	413	13	scores	score	NOUN
cana-2991	413	14	,	,	PUNCT
cana-2991	413	15	but	but	CCONJ
cana-2991	413	16	computational	computational	ADJ
cana-2991	413	17	power	power	NOUN
cana-2991	413	18	is	be	AUX
cana-2991	413	19	quite	quite	ADV
cana-2991	413	20	expensive	expensive	ADJ
cana-2991	413	21	.	.	PUNCT
cana-2991	414	1	especially	especially	ADV
cana-2991	414	2	bert	bert	PROPN
cana-2991	414	3	,	,	PUNCT
cana-2991	414	4	it	it	PRON
cana-2991	414	5	requires	require	VERB
cana-2991	414	6	a	a	DET
cana-2991	414	7	lot	lot	NOUN
cana-2991	414	8	of	of	ADP
cana-2991	414	9	processing	processing	NOUN
cana-2991	414	10	power	power	NOUN
cana-2991	414	11	and	and	CCONJ
cana-2991	414	12	memory	memory	NOUN
cana-2991	414	13	to	to	PART
cana-2991	414	14	train	train	VERB
cana-2991	414	15	those	those	DET
cana-2991	414	16	models	model	NOUN
cana-2991	414	17	and	and	CCONJ
cana-2991	414	18	therefore	therefore	ADV
cana-2991	414	19	might	might	AUX
cana-2991	414	20	not	not	PART
cana-2991	414	21	be	be	AUX
cana-2991	414	22	suitable	suitable	ADJ
cana-2991	414	23	for	for	ADP
cana-2991	414	24	resource	resource	NOUN
cana-2991	414	25	-	-	PUNCT
cana-2991	414	26	restricted	restrict	VERB
cana-2991	414	27	environments	environment	NOUN
cana-2991	414	28	.	.	PUNCT
cana-2991	415	1	while	while	SCONJ
cana-2991	415	2	using	use	VERB
cana-2991	415	3	distributed	distribute	VERB
cana-2991	415	4	processing	processing	NOUN
cana-2991	415	5	frameworks	framework	NOUN
cana-2991	415	6	solve	solve	VERB
cana-2991	415	7	this	this	PRON
cana-2991	415	8	by	by	ADP
cana-2991	415	9	distributing	distribute	VERB
cana-2991	415	10	the	the	DET
cana-2991	415	11	computational	computational	ADJ
cana-2991	415	12	load	load	NOUN
cana-2991	415	13	across	across	ADP
cana-2991	415	14	multiple	multiple	ADJ
cana-2991	415	15	machines	machine	NOUN
cana-2991	415	16	,	,	PUNCT
cana-2991	415	17	smaller	small	ADJ
cana-2991	415	18	organizations	organization	NOUN
cana-2991	415	19	or	or	CCONJ
cana-2991	415	20	individuals	individual	NOUN
cana-2991	415	21	with	with	ADP
cana-2991	415	22	limited	limited	ADJ
cana-2991	415	23	access	access	NOUN
cana-2991	415	24	to	to	ADP
cana-2991	415	25	computing	compute	VERB
cana-2991	415	26	resources	resource	NOUN
cana-2991	415	27	may	may	AUX
cana-2991	415	28	find	find	VERB
cana-2991	415	29	it	it	PRON
cana-2991	415	30	challenging	challenging	ADJ
cana-2991	415	31	to	to	PART
cana-2991	415	32	enable	enable	VERB
cana-2991	415	33	bert	bert	NOUN
cana-2991	415	34	-	-	PUNCT
cana-2991	415	35	based	base	VERB
cana-2991	415	36	models	model	NOUN
cana-2991	415	37	at	at	ADP
cana-2991	415	38	scale	scale	NOUN
cana-2991	415	39	.	.	PUNCT
cana-2991	416	1	another	another	DET
cana-2991	416	2	hurdle	hurdle	NOUN
cana-2991	416	3	is	be	AUX
cana-2991	416	4	that	that	SCONJ
cana-2991	416	5	the	the	DET
cana-2991	416	6	model	model	NOUN
cana-2991	416	7	might	might	AUX
cana-2991	416	8	not	not	PART
cana-2991	416	9	be	be	AUX
cana-2991	416	10	generalizable	generalizable	ADJ
cana-2991	416	11	.	.	PUNCT
cana-2991	417	1	since	since	SCONJ
cana-2991	417	2	the	the	DET
cana-2991	417	3	datasets	dataset	NOUN
cana-2991	417	4	used	use	VERB
cana-2991	417	5	in	in	ADP
cana-2991	417	6	this	this	DET
cana-2991	417	7	study	study	NOUN
cana-2991	417	8	(	(	PUNCT
cana-2991	417	9	politifact	politifact	NOUN
cana-2991	417	10	and	and	CCONJ
cana-2991	417	11	liar	liar	NOUN
cana-2991	417	12	)	)	PUNCT
cana-2991	417	13	mainly	mainly	ADV
cana-2991	417	14	deal	deal	VERB
cana-2991	417	15	with	with	ADP
cana-2991	417	16	political	political	ADJ
cana-2991	417	17	news	news	NOUN
cana-2991	417	18	only	only	ADV
cana-2991	417	19	,	,	PUNCT
cana-2991	417	20	it	it	PRON
cana-2991	417	21	is	be	AUX
cana-2991	417	22	not	not	PART
cana-2991	417	23	guaranteed	guarantee	VERB
cana-2991	417	24	that	that	SCONJ
cana-2991	417	25	other	other	ADJ
cana-2991	417	26	types	type	NOUN
cana-2991	417	27	of	of	ADP
cana-2991	417	28	fake	fake	ADJ
cana-2991	417	29	news	news	NOUN
cana-2991	417	30	,	,	PUNCT
cana-2991	417	31	for	for	ADP
cana-2991	417	32	instance	instance	NOUN
cana-2991	417	33	health	health	NOUN
cana-2991	417	34	-	-	PUNCT
cana-2991	417	35	related	relate	VERB
cana-2991	417	36	misinformation	misinformation	NOUN
cana-2991	417	37	or	or	CCONJ
cana-2991	417	38	financial	financial	ADJ
cana-2991	417	39	news	news	NOUN
cana-2991	417	40	etc	etc	X
cana-2991	417	41	.	.	X
cana-2991	417	42	,	,	PUNCT
cana-2991	417	43	would	would	AUX
cana-2991	417	44	have	have	AUX
cana-2991	417	45	been	be	AUX
cana-2991	417	46	effectively	effectively	ADV
cana-2991	417	47	detected	detect	VERB
cana-2991	417	48	using	use	VERB
cana-2991	417	49	the	the	DET
cana-2991	417	50	proposed	propose	VERB
cana-2991	417	51	model	model	NOUN
cana-2991	417	52	.	.	PUNCT
cana-2991	418	1	though	though	SCONJ
cana-2991	418	2	it	it	PRON
cana-2991	418	3	does	do	AUX
cana-2991	418	4	have	have	VERB
cana-2991	418	5	some	some	DET
cana-2991	418	6	adaptability	adaptability	NOUN
cana-2991	418	7	to	to	ADP
cana-2991	418	8	new	new	ADJ
cana-2991	418	9	datasets	dataset	NOUN
cana-2991	418	10	,	,	PUNCT
cana-2991	418	11	we	we	PRON
cana-2991	418	12	need	need	VERB
cana-2991	418	13	results	result	NOUN
cana-2991	418	14	on	on	ADP
cana-2991	418	15	additional	additional	ADJ
cana-2991	418	16	fake	fake	ADJ
cana-2991	418	17	news	news	NOUN
cana-2991	418	18	domains	domain	NOUN
cana-2991	418	19	.	.	PUNCT
cana-2991	419	1	however	however	ADV
cana-2991	419	2	,	,	PUNCT
cana-2991	419	3	future	future	ADJ
cana-2991	419	4	work	work	NOUN
cana-2991	419	5	should	should	AUX
cana-2991	419	6	aim	aim	VERB
cana-2991	419	7	at	at	ADP
cana-2991	419	8	evaluating	evaluate	VERB
cana-2991	419	9	our	our	PRON
cana-2991	419	10	approach	approach	NOUN
cana-2991	419	11	on	on	ADP
cana-2991	419	12	more	more	ADJ
cana-2991	419	13	varieties	variety	NOUN
cana-2991	419	14	of	of	ADP
cana-2991	419	15	fake	fake	ADJ
cana-2991	419	16	news	news	NOUN
cana-2991	419	17	to	to	PART
cana-2991	419	18	test	test	VERB
cana-2991	419	19	the	the	DET
cana-2991	419	20	generality	generality	NOUN
cana-2991	419	21	of	of	ADP
cana-2991	419	22	the	the	DET
cana-2991	419	23	model	model	NOUN
cana-2991	419	24	,	,	PUNCT
cana-2991	419	25	as	as	ADV
cana-2991	419	26	well	well	ADV
cana-2991	419	27	as	as	ADP
cana-2991	419	28	integrating	integrate	VERB
cana-2991	419	29	extra	extra	ADJ
cana-2991	419	30	datasets	dataset	NOUN
cana-2991	419	31	to	to	PART
cana-2991	419	32	train	train	VERB
cana-2991	419	33	it	it	PRON
cana-2991	419	34	on	on	ADP
cana-2991	419	35	a	a	DET
cana-2991	419	36	variety	variety	NOUN
cana-2991	419	37	of	of	ADP
cana-2991	419	38	subjects	subject	NOUN
cana-2991	419	39	.	.	PUNCT
cana-2991	420	1	communications	communication	NOUN
cana-2991	420	2	on	on	ADP
cana-2991	420	3	applied	apply	VERB
cana-2991	420	4	nonlinear	nonlinear	ADJ
cana-2991	420	5	analysis	analysis	NOUN
cana-2991	420	6	issn	issn	NOUN
cana-2991	420	7	:	:	PUNCT
cana-2991	420	8	1074	1074	NUM
cana-2991	420	9	-	-	PUNCT
cana-2991	420	10	133x	133x	NUM
cana-2991	420	11	vol	vol	NOUN
cana-2991	420	12	32	32	NUM
cana-2991	420	13	no	no	NOUN
cana-2991	420	14	.	.	PUNCT
cana-2991	421	1	5s	5s	NUM
cana-2991	421	2	(	(	PUNCT
cana-2991	421	3	2025	2025	NUM
cana-2991	421	4	)	)	PUNCT
cana-2991	421	5	174	174	NUM
cana-2991	421	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	421	7	the	the	DET
cana-2991	421	8	system	system	NOUN
cana-2991	421	9	is	be	AUX
cana-2991	421	10	also	also	ADV
cana-2991	421	11	limited	limit	VERB
cana-2991	421	12	by	by	ADP
cana-2991	421	13	the	the	DET
cana-2991	421	14	dependency	dependency	NOUN
cana-2991	421	15	on	on	ADP
cana-2991	421	16	labeled	label	VERB
cana-2991	421	17	datasets	dataset	NOUN
cana-2991	421	18	.	.	PUNCT
cana-2991	422	1	training	training	NOUN
cana-2991	422	2	machine	machine	NOUN
cana-2991	422	3	learning	learning	NOUN
cana-2991	422	4	models	model	NOUN
cana-2991	422	5	on	on	ADP
cana-2991	422	6	fake	fake	ADJ
cana-2991	422	7	news	news	NOUN
cana-2991	422	8	is	be	AUX
cana-2991	422	9	difficult	difficult	ADJ
cana-2991	422	10	because	because	SCONJ
cana-2991	422	11	the	the	DET
cana-2991	422	12	training	training	NOUN
cana-2991	422	13	data	datum	NOUN
cana-2991	422	14	requires	require	VERB
cana-2991	422	15	a	a	DET
cana-2991	422	16	large	large	ADJ
cana-2991	422	17	number	number	NOUN
cana-2991	422	18	of	of	ADP
cana-2991	422	19	labeled	label	VERB
cana-2991	422	20	inputs	input	NOUN
cana-2991	422	21	,	,	PUNCT
cana-2991	422	22	and	and	CCONJ
cana-2991	422	23	labeling	label	VERB
cana-2991	422	24	fake	fake	ADJ
cana-2991	422	25	news	news	NOUN
cana-2991	422	26	is	be	AUX
cana-2991	422	27	in	in	ADP
cana-2991	422	28	general	general	ADJ
cana-2991	422	29	done	do	VERB
cana-2991	422	30	manually	manually	ADV
cana-2991	422	31	so	so	SCONJ
cana-2991	422	32	it	it	PRON
cana-2991	422	33	's	be	AUX
cana-2991	422	34	time	time	NOUN
cana-2991	422	35	-	-	PUNCT
cana-2991	422	36	consuming	consume	VERB
cana-2991	422	37	and	and	CCONJ
cana-2991	422	38	expensive	expensive	ADJ
cana-2991	422	39	.	.	PUNCT
cana-2991	423	1	while	while	SCONJ
cana-2991	423	2	crowdsourcing	crowdsourcing	NOUN
cana-2991	423	3	platforms	platform	NOUN
cana-2991	423	4	and	and	CCONJ
cana-2991	423	5	automated	automate	VERB
cana-2991	423	6	labeling	labeling	NOUN
cana-2991	423	7	tools	tool	NOUN
cana-2991	423	8	can	can	AUX
cana-2991	423	9	lighten	lighten	VERB
cana-2991	423	10	this	this	DET
cana-2991	423	11	load	load	NOUN
cana-2991	423	12	,	,	PUNCT
cana-2991	423	13	acquiring	acquire	VERB
cana-2991	423	14	properly	properly	ADV
cana-2991	423	15	annotated	annotate	VERB
cana-2991	423	16	data	datum	NOUN
cana-2991	423	17	in	in	ADP
cana-2991	423	18	the	the	DET
cana-2991	423	19	domain	domain	NOUN
cana-2991	423	20	of	of	ADP
cana-2991	423	21	fake	fake	ADJ
cana-2991	423	22	news	news	NOUN
cana-2991	423	23	detection	detection	NOUN
cana-2991	423	24	remains	remain	VERB
cana-2991	423	25	one	one	NUM
cana-2991	423	26	of	of	ADP
cana-2991	423	27	the	the	DET
cana-2991	423	28	most	most	ADV
cana-2991	423	29	significant	significant	ADJ
cana-2991	423	30	challenges	challenge	NOUN
cana-2991	423	31	.	.	PUNCT
cana-2991	424	1	in	in	ADP
cana-2991	424	2	addition	addition	NOUN
cana-2991	424	3	,	,	PUNCT
cana-2991	424	4	the	the	DET
cana-2991	424	5	system	system	NOUN
cana-2991	424	6	needs	need	VERB
cana-2991	424	7	to	to	PART
cana-2991	424	8	be	be	AUX
cana-2991	424	9	trained	train	VERB
cana-2991	424	10	repeatedly	repeatedly	ADV
cana-2991	424	11	with	with	ADP
cana-2991	424	12	new	new	ADJ
cana-2991	424	13	data	datum	NOUN
cana-2991	424	14	in	in	ADP
cana-2991	424	15	order	order	NOUN
cana-2991	424	16	to	to	PART
cana-2991	424	17	strengthen	strengthen	VERB
cana-2991	424	18	its	its	PRON
cana-2991	424	19	effectiveness	effectiveness	NOUN
cana-2991	424	20	as	as	SCONJ
cana-2991	424	21	fake	fake	ADJ
cana-2991	424	22	new	new	ADJ
cana-2991	424	23	types	type	NOUN
cana-2991	424	24	evolve	evolve	VERB
cana-2991	424	25	over	over	ADP
cana-2991	424	26	time	time	NOUN
cana-2991	424	27	.	.	PUNCT
cana-2991	425	1	another	another	DET
cana-2991	425	2	vital	vital	ADJ
cana-2991	425	3	consideration	consideration	NOUN
cana-2991	425	4	is	be	AUX
cana-2991	425	5	the	the	DET
cana-2991	425	6	trade	trade	NOUN
cana-2991	425	7	-	-	PUNCT
cana-2991	425	8	off	off	NOUN
cana-2991	425	9	between	between	ADP
cana-2991	425	10	computational	computational	ADJ
cana-2991	425	11	efficiency	efficiency	NOUN
cana-2991	425	12	and	and	CCONJ
cana-2991	425	13	complexity	complexity	NOUN
cana-2991	425	14	of	of	ADP
cana-2991	425	15	the	the	DET
cana-2991	425	16	model	model	NOUN
cana-2991	425	17	.	.	PUNCT
cana-2991	426	1	although	although	SCONJ
cana-2991	426	2	the	the	DET
cana-2991	426	3	performance	performance	NOUN
cana-2991	426	4	of	of	ADP
cana-2991	426	5	neural	neural	ADJ
cana-2991	426	6	networks	network	NOUN
cana-2991	426	7	(	(	PUNCT
cana-2991	426	8	a	a	DET
cana-2991	426	9	type	type	NOUN
cana-2991	426	10	of	of	ADP
cana-2991	426	11	deep	deep	ADJ
cana-2991	426	12	learning	learning	NOUN
cana-2991	426	13	model	model	NOUN
cana-2991	426	14	)	)	PUNCT
cana-2991	426	15	was	be	AUX
cana-2991	426	16	generally	generally	ADV
cana-2991	426	17	best	good	ADJ
cana-2991	426	18	in	in	ADP
cana-2991	426	19	our	our	PRON
cana-2991	426	20	experiments	experiment	NOUN
cana-2991	426	21	,	,	PUNCT
cana-2991	426	22	they	they	PRON
cana-2991	426	23	required	require	VERB
cana-2991	426	24	many	many	ADJ
cana-2991	426	25	computational	computational	ADJ
cana-2991	426	26	resources	resource	NOUN
cana-2991	426	27	and	and	CCONJ
cana-2991	426	28	much	much	ADJ
cana-2991	426	29	training	training	NOUN
cana-2991	426	30	time	time	NOUN
cana-2991	426	31	.	.	PUNCT
cana-2991	427	1	on	on	ADP
cana-2991	427	2	the	the	DET
cana-2991	427	3	other	other	ADJ
cana-2991	427	4	hand	hand	NOUN
cana-2991	427	5	,	,	PUNCT
cana-2991	427	6	simpler	simple	ADJ
cana-2991	427	7	models	model	NOUN
cana-2991	427	8	like	like	ADP
cana-2991	427	9	logistic	logistic	ADJ
cana-2991	427	10	regression	regression	NOUN
cana-2991	427	11	and	and	CCONJ
cana-2991	427	12	random	random	ADJ
cana-2991	427	13	forests	forest	NOUN
cana-2991	427	14	although	although	SCONJ
cana-2991	427	15	not	not	PART
cana-2991	427	16	as	as	ADV
cana-2991	427	17	accurate	accurate	ADJ
cana-2991	427	18	are	be	AUX
cana-2991	427	19	faster	fast	ADJ
cana-2991	427	20	to	to	PART
cana-2991	427	21	train	train	VERB
cana-2991	427	22	with	with	ADP
cana-2991	427	23	less	less	ADJ
cana-2991	427	24	resource	resource	NOUN
cana-2991	427	25	required	require	VERB
cana-2991	427	26	.	.	PUNCT
cana-2991	428	1	in	in	ADP
cana-2991	428	2	practice	practice	NOUN
cana-2991	428	3	,	,	PUNCT
cana-2991	428	4	especially	especially	ADV
cana-2991	428	5	if	if	SCONJ
cana-2991	428	6	operating	operate	VERB
cana-2991	428	7	in	in	ADP
cana-2991	428	8	high	high	ADJ
cana-2991	428	9	-	-	PUNCT
cana-2991	428	10	speed	speed	NOUN
cana-2991	428	11	environments	environment	NOUN
cana-2991	428	12	(	(	PUNCT
cana-2991	428	13	like	like	ADP
cana-2991	428	14	monitoring	monitor	VERB
cana-2991	428	15	social	social	ADJ
cana-2991	428	16	media	medium	NOUN
cana-2991	428	17	for	for	ADP
cana-2991	428	18	real	real	ADJ
cana-2991	428	19	-	-	PUNCT
cana-2991	428	20	time	time	NOUN
cana-2991	428	21	activity	activity	NOUN
cana-2991	428	22	)	)	PUNCT
cana-2991	428	23	,	,	PUNCT
cana-2991	428	24	which	which	DET
cana-2991	428	25	model	model	NOUN
cana-2991	428	26	to	to	PART
cana-2991	428	27	use	use	VERB
cana-2991	428	28	might	might	AUX
cana-2991	428	29	be	be	AUX
cana-2991	428	30	dependent	dependent	ADJ
cana-2991	428	31	on	on	ADP
cana-2991	428	32	the	the	DET
cana-2991	428	33	constraints	constraint	NOUN
cana-2991	428	34	of	of	ADP
cana-2991	428	35	the	the	DET
cana-2991	428	36	system	system	NOUN
cana-2991	428	37	like	like	ADP
cana-2991	428	38	how	how	SCONJ
cana-2991	428	39	much	much	ADJ
cana-2991	428	40	processing	processing	NOUN
cana-2991	428	41	power	power	NOUN
cana-2991	428	42	is	be	AUX
cana-2991	428	43	available	available	ADJ
cana-2991	428	44	and	and	CCONJ
cana-2991	428	45	how	how	SCONJ
cana-2991	428	46	much	much	ADJ
cana-2991	428	47	data	datum	NOUN
cana-2991	428	48	requires	require	VERB
cana-2991	428	49	analysis	analysis	NOUN
cana-2991	428	50	.	.	PUNCT
cana-2991	429	1	future	future	ADJ
cana-2991	429	2	directions	direction	NOUN
cana-2991	429	3	the	the	DET
cana-2991	429	4	research	research	NOUN
cana-2991	429	5	opens	open	VERB
cana-2991	429	6	up	up	ADP
cana-2991	429	7	a	a	DET
cana-2991	429	8	wide	wide	ADJ
cana-2991	429	9	range	range	NOUN
cana-2991	429	10	of	of	ADP
cana-2991	429	11	possible	possible	ADJ
cana-2991	429	12	directions	direction	NOUN
cana-2991	429	13	for	for	ADP
cana-2991	429	14	future	future	ADJ
cana-2991	429	15	work	work	NOUN
cana-2991	429	16	.	.	PUNCT
cana-2991	430	1	a	a	DET
cana-2991	430	2	possible	possible	ADJ
cana-2991	430	3	direction	direction	NOUN
cana-2991	430	4	could	could	AUX
cana-2991	430	5	be	be	AUX
cana-2991	430	6	to	to	PART
cana-2991	430	7	delve	delve	VERB
cana-2991	430	8	into	into	ADP
cana-2991	430	9	even	even	ADV
cana-2991	430	10	higher	high	ADJ
cana-2991	430	11	-	-	PUNCT
cana-2991	430	12	level	level	NOUN
cana-2991	430	13	contextual	contextual	ADJ
cana-2991	430	14	embeddings	embedding	NOUN
cana-2991	430	15	(	(	PUNCT
cana-2991	430	16	roberta	roberta	PROPN
cana-2991	430	17	,	,	PUNCT
cana-2991	430	18	etc	etc	X
cana-2991	430	19	.	.	X
cana-2991	430	20	)	)	PUNCT
cana-2991	430	21	.	.	PUNCT
cana-2991	431	1	roberta	roberta	PROPN
cana-2991	431	2	(	(	PUNCT
cana-2991	431	3	robustly	robustly	ADV
cana-2991	431	4	optimized	optimize	VERB
cana-2991	431	5	bert	bert	PROPN
cana-2991	431	6	pre	pre	ADJ
cana-2991	431	7	training	training	NOUN
cana-2991	431	8	approach	approach	NOUN
cana-2991	431	9	)	)	PUNCT
cana-2991	431	10	improves	improve	VERB
cana-2991	431	11	over	over	ADP
cana-2991	431	12	bert	bert	PROPN
cana-2991	431	13	as	as	SCONJ
cana-2991	431	14	it	it	PRON
cana-2991	431	15	trains	train	VERB
cana-2991	431	16	on	on	ADP
cana-2991	431	17	longer	long	ADJ
cana-2991	431	18	sequences	sequence	NOUN
cana-2991	431	19	and	and	CCONJ
cana-2991	431	20	with	with	ADP
cana-2991	431	21	larger	large	ADJ
cana-2991	431	22	mini	mini	NOUN
cana-2991	431	23	-	-	NOUN
cana-2991	431	24	batches	batch	NOUN
cana-2991	431	25	,	,	PUNCT
cana-2991	431	26	while	while	SCONJ
cana-2991	431	27	recent	recent	ADJ
cana-2991	431	28	versions	version	NOUN
cana-2991	431	29	of	of	ADP
cana-2991	431	30	gpt	gpt	NOUN
cana-2991	431	31	(	(	PUNCT
cana-2991	431	32	generative	generative	ADJ
cana-2991	431	33	pretrained	pretraine	VERB
cana-2991	431	34	transformer	transformer	NOUN
cana-2991	431	35	)	)	PUNCT
cana-2991	431	36	models	model	NOUN
cana-2991	431	37	can	can	AUX
cana-2991	431	38	generate	generate	VERB
cana-2991	431	39	text	text	NOUN
cana-2991	431	40	in	in	ADP
cana-2991	431	41	autoregressive	autoregressive	ADJ
cana-2991	431	42	model	model	NOUN
cana-2991	431	43	which	which	PRON
cana-2991	431	44	may	may	AUX
cana-2991	431	45	be	be	AUX
cana-2991	431	46	useful	useful	ADJ
cana-2991	431	47	to	to	PART
cana-2991	431	48	recognize	recognize	VERB
cana-2991	431	49	certain	certain	ADJ
cana-2991	431	50	types	type	NOUN
cana-2991	431	51	of	of	ADP
cana-2991	431	52	linguistic	linguistic	ADJ
cana-2991	431	53	manipulation	manipulation	NOUN
cana-2991	431	54	that	that	PRON
cana-2991	431	55	occur	occur	VERB
cana-2991	431	56	in	in	ADP
cana-2991	431	57	fake	fake	ADJ
cana-2991	431	58	news	news	NOUN
cana-2991	431	59	articles	article	NOUN
cana-2991	431	60	.	.	PUNCT
cana-2991	432	1	investigating	investigate	VERB
cana-2991	432	2	these	these	DET
cana-2991	432	3	approaches	approach	NOUN
cana-2991	432	4	could	could	AUX
cana-2991	432	5	lead	lead	VERB
cana-2991	432	6	to	to	ADP
cana-2991	432	7	additional	additional	ADJ
cana-2991	432	8	performance	performance	NOUN
cana-2991	432	9	benefits	benefit	NOUN
cana-2991	432	10	on	on	ADP
cana-2991	432	11	top	top	NOUN
cana-2991	432	12	of	of	ADP
cana-2991	432	13	the	the	DET
cana-2991	432	14	current	current	ADJ
cana-2991	432	15	state	state	NOUN
cana-2991	432	16	-	-	PUNCT
cana-2991	432	17	of	of	ADP
cana-2991	432	18	-	-	PUNCT
cana-2991	432	19	the	the	DET
cana-2991	432	20	-	-	PUNCT
cana-2991	432	21	art	art	NOUN
cana-2991	432	22	and	and	CCONJ
cana-2991	432	23	push	push	VERB
cana-2991	432	24	forward	forward	ADV
cana-2991	432	25	fake	fake	ADJ
cana-2991	432	26	news	news	NOUN
cana-2991	432	27	detection	detection	NOUN
cana-2991	432	28	research	research	NOUN
cana-2991	432	29	.	.	PUNCT
cana-2991	433	1	a	a	DET
cana-2991	433	2	further	further	ADJ
cana-2991	433	3	area	area	NOUN
cana-2991	433	4	for	for	ADP
cana-2991	433	5	future	future	ADJ
cana-2991	433	6	research	research	NOUN
cana-2991	433	7	could	could	AUX
cana-2991	433	8	involve	involve	VERB
cana-2991	433	9	designing	design	VERB
cana-2991	433	10	domain	domain	NOUN
cana-2991	433	11	-	-	PUNCT
cana-2991	433	12	specific	specific	ADJ
cana-2991	433	13	fake	fake	ADJ
cana-2991	433	14	news	news	NOUN
cana-2991	433	15	detection	detection	NOUN
cana-2991	433	16	models	model	NOUN
cana-2991	433	17	.	.	PUNCT
cana-2991	434	1	since	since	SCONJ
cana-2991	434	2	the	the	DET
cana-2991	434	3	fake	fake	ADJ
cana-2991	434	4	news	news	NOUN
cana-2991	434	5	is	be	AUX
cana-2991	434	6	diverse	diverse	ADJ
cana-2991	434	7	in	in	ADP
cana-2991	434	8	the	the	DET
cana-2991	434	9	domains	domain	NOUN
cana-2991	434	10	,	,	PUNCT
cana-2991	434	11	i.e.	i.e.	X
cana-2991	434	12	political	political	ADJ
cana-2991	434	13	,	,	PUNCT
cana-2991	434	14	health	health	NOUN
cana-2991	434	15	,	,	PUNCT
cana-2991	434	16	financial	financial	ADJ
cana-2991	434	17	and	and	CCONJ
cana-2991	434	18	entertainment	entertainment	NOUN
cana-2991	434	19	news	news	PROPN
cana-2991	434	20	etc	etc	X
cana-2991	434	21	.	.	X
cana-2991	434	22	,	,	PUNCT
cana-2991	434	23	there	there	PRON
cana-2991	434	24	may	may	AUX
cana-2991	434	25	be	be	AUX
cana-2991	434	26	many	many	ADJ
cana-2991	434	27	separable	separable	ADJ
cana-2991	434	28	representations	representation	NOUN
cana-2991	434	29	that	that	PRON
cana-2991	434	30	might	might	AUX
cana-2991	434	31	need	need	VERB
cana-2991	434	32	to	to	PART
cana-2991	434	33	be	be	AUX
cana-2991	434	34	learnt	learn	VERB
cana-2991	434	35	for	for	ADP
cana-2991	434	36	different	different	ADJ
cana-2991	434	37	domains	domain	NOUN
cana-2991	434	38	,	,	PUNCT
cana-2991	434	39	which	which	PRON
cana-2991	434	40	we	we	PRON
cana-2991	434	41	are	be	AUX
cana-2991	434	42	not	not	PART
cana-2991	434	43	capturing	capture	VERB
cana-2991	434	44	using	use	VERB
cana-2991	434	45	a	a	DET
cana-2991	434	46	broader	broad	ADJ
cana-2991	434	47	model	model	NOUN
cana-2991	434	48	where	where	SCONJ
cana-2991	434	49	all	all	PRON
cana-2991	434	50	of	of	ADP
cana-2991	434	51	the	the	DET
cana-2991	434	52	data	data	NOUN
cana-2991	434	53	points	point	NOUN
cana-2991	434	54	with	with	ADP
cana-2991	434	55	similar	similar	ADJ
cana-2991	434	56	label	label	NOUN
cana-2991	434	57	type	type	NOUN
cana-2991	434	58	have	have	VERB
cana-2991	434	59	similar	similar	ADJ
cana-2991	434	60	representations	representation	NOUN
cana-2991	434	61	.	.	PUNCT
cana-2991	435	1	for	for	ADP
cana-2991	435	2	example	example	NOUN
cana-2991	435	3	,	,	PUNCT
cana-2991	435	4	domain	domain	NOUN
cana-2991	435	5	-	-	PUNCT
cana-2991	435	6	specific	specific	ADJ
cana-2991	435	7	models	model	NOUN
cana-2991	435	8	could	could	AUX
cana-2991	435	9	learn	learn	VERB
cana-2991	435	10	specialized	specialized	ADJ
cana-2991	435	11	linguistic	linguistic	ADJ
cana-2991	435	12	and	and	CCONJ
cana-2991	435	13	contextual	contextual	ADJ
cana-2991	435	14	patterns	pattern	NOUN
cana-2991	435	15	for	for	ADP
cana-2991	435	16	different	different	ADJ
cana-2991	435	17	types	type	NOUN
cana-2991	435	18	of	of	ADP
cana-2991	435	19	misinformation	misinformation	NOUN
cana-2991	435	20	to	to	PART
cana-2991	435	21	better	well	ADV
cana-2991	435	22	guess	guess	VERB
cana-2991	435	23	the	the	DET
cana-2991	435	24	content	content	NOUN
cana-2991	435	25	type	type	NOUN
cana-2991	435	26	and	and	CCONJ
cana-2991	435	27	improve	improve	VERB
cana-2991	435	28	performance	performance	NOUN
cana-2991	435	29	.	.	PUNCT
cana-2991	436	1	while	while	SCONJ
cana-2991	436	2	health	health	NOUN
cana-2991	436	3	-	-	PUNCT
cana-2991	436	4	related	relate	VERB
cana-2991	436	5	fake	fake	ADJ
cana-2991	436	6	news	news	NOUN
cana-2991	436	7	often	often	ADV
cana-2991	436	8	uses	use	VERB
cana-2991	436	9	medical	medical	ADJ
cana-2991	436	10	jargon	jargon	NOUN
cana-2991	436	11	,	,	PUNCT
cana-2991	436	12	and	and	CCONJ
cana-2991	436	13	appeals	appeal	NOUN
cana-2991	436	14	to	to	ADP
cana-2991	436	15	the	the	DET
cana-2991	436	16	authority	authority	NOUN
cana-2991	436	17	with	with	ADP
cana-2991	436	18	fake	fake	ADJ
cana-2991	436	19	claims	claim	NOUN
cana-2991	436	20	from	from	ADP
cana-2991	436	21	supposed	suppose	VERB
cana-2991	436	22	doctors	doctor	NOUN
cana-2991	436	23	;	;	PUNCT
cana-2991	436	24	the	the	DET
cana-2991	436	25	political	political	ADJ
cana-2991	436	26	sphere	sphere	NOUN
cana-2991	436	27	has	have	VERB
cana-2991	436	28	a	a	DET
cana-2991	436	29	different	different	ADJ
cana-2991	436	30	type	type	NOUN
cana-2991	436	31	that	that	PRON
cana-2991	436	32	reaches	reach	VERB
cana-2991	436	33	at	at	ADP
cana-2991	436	34	emotions	emotion	NOUN
cana-2991	436	35	by	by	ADP
cana-2991	436	36	sensationalism	sensationalism	NOUN
cana-2991	436	37	.	.	PUNCT
cana-2991	437	1	finally	finally	ADV
cana-2991	437	2	,	,	PUNCT
cana-2991	437	3	we	we	PRON
cana-2991	437	4	also	also	ADV
cana-2991	437	5	could	could	AUX
cana-2991	437	6	integrate	integrate	VERB
cana-2991	437	7	to	to	ADP
cana-2991	437	8	our	our	PRON
cana-2991	437	9	system	system	NOUN
cana-2991	437	10	other	other	ADJ
cana-2991	437	11	source	source	NOUN
cana-2991	437	12	of	of	ADP
cana-2991	437	13	knowledge	knowledge	NOUN
cana-2991	437	14	as	as	ADP
cana-2991	437	15	future	future	ADJ
cana-2991	437	16	research	research	NOUN
cana-2991	437	17	work	work	NOUN
cana-2991	437	18	in	in	ADP
cana-2991	437	19	the	the	DET
cana-2991	437	20	fake	fake	ADJ
cana-2991	437	21	news	news	NOUN
cana-2991	437	22	detection	detection	NOUN
cana-2991	437	23	process	process	NOUN
cana-2991	437	24	.	.	PUNCT
cana-2991	438	1	while	while	SCONJ
cana-2991	438	2	this	this	DET
cana-2991	438	3	research	research	NOUN
cana-2991	438	4	was	be	AUX
cana-2991	438	5	confined	confine	VERB
cana-2991	438	6	only	only	ADV
cana-2991	438	7	to	to	ADP
cana-2991	438	8	text	text	NOUN
cana-2991	438	9	-	-	PUNCT
cana-2991	438	10	based	base	VERB
cana-2991	438	11	classification	classification	NOUN
cana-2991	438	12	,	,	PUNCT
cana-2991	438	13	we	we	PRON
cana-2991	438	14	can	can	AUX
cana-2991	438	15	boost	boost	VERB
cana-2991	438	16	the	the	DET
cana-2991	438	17	potential	potential	NOUN
cana-2991	438	18	of	of	ADP
cana-2991	438	19	this	this	DET
cana-2991	438	20	model	model	NOUN
cana-2991	438	21	by	by	ADP
cana-2991	438	22	incorporating	incorporate	VERB
cana-2991	438	23	knowledge	knowledge	NOUN
cana-2991	438	24	graphs	graph	NOUN
cana-2991	438	25	and	and	CCONJ
cana-2991	438	26	external	external	ADJ
cana-2991	438	27	repositories	repository	NOUN
cana-2991	438	28	containing	contain	VERB
cana-2991	438	29	facts	fact	NOUN
cana-2991	438	30	which	which	PRON
cana-2991	438	31	have	have	AUX
cana-2991	438	32	gone	go	VERB
cana-2991	438	33	through	through	ADP
cana-2991	438	34	some	some	DET
cana-2991	438	35	verification	verification	NOUN
cana-2991	438	36	,	,	PUNCT
cana-2991	438	37	in	in	ADP
cana-2991	438	38	detecting	detect	VERB
cana-2991	438	39	the	the	DET
cana-2991	438	40	fake	fake	ADJ
cana-2991	438	41	news	news	NOUN
cana-2991	438	42	.	.	PUNCT
cana-2991	439	1	for	for	ADP
cana-2991	439	2	example	example	NOUN
cana-2991	439	3	,	,	PUNCT
cana-2991	439	4	the	the	DET
cana-2991	439	5	model	model	NOUN
cana-2991	439	6	might	might	AUX
cana-2991	439	7	cross	cross	VERB
cana-2991	439	8	reference	reference	NOUN
cana-2991	439	9	news	news	NOUN
cana-2991	439	10	articles	article	NOUN
cana-2991	439	11	against	against	ADP
cana-2991	439	12	all	all	PRON
cana-2991	439	13	of	of	ADP
cana-2991	439	14	the	the	DET
cana-2991	439	15	scientific	scientific	ADJ
cana-2991	439	16	research	research	NOUN
cana-2991	439	17	papers	paper	NOUN
cana-2991	439	18	or	or	CCONJ
cana-2991	439	19	fact	fact	NOUN
cana-2991	439	20	-	-	PUNCT
cana-2991	439	21	check	check	NOUN
cana-2991	439	22	websites	website	NOUN
cana-2991	439	23	it	it	PRON
cana-2991	439	24	linked	link	VERB
cana-2991	439	25	to	to	ADP
cana-2991	439	26	in	in	ADP
cana-2991	439	27	our	our	PRON
cana-2991	439	28	previous	previous	ADJ
cana-2991	439	29	exercise	exercise	NOUN
cana-2991	439	30	to	to	PART
cana-2991	439	31	verify	verify	VERB
cana-2991	439	32	the	the	DET
cana-2991	439	33	claims	claim	NOUN
cana-2991	439	34	made	make	VERB
cana-2991	439	35	in	in	ADP
cana-2991	439	36	the	the	DET
cana-2991	439	37	news	news	NOUN
cana-2991	439	38	article	article	NOUN
cana-2991	439	39	.	.	PUNCT
cana-2991	440	1	communications	communication	NOUN
cana-2991	440	2	on	on	ADP
cana-2991	440	3	applied	apply	VERB
cana-2991	440	4	nonlinear	nonlinear	ADJ
cana-2991	440	5	analysis	analysis	NOUN
cana-2991	440	6	issn	issn	NOUN
cana-2991	440	7	:	:	PUNCT
cana-2991	440	8	1074	1074	NUM
cana-2991	440	9	-	-	PUNCT
cana-2991	440	10	133x	133x	NUM
cana-2991	440	11	vol	vol	NOUN
cana-2991	440	12	32	32	NUM
cana-2991	440	13	no	no	NOUN
cana-2991	440	14	.	.	PUNCT
cana-2991	441	1	5s	5s	NUM
cana-2991	441	2	(	(	PUNCT
cana-2991	441	3	2025	2025	NUM
cana-2991	441	4	)	)	PUNCT
cana-2991	441	5	175	175	NUM
cana-2991	441	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	441	7	this	this	PRON
cana-2991	441	8	also	also	ADV
cana-2991	441	9	brings	bring	VERB
cana-2991	441	10	up	up	ADP
cana-2991	441	11	the	the	DET
cana-2991	441	12	ethical	ethical	ADJ
cana-2991	441	13	concerns	concern	NOUN
cana-2991	441	14	with	with	ADP
cana-2991	441	15	fake	fake	ADJ
cana-2991	441	16	news	news	NOUN
cana-2991	441	17	detection	detection	NOUN
cana-2991	441	18	systems	system	NOUN
cana-2991	441	19	.	.	PUNCT
cana-2991	442	1	when	when	SCONJ
cana-2991	442	2	the	the	DET
cana-2991	442	3	automatic	automatic	ADJ
cana-2991	442	4	detection	detection	NOUN
cana-2991	442	5	system	system	NOUN
cana-2991	442	6	is	be	AUX
cana-2991	442	7	widely	widely	ADV
cana-2991	442	8	used	use	VERB
cana-2991	442	9	,	,	PUNCT
cana-2991	442	10	we	we	PRON
cana-2991	442	11	must	must	AUX
cana-2991	442	12	guarantee	guarantee	VERB
cana-2991	442	13	its	its	PRON
cana-2991	442	14	transparency	transparency	NOUN
cana-2991	442	15	,	,	PUNCT
cana-2991	442	16	fairness	fairness	NOUN
cana-2991	442	17	and	and	CCONJ
cana-2991	442	18	impartiality	impartiality	NOUN
cana-2991	442	19	.	.	PUNCT
cana-2991	443	1	further	further	ADJ
cana-2991	443	2	research	research	NOUN
cana-2991	443	3	needs	need	VERB
cana-2991	443	4	to	to	PART
cana-2991	443	5	be	be	AUX
cana-2991	443	6	conducted	conduct	VERB
cana-2991	443	7	in	in	ADP
cana-2991	443	8	developing	develop	VERB
cana-2991	443	9	explainable	explainable	ADJ
cana-2991	443	10	ai	ai	NOUN
cana-2991	443	11	(	(	PUNCT
cana-2991	443	12	xai	xai	PROPN
cana-2991	443	13	)	)	PUNCT
cana-2991	443	14	techniques	technique	NOUN
cana-2991	443	15	for	for	ADP
cana-2991	443	16	fake	fake	ADJ
cana-2991	443	17	news	news	NOUN
cana-2991	443	18	detection	detection	NOUN
cana-2991	443	19	cascaded	cascade	VERB
cana-2991	443	20	with	with	ADP
cana-2991	443	21	reasons	reason	NOUN
cana-2991	443	22	why	why	SCONJ
cana-2991	443	23	articles	article	NOUN
cana-2991	443	24	are	be	AUX
cana-2991	443	25	flagged	flag	VERB
cana-2991	443	26	as	as	ADP
cana-2991	443	27	fake	fake	ADJ
cana-2991	443	28	.	.	PUNCT
cana-2991	444	1	there	there	PRON
cana-2991	444	2	are	be	VERB
cana-2991	444	3	also	also	ADV
cana-2991	444	4	attempts	attempt	NOUN
cana-2991	444	5	to	to	PART
cana-2991	444	6	make	make	VERB
cana-2991	444	7	sure	sure	ADJ
cana-2991	444	8	that	that	SCONJ
cana-2991	444	9	the	the	DET
cana-2991	444	10	system	system	NOUN
cana-2991	444	11	does	do	AUX
cana-2991	444	12	not	not	PART
cana-2991	444	13	end	end	VERB
cana-2991	444	14	up	up	ADP
cana-2991	444	15	censoring	censor	VERB
cana-2991	444	16	legitimate	legitimate	ADJ
cana-2991	444	17	content	content	NOUN
cana-2991	444	18	or	or	CCONJ
cana-2991	444	19	bias	bias	VERB
cana-2991	444	20	the	the	DET
cana-2991	444	21	news	news	NOUN
cana-2991	444	22	ecosystem	ecosystem	NOUN
cana-2991	444	23	in	in	ADP
cana-2991	444	24	some	some	DET
cana-2991	444	25	way	way	NOUN
cana-2991	444	26	.	.	PUNCT
cana-2991	445	1	to	to	PART
cana-2991	445	2	sum	sum	VERB
cana-2991	445	3	up	up	ADP
cana-2991	445	4	,	,	PUNCT
cana-2991	445	5	this	this	DET
cana-2991	445	6	paper	paper	NOUN
cana-2991	445	7	features	feature	VERB
cana-2991	445	8	a	a	DET
cana-2991	445	9	scalable	scalable	ADJ
cana-2991	445	10	and	and	CCONJ
cana-2991	445	11	efficient	efficient	ADJ
cana-2991	445	12	method	method	NOUN
cana-2991	445	13	to	to	PART
cana-2991	445	14	detect	detect	VERB
cana-2991	445	15	fake	fake	ADJ
cana-2991	445	16	news	news	NOUN
cana-2991	445	17	using	use	VERB
cana-2991	445	18	combined	combined	ADJ
cana-2991	445	19	word	word	NOUN
cana-2991	445	20	embedding	embed	VERB
cana-2991	445	21	models	model	NOUN
cana-2991	445	22	,	,	PUNCT
cana-2991	445	23	machine	machine	NOUN
cana-2991	445	24	learning	learn	VERB
cana-2991	445	25	classifiers	classifier	NOUN
cana-2991	445	26	,	,	PUNCT
cana-2991	445	27	and	and	CCONJ
cana-2991	445	28	distributed	distributed	ADJ
cana-2991	445	29	processing	processing	NOUN
cana-2991	445	30	.	.	PUNCT
cana-2991	446	1	this	this	PRON
cana-2991	446	2	is	be	AUX
cana-2991	446	3	a	a	DET
cana-2991	446	4	very	very	ADV
cana-2991	446	5	powerful	powerful	ADJ
cana-2991	446	6	result	result	NOUN
cana-2991	446	7	and	and	CCONJ
cana-2991	446	8	shows	show	VERB
cana-2991	446	9	that	that	SCONJ
cana-2991	446	10	models	model	NOUN
cana-2991	446	11	such	such	ADJ
cana-2991	446	12	as	as	ADP
cana-2991	446	13	bert	bert	PROPN
cana-2991	446	14	along	along	ADP
cana-2991	446	15	with	with	ADP
cana-2991	446	16	neural	neural	ADJ
cana-2991	446	17	networks	network	NOUN
cana-2991	446	18	have	have	VERB
cana-2991	446	19	the	the	DET
cana-2991	446	20	ability	ability	NOUN
cana-2991	446	21	to	to	PART
cana-2991	446	22	attain	attain	VERB
cana-2991	446	23	state	state	NOUN
cana-2991	446	24	-	-	PUNCT
cana-2991	446	25	of	of	ADP
cana-2991	446	26	-	-	PUNCT
cana-2991	446	27	the	the	DET
cana-2991	446	28	-	-	PUNCT
cana-2991	446	29	art	art	NOUN
cana-2991	446	30	accuracy	accuracy	NOUN
cana-2991	446	31	for	for	ADP
cana-2991	446	32	fake	fake	ADJ
cana-2991	446	33	news	news	NOUN
cana-2991	446	34	detection	detection	NOUN
cana-2991	446	35	;	;	PUNCT
cana-2991	446	36	providing	provide	VERB
cana-2991	446	37	significant	significant	ADJ
cana-2991	446	38	information	information	NOUN
cana-2991	446	39	in	in	ADP
cana-2991	446	40	the	the	DET
cana-2991	446	41	battle	battle	NOUN
cana-2991	446	42	against	against	ADP
cana-2991	446	43	misinformation	misinformation	NOUN
cana-2991	446	44	.	.	PUNCT
cana-2991	447	1	has	have	VERB
cana-2991	447	2	good	good	ADJ
cana-2991	447	3	scalability	scalability	NOUN
cana-2991	447	4	for	for	ADP
cana-2991	447	5	dealing	deal	VERB
cana-2991	447	6	with	with	ADP
cana-2991	447	7	massive	massive	ADJ
cana-2991	447	8	datasets	dataset	NOUN
cana-2991	447	9	in	in	ADP
cana-2991	447	10	production	production	NOUN
cana-2991	447	11	thanks	thank	NOUN
cana-2991	447	12	to	to	ADP
cana-2991	447	13	leveraging	leverage	VERB
cana-2991	447	14	distributed	distribute	VERB
cana-2991	447	15	processing	processing	NOUN
cana-2991	447	16	frameworks	framework	NOUN
cana-2991	447	17	,	,	PUNCT
cana-2991	447	18	thus	thus	ADV
cana-2991	447	19	supports	support	VERB
cana-2991	447	20	use	use	NOUN
cana-2991	447	21	-	-	PUNCT
cana-2991	447	22	cases	case	NOUN
cana-2991	447	23	like	like	ADP
cana-2991	447	24	social	social	ADJ
cana-2991	447	25	media	medium	NOUN
cana-2991	447	26	monitoring	monitoring	NOUN
cana-2991	447	27	,	,	PUNCT
cana-2991	447	28	news	news	NOUN
cana-2991	447	29	aggregations	aggregation	NOUN
cana-2991	447	30	and	and	CCONJ
cana-2991	447	31	fact	fact	NOUN
cana-2991	447	32	-	-	PUNCT
cana-2991	447	33	checker	checker	NOUN
cana-2991	447	34	variations	variation	NOUN
cana-2991	447	35	.	.	PUNCT
cana-2991	448	1	although	although	SCONJ
cana-2991	448	2	there	there	PRON
cana-2991	448	3	are	be	VERB
cana-2991	448	4	some	some	DET
cana-2991	448	5	challenges	challenge	NOUN
cana-2991	448	6	and	and	CCONJ
cana-2991	448	7	limitations	limitation	NOUN
cana-2991	448	8	,	,	PUNCT
cana-2991	448	9	such	such	ADJ
cana-2991	448	10	as	as	ADP
cana-2991	448	11	the	the	DET
cana-2991	448	12	computational	computational	ADJ
cana-2991	448	13	burden	burden	NOUN
cana-2991	448	14	of	of	ADP
cana-2991	448	15	advanced	advanced	ADJ
cana-2991	448	16	models	model	NOUN
cana-2991	448	17	and	and	CCONJ
cana-2991	448	18	the	the	DET
cana-2991	448	19	requirement	requirement	NOUN
cana-2991	448	20	for	for	ADP
cana-2991	448	21	large	large	ADJ
cana-2991	448	22	amounts	amount	NOUN
cana-2991	448	23	of	of	ADP
cana-2991	448	24	labeled	label	VERB
cana-2991	448	25	data	datum	NOUN
cana-2991	448	26	,	,	PUNCT
cana-2991	448	27	the	the	DET
cana-2991	448	28	proposed	propose	VERB
cana-2991	448	29	system	system	NOUN
cana-2991	448	30	presents	present	VERB
cana-2991	448	31	a	a	DET
cana-2991	448	32	promising	promising	ADJ
cana-2991	448	33	framework	framework	NOUN
cana-2991	448	34	to	to	PART
cana-2991	448	35	address	address	VERB
cana-2991	448	36	the	the	DET
cana-2991	448	37	issue	issue	NOUN
cana-2991	448	38	of	of	ADP
cana-2991	448	39	fake	fake	ADJ
cana-2991	448	40	news	news	NOUN
cana-2991	448	41	at	at	ADP
cana-2991	448	42	scale	scale	NOUN
cana-2991	448	43	.	.	PUNCT
cana-2991	449	1	the	the	DET
cana-2991	449	2	modularity	modularity	NOUN
cana-2991	449	3	of	of	ADP
cana-2991	449	4	the	the	DET
cana-2991	449	5	system	system	NOUN
cana-2991	449	6	opens	open	VERB
cana-2991	449	7	a	a	DET
cana-2991	449	8	range	range	NOUN
cana-2991	449	9	of	of	ADP
cana-2991	449	10	opportunities	opportunity	NOUN
cana-2991	449	11	for	for	ADP
cana-2991	449	12	future	future	ADJ
cana-2991	449	13	enhancement	enhancement	NOUN
cana-2991	449	14	,	,	PUNCT
cana-2991	449	15	including	include	VERB
cana-2991	449	16	the	the	DET
cana-2991	449	17	use	use	NOUN
cana-2991	449	18	of	of	ADP
cana-2991	449	19	newer	new	ADJ
cana-2991	449	20	models	model	NOUN
cana-2991	449	21	for	for	ADP
cana-2991	449	22	embedding	embed	VERB
cana-2991	449	23	,	,	PUNCT
cana-2991	449	24	training	train	VERB
cana-2991	449	25	the	the	DET
cana-2991	449	26	system	system	NOUN
cana-2991	449	27	with	with	ADP
cana-2991	449	28	domain	domain	NOUN
cana-2991	449	29	-	-	PUNCT
cana-2991	449	30	specific	specific	ADJ
cana-2991	449	31	data	datum	NOUN
cana-2991	449	32	,	,	PUNCT
cana-2991	449	33	and	and	CCONJ
cana-2991	449	34	integrating	integrate	VERB
cana-2991	449	35	external	external	ADJ
cana-2991	449	36	sources	source	NOUN
cana-2991	449	37	of	of	ADP
cana-2991	449	38	knowledge	knowledge	NOUN
cana-2991	449	39	.	.	PUNCT
cana-2991	450	1	eventually	eventually	ADV
cana-2991	450	2	,	,	PUNCT
cana-2991	450	3	the	the	DET
cana-2991	450	4	findings	finding	NOUN
cana-2991	450	5	of	of	ADP
cana-2991	450	6	this	this	DET
cana-2991	450	7	paper	paper	NOUN
cana-2991	450	8	are	be	AUX
cana-2991	450	9	a	a	DET
cana-2991	450	10	valuable	valuable	ADJ
cana-2991	450	11	addition	addition	NOUN
cana-2991	450	12	to	to	ADP
cana-2991	450	13	the	the	DET
cana-2991	450	14	field	field	NOUN
cana-2991	450	15	of	of	ADP
cana-2991	450	16	fighting	fight	VERB
cana-2991	450	17	disinformation	disinformation	NOUN
cana-2991	450	18	that	that	PRON
cana-2991	450	19	offers	offer	VERB
cana-2991	450	20	a	a	DET
cana-2991	450	21	reliable	reliable	ADJ
cana-2991	450	22	,	,	PUNCT
cana-2991	450	23	scalable	scalable	ADJ
cana-2991	450	24	solution	solution	NOUN
cana-2991	450	25	to	to	ADP
cana-2991	450	26	the	the	DET
cana-2991	450	27	challenge	challenge	NOUN
cana-2991	450	28	of	of	ADP
cana-2991	450	29	fake	fake	ADJ
cana-2991	450	30	news	news	NOUN
cana-2991	450	31	detection	detection	NOUN
cana-2991	450	32	in	in	ADP
cana-2991	450	33	the	the	DET
cana-2991	450	34	modern	modern	ADJ
cana-2991	450	35	digital	digital	ADJ
cana-2991	450	36	era	era	NOUN
cana-2991	450	37	.	.	PUNCT
cana-2991	451	1	by	by	ADP
cana-2991	451	2	combining	combine	VERB
cana-2991	451	3	these	these	DET
cana-2991	451	4	strengths	strength	NOUN
cana-2991	451	5	to	to	PART
cana-2991	451	6	build	build	VERB
cana-2991	451	7	on	on	ADP
cana-2991	451	8	the	the	DET
cana-2991	451	9	state	state	NOUN
cana-2991	451	10	of	of	ADP
cana-2991	451	11	the	the	DET
cana-2991	451	12	art	art	NOUN
cana-2991	451	13	of	of	ADP
cana-2991	451	14	fake	fake	ADJ
cana-2991	451	15	news	news	NOUN
cana-2991	451	16	detection	detection	NOUN
cana-2991	451	17	systems	system	NOUN
cana-2991	451	18	,	,	PUNCT
cana-2991	451	19	this	this	DET
cana-2991	451	20	research	research	NOUN
cana-2991	451	21	serves	serve	VERB
cana-2991	451	22	as	as	ADP
cana-2991	451	23	a	a	DET
cana-2991	451	24	platform	platform	NOUN
cana-2991	451	25	for	for	ADP
cana-2991	451	26	future	future	ADJ
cana-2991	451	27	research	research	NOUN
cana-2991	451	28	efforts	effort	NOUN
cana-2991	451	29	in	in	ADP
cana-2991	451	30	combating	combat	VERB
cana-2991	451	31	new	new	ADJ
cana-2991	451	32	manifestations	manifestation	NOUN
cana-2991	451	33	of	of	ADP
cana-2991	451	34	misinformation	misinformation	NOUN
cana-2991	451	35	as	as	SCONJ
cana-2991	451	36	they	they	PRON
cana-2991	451	37	continue	continue	VERB
cana-2991	451	38	to	to	PART
cana-2991	451	39	evolve	evolve	VERB
cana-2991	451	40	.	.	PUNCT
cana-2991	452	1	our	our	PRON
cana-2991	452	2	next	next	ADJ
cana-2991	452	3	steps	step	NOUN
cana-2991	452	4	on	on	ADP
cana-2991	452	5	this	this	DET
cana-2991	452	6	journey	journey	NOUN
cana-2991	452	7	will	will	AUX
cana-2991	452	8	involve	involve	VERB
cana-2991	452	9	fine	fine	ADV
cana-2991	452	10	-	-	PUNCT
cana-2991	452	11	tuning	tune	VERB
cana-2991	452	12	our	our	PRON
cana-2991	452	13	models	model	NOUN
cana-2991	452	14	and	and	CCONJ
cana-2991	452	15	extending	extend	VERB
cana-2991	452	16	their	their	PRON
cana-2991	452	17	application	application	NOUN
cana-2991	452	18	to	to	ADP
cana-2991	452	19	new	new	ADJ
cana-2991	452	20	domains	domain	NOUN
cana-2991	452	21	,	,	PUNCT
cana-2991	452	22	ensuring	ensure	VERB
cana-2991	452	23	that	that	SCONJ
cana-2991	452	24	the	the	DET
cana-2991	452	25	systems	system	NOUN
cana-2991	452	26	we	we	PRON
cana-2991	452	27	create	create	VERB
cana-2991	452	28	are	be	AUX
cana-2991	452	29	transparent	transparent	ADJ
cana-2991	452	30	,	,	PUNCT
cana-2991	452	31	ethical	ethical	ADJ
cana-2991	452	32	,	,	PUNCT
cana-2991	452	33	and	and	CCONJ
cana-2991	452	34	powerful	powerful	ADJ
cana-2991	452	35	enough	enough	ADV
cana-2991	452	36	to	to	PART
cana-2991	452	37	meet	meet	VERB
cana-2991	452	38	the	the	DET
cana-2991	452	39	demands	demand	NOUN
cana-2991	452	40	of	of	ADP
cana-2991	452	41	an	an	DET
cana-2991	452	42	increasingly	increasingly	ADV
cana-2991	452	43	sophisticated	sophisticated	ADJ
cana-2991	452	44	information	information	NOUN
cana-2991	452	45	ecology	ecology	NOUN
cana-2991	452	46	.	.	PUNCT
cana-2991	453	1	references	reference	NOUN
cana-2991	453	2	:	:	PUNCT
cana-2991	454	1	[	[	X
cana-2991	454	2	1	1	X
cana-2991	454	3	]	]	X
cana-2991	454	4	david	david	PROPN
cana-2991	454	5	mj	mj	PROPN
cana-2991	454	6	lazer	lazer	PROPN
cana-2991	454	7	,	,	PUNCT
cana-2991	454	8	matthew	matthew	PROPN
cana-2991	454	9	a	a	DET
cana-2991	454	10	baum	baum	PROPN
cana-2991	454	11	,	,	PUNCT
cana-2991	454	12	yochai	yochai	PROPN
cana-2991	454	13	benkler	benkler	NOUN
cana-2991	454	14	,	,	PUNCT
cana-2991	454	15	adam	adam	PROPN
cana-2991	454	16	j	j	PROPN
cana-2991	454	17	berinsky	berinsky	PROPN
cana-2991	454	18	,	,	PUNCT
cana-2991	454	19	kelly	kelly	PROPN
cana-2991	454	20	m	m	PROPN
cana-2991	454	21	greenhill	greenhill	PROPN
cana-2991	454	22	,	,	PUNCT
cana-2991	454	23	filippo	filippo	PROPN
cana-2991	454	24	menczer	menczer	NOUN
cana-2991	454	25	,	,	PUNCT
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cana-2991	454	27	j	j	PROPN
cana-2991	454	28	metzger	metzger	PROPN
cana-2991	454	29	,	,	PUNCT
cana-2991	454	30	brendan	brendan	PROPN
cana-2991	454	31	nyhan	nyhan	PROPN
cana-2991	454	32	,	,	PUNCT
cana-2991	454	33	gordon	gordon	PROPN
cana-2991	454	34	pennycook	pennycook	PROPN
cana-2991	454	35	,	,	PUNCT
cana-2991	454	36	david	david	PROPN
cana-2991	454	37	rothschild	rothschild	PROPN
cana-2991	454	38	,	,	PUNCT
cana-2991	454	39	et	et	PROPN
cana-2991	454	40	al	al	PROPN
cana-2991	454	41	.	.	PUNCT
cana-2991	455	1	the	the	DET
cana-2991	455	2	science	science	NOUN
cana-2991	455	3	of	of	ADP
cana-2991	455	4	fake	fake	ADJ
cana-2991	455	5	news	news	NOUN
cana-2991	455	6	.	.	PUNCT
cana-2991	456	1	science	science	NOUN
cana-2991	456	2	,	,	PUNCT
cana-2991	456	3	359(6380):1094–1096	359(6380):1094–1096	NUM
cana-2991	456	4	,	,	PUNCT
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cana-2991	456	6	.	.	PUNCT
cana-2991	457	1	[	[	X
cana-2991	457	2	2	2	NUM
cana-2991	457	3	]	]	PUNCT
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cana-2991	457	6	,	,	PUNCT
cana-2991	457	7	ullrich	ullrich	PROPN
cana-2991	457	8	kh	kh	PROPN
cana-2991	457	9	ecker	ecker	PROPN
cana-2991	457	10	,	,	PUNCT
cana-2991	457	11	and	and	CCONJ
cana-2991	457	12	john	john	PROPN
cana-2991	457	13	cook	cook	PROPN
cana-2991	457	14	.	.	PUNCT
cana-2991	458	1	beyond	beyond	ADP
cana-2991	458	2	misinformation	misinformation	NOUN
cana-2991	458	3	:	:	PUNCT
cana-2991	458	4	understanding	understanding	NOUN
cana-2991	458	5	and	and	CCONJ
cana-2991	458	6	coping	cope	VERB
cana-2991	458	7	with	with	ADP
cana-2991	458	8	the	the	DET
cana-2991	458	9	“	"	PUNCT
cana-2991	458	10	post	post	ADJ
cana-2991	458	11	-	-	ADJ
cana-2991	458	12	truth	truth	ADJ
cana-2991	458	13	”	"	PUNCT
cana-2991	458	14	era	era	NOUN
cana-2991	458	15	.	.	PUNCT
cana-2991	459	1	journal	journal	NOUN
cana-2991	459	2	of	of	ADP
cana-2991	459	3	applied	apply	VERB
cana-2991	459	4	research	research	NOUN
cana-2991	459	5	in	in	ADP
cana-2991	459	6	memory	memory	NOUN
cana-2991	459	7	and	and	CCONJ
cana-2991	459	8	cognition	cognition	NOUN
cana-2991	459	9	,	,	PUNCT
cana-2991	459	10	6(4):353–369	6(4):353–369	NUM
cana-2991	459	11	,	,	PUNCT
cana-2991	459	12	2017	2017	NUM
cana-2991	459	13	.	.	PUNCT
cana-2991	460	1	[	[	X
cana-2991	460	2	3	3	NUM
cana-2991	460	3	]	]	X
cana-2991	460	4	mallareddy	mallareddy	ADJ
cana-2991	460	5	,	,	PUNCT
cana-2991	460	6	a.	a.	NOUN
cana-2991	460	7	,	,	PUNCT
cana-2991	460	8	sridevi	sridevi	NOUN
cana-2991	460	9	,	,	PUNCT
cana-2991	460	10	r.	r.	PROPN
cana-2991	460	11	,	,	PUNCT
cana-2991	460	12	&	&	CCONJ
cana-2991	460	13	prasad	prasad	PROPN
cana-2991	460	14	,	,	PUNCT
cana-2991	460	15	c.	c.	PROPN
cana-2991	460	16	g.	g.	PROPN
cana-2991	460	17	v.	v.	PROPN
cana-2991	460	18	n.	n.	PROPN
cana-2991	460	19	(	(	PUNCT
cana-2991	460	20	2019	2019	NUM
cana-2991	460	21	)	)	PUNCT
cana-2991	460	22	.	.	PUNCT
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cana-2991	461	2	p	p	NOUN
cana-2991	461	3	-	-	PUNCT
cana-2991	461	4	gene	gene	NOUN
cana-2991	461	5	based	base	VERB
cana-2991	461	6	data	datum	NOUN
cana-2991	461	7	hiding	hide	VERB
cana-2991	461	8	for	for	ADP
cana-2991	461	9	data	datum	NOUN
cana-2991	461	10	security	security	NOUN
cana-2991	461	11	in	in	ADP
cana-2991	461	12	cloud	cloud	NOUN
cana-2991	461	13	.	.	PUNCT
cana-2991	462	1	international	international	ADJ
cana-2991	462	2	journal	journal	NOUN
cana-2991	462	3	of	of	ADP
cana-2991	462	4	recent	recent	ADJ
cana-2991	462	5	technology	technology	NOUN
cana-2991	462	6	and	and	CCONJ
cana-2991	462	7	engineering	engineering	NOUN
cana-2991	462	8	,	,	PUNCT
cana-2991	462	9	8(1	8(1	NOUN
cana-2991	462	10	)	)	PUNCT
cana-2991	462	11	,	,	PUNCT
cana-2991	462	12	2086	2086	NUM
cana-2991	462	13	-	-	SYM
cana-2991	462	14	2093	2093	NUM
cana-2991	462	15	.	.	PUNCT
cana-2991	463	1	[	[	X
cana-2991	463	2	4	4	NUM
cana-2991	463	3	]	]	X
cana-2991	463	4	prasad	prasad	PROPN
cana-2991	463	5	,	,	PUNCT
cana-2991	463	6	c.	c.	PROPN
cana-2991	463	7	g.	g.	PROPN
cana-2991	463	8	v.	v.	PROPN
cana-2991	463	9	n.	n.	PROPN
cana-2991	463	10	,	,	PUNCT
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cana-2991	463	12	,	,	PUNCT
cana-2991	463	13	a.	a.	NOUN
cana-2991	463	14	,	,	PUNCT
cana-2991	463	15	pounambal	pounambal	ADJ
cana-2991	463	16	,	,	PUNCT
cana-2991	463	17	m.	m.	NOUN
cana-2991	463	18	,	,	PUNCT
cana-2991	463	19	&	&	CCONJ
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cana-2991	463	21	,	,	PUNCT
cana-2991	463	22	v.	v.	PROPN
cana-2991	463	23	(	(	PUNCT
cana-2991	463	24	2022	2022	NUM
cana-2991	463	25	)	)	PUNCT
cana-2991	463	26	.	.	PUNCT
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cana-2991	464	2	computing	computing	NOUN
cana-2991	464	3	and	and	CCONJ
cana-2991	464	4	blockchain	blockchain	PROPN
cana-2991	464	5	in	in	ADP
cana-2991	464	6	smart	smart	ADJ
cana-2991	464	7	agriculture	agriculture	NOUN
cana-2991	464	8	systems	system	NOUN
cana-2991	464	9	.	.	PUNCT
cana-2991	465	1	international	international	ADJ
cana-2991	465	2	journal	journal	PROPN
cana-2991	465	3	on	on	ADP
cana-2991	465	4	recent	recent	ADJ
cana-2991	465	5	and	and	CCONJ
cana-2991	465	6	innovation	innovation	NOUN
cana-2991	465	7	trends	trend	NOUN
cana-2991	465	8	in	in	ADP
cana-2991	465	9	computing	computing	NOUN
cana-2991	465	10	and	and	CCONJ
cana-2991	465	11	communication	communication	NOUN
cana-2991	465	12	,	,	PUNCT
cana-2991	465	13	10(1	10(1	NUM
cana-2991	465	14	)	)	PUNCT
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cana-2991	465	17	-	-	SYM
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cana-2991	465	19	.	.	PUNCT
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cana-2991	466	2	5	5	NUM
cana-2991	466	3	]	]	PUNCT
cana-2991	466	4	diaa	diaa	ADJ
cana-2991	466	5	salama	salama	PROPN
cana-2991	466	6	abdelminaam	abdelminaam	PROPN
cana-2991	466	7	,	,	PUNCT
cana-2991	466	8	fatma	fatma	PROPN
cana-2991	466	9	helmy	helmy	PROPN
cana-2991	466	10	ismail	ismail	PROPN
cana-2991	466	11	,	,	PUNCT
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cana-2991	466	14	,	,	PUNCT
cana-2991	466	15	ahmed	ahmed	PROPN
cana-2991	466	16	taha	taha	PROPN
cana-2991	466	17	,	,	PUNCT
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cana-2991	466	19	h	h	PROPN
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cana-2991	466	21	,	,	PUNCT
cana-2991	466	22	and	and	CCONJ
cana-2991	466	23	ayman	ayman	PROPN
cana-2991	466	24	nabil	nabil	PROPN
cana-2991	466	25	.	.	PUNCT
cana-2991	467	1	coaid	coaid	VERB
cana-2991	467	2	-	-	PUNCT
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cana-2991	467	4	:	:	PUNCT
cana-2991	467	5	an	an	DET
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cana-2991	467	7	intelligent	intelligent	ADJ
cana-2991	467	8	framework	framework	NOUN
cana-2991	467	9	for	for	ADP
cana-2991	467	10	automated	automate	VERB
cana-2991	467	11	detecting	detect	VERB
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cana-2991	467	13	misleading	mislead	VERB
cana-2991	467	14	information	information	NOUN
cana-2991	467	15	on	on	ADP
cana-2991	467	16	twitter	twitter	NOUN
cana-2991	467	17	.	.	PUNCT
cana-2991	468	1	ieee	ieee	NOUN
cana-2991	468	2	access	access	NOUN
cana-2991	468	3	,	,	PUNCT
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cana-2991	468	5	,	,	PUNCT
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cana-2991	468	7	.	.	PUNCT
cana-2991	469	1	[	[	X
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cana-2991	469	3	]	]	X
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cana-2991	469	7	,	,	PUNCT
cana-2991	469	8	saeedeh	saeedeh	ADJ
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cana-2991	469	10	,	,	PUNCT
cana-2991	469	11	and	and	CCONJ
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cana-2991	469	14	.	.	PUNCT
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cana-2991	470	4	with	with	ADP
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cana-2991	470	7	networks	network	NOUN
cana-2991	470	8	.	.	PUNCT
cana-2991	471	1	applied	apply	VERB
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cana-2991	471	4	,	,	PUNCT
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cana-2991	471	6	,	,	PUNCT
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cana-2991	471	8	.	.	PUNCT
cana-2991	472	1	[	[	X
cana-2991	472	2	7	7	X
cana-2991	472	3	]	]	X
cana-2991	472	4	ciprian	ciprian	ADJ
cana-2991	472	5	-	-	PUNCT
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cana-2991	472	7	truică	truică	NOUN
cana-2991	472	8	and	and	CCONJ
cana-2991	472	9	elena	elena	NOUN
cana-2991	472	10	-	-	PUNCT
cana-2991	472	11	simona	simona	PROPN
cana-2991	472	12	apostol	apostol	NOUN
cana-2991	472	13	.	.	PUNCT
cana-2991	473	1	it	it	PRON
cana-2991	473	2	’s	’	VERB
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cana-2991	473	4	in	in	ADP
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cana-2991	473	6	embedding	embed	VERB
cana-2991	473	7	!	!	PUNCT
cana-2991	474	1	fake	fake	ADJ
cana-2991	474	2	news	news	NOUN
cana-2991	474	3	detection	detection	NOUN
cana-2991	474	4	using	use	VERB
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cana-2991	474	7	.	.	PUNCT
cana-2991	475	1	mathematics	mathematic	NOUN
cana-2991	475	2	,	,	PUNCT
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cana-2991	475	4	,	,	PUNCT
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cana-2991	475	6	.	.	PUNCT
cana-2991	476	1	communications	communication	NOUN
cana-2991	476	2	on	on	ADP
cana-2991	476	3	applied	apply	VERB
cana-2991	476	4	nonlinear	nonlinear	ADJ
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cana-2991	476	6	issn	issn	NOUN
cana-2991	476	7	:	:	PUNCT
cana-2991	476	8	1074	1074	NUM
cana-2991	476	9	-	-	PUNCT
cana-2991	476	10	133x	133x	NUM
cana-2991	476	11	vol	vol	NOUN
cana-2991	476	12	32	32	NUM
cana-2991	476	13	no	no	NOUN
cana-2991	476	14	.	.	PUNCT
cana-2991	477	1	5s	5s	NUM
cana-2991	477	2	(	(	PUNCT
cana-2991	477	3	2025	2025	NUM
cana-2991	477	4	)	)	PUNCT
cana-2991	477	5	176	176	NUM
cana-2991	477	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	478	1	[	[	X
cana-2991	478	2	8	8	NUM
cana-2991	478	3	]	]	PUNCT
cana-2991	478	4	liwen	liwen	PROPN
cana-2991	478	5	peng	peng	PROPN
cana-2991	478	6	,	,	PUNCT
cana-2991	478	7	songlei	songlei	PROPN
cana-2991	478	8	jian	jian	PROPN
cana-2991	478	9	,	,	PUNCT
cana-2991	478	10	zhigang	zhigang	PROPN
cana-2991	478	11	kan	kan	PROPN
cana-2991	478	12	,	,	PUNCT
cana-2991	478	13	linbo	linbo	PROPN
cana-2991	478	14	qiao	qiao	PROPN
cana-2991	478	15	,	,	PUNCT
cana-2991	478	16	and	and	CCONJ
cana-2991	478	17	dongsheng	dongsheng	PROPN
cana-2991	478	18	li	li	PROPN
cana-2991	478	19	.	.	PUNCT
cana-2991	478	20	not	not	PART
cana-2991	478	21	all	all	DET
cana-2991	478	22	fake	fake	ADJ
cana-2991	478	23	news	news	NOUN
cana-2991	478	24	is	be	AUX
cana-2991	478	25	semantically	semantically	ADV
cana-2991	478	26	similar	similar	ADJ
cana-2991	478	27	:	:	PUNCT
cana-2991	478	28	contextual	contextual	ADJ
cana-2991	478	29	semantic	semantic	ADJ
cana-2991	478	30	representation	representation	NOUN
cana-2991	478	31	learning	learn	VERB
cana-2991	478	32	for	for	ADP
cana-2991	478	33	multimodal	multimodal	ADJ
cana-2991	478	34	fake	fake	ADJ
cana-2991	478	35	news	news	NOUN
cana-2991	478	36	detection	detection	NOUN
cana-2991	478	37	.	.	PUNCT
cana-2991	479	1	information	information	NOUN
cana-2991	479	2	processing	processing	NOUN
cana-2991	479	3	&	&	CCONJ
cana-2991	479	4	management	management	NOUN
cana-2991	479	5	,	,	PUNCT
cana-2991	479	6	61(1):103564	61(1):103564	NUM
cana-2991	479	7	,	,	PUNCT
cana-2991	479	8	2024	2024	NUM
cana-2991	479	9	.	.	PUNCT
cana-2991	480	1	[	[	X
cana-2991	480	2	9	9	NUM
cana-2991	480	3	]	]	PUNCT
cana-2991	480	4	mayank	mayank	PROPN
cana-2991	480	5	kumar	kumar	PROPN
cana-2991	480	6	jain	jain	PROPN
cana-2991	480	7	,	,	PUNCT
cana-2991	480	8	dinesh	dinesh	PROPN
cana-2991	480	9	gopalani	gopalani	PROPN
cana-2991	480	10	,	,	PUNCT
cana-2991	480	11	and	and	CCONJ
cana-2991	480	12	yogesh	yogesh	PROPN
cana-2991	480	13	kumar	kumar	PROPN
cana-2991	480	14	meena	meena	PROPN
cana-2991	480	15	.	.	PUNCT
cana-2991	480	16	confake	confake	PROPN
cana-2991	480	17	:	:	PUNCT
cana-2991	480	18	fake	fake	ADJ
cana-2991	480	19	news	news	NOUN
cana-2991	480	20	identification	identification	NOUN
cana-2991	480	21	using	use	VERB
cana-2991	480	22	content	content	NOUN
cana-2991	480	23	based	base	VERB
cana-2991	480	24	features	feature	NOUN
cana-2991	480	25	.	.	PUNCT
cana-2991	481	1	multimedia	multimedia	NOUN
cana-2991	481	2	tools	tool	NOUN
cana-2991	481	3	and	and	CCONJ
cana-2991	481	4	applications	application	NOUN
cana-2991	481	5	,	,	PUNCT
cana-2991	481	6	83(3):8729–8755	83(3):8729–8755	NUM
cana-2991	481	7	,	,	PUNCT
cana-2991	481	8	2024	2024	NUM
cana-2991	481	9	.	.	PUNCT
cana-2991	482	1	[	[	X
cana-2991	482	2	10	10	NUM
cana-2991	482	3	]	]	X
cana-2991	482	4	jianqiao	jianqiao	PROPN
cana-2991	482	5	lai	lai	PROPN
cana-2991	482	6	,	,	PUNCT
cana-2991	482	7	xinran	xinran	PROPN
cana-2991	482	8	yang	yang	PROPN
cana-2991	482	9	,	,	PUNCT
cana-2991	482	10	wenyue	wenyue	PROPN
cana-2991	482	11	luo	luo	PROPN
cana-2991	482	12	,	,	PUNCT
cana-2991	482	13	linjiang	linjiang	PROPN
cana-2991	482	14	zhou	zhou	PROPN
cana-2991	482	15	,	,	PUNCT
cana-2991	482	16	langchen	langchen	PROPN
cana-2991	482	17	li	li	PROPN
cana-2991	482	18	,	,	PUNCT
cana-2991	482	19	yongqi	yongqi	PROPN
cana-2991	482	20	wang	wang	PROPN
cana-2991	482	21	,	,	PUNCT
cana-2991	482	22	and	and	CCONJ
cana-2991	482	23	xiaochuan	xiaochuan	PROPN
cana-2991	482	24	shi	shi	PROPN
cana-2991	482	25	.	.	PUNCT
cana-2991	483	1	rumorllm	rumorllm	PROPN
cana-2991	483	2	:	:	PUNCT
cana-2991	483	3	a	a	DET
cana-2991	483	4	rumor	rumor	ADJ
cana-2991	483	5	large	large	ADJ
cana-2991	483	6	language	language	NOUN
cana-2991	483	7	model	model	NOUN
cana-2991	483	8	-	-	PUNCT
cana-2991	483	9	based	base	VERB
cana-2991	483	10	fake	fake	ADJ
cana-2991	483	11	-	-	PUNCT
cana-2991	483	12	news	news	NOUN
cana-2991	483	13	-	-	PUNCT
cana-2991	483	14	detection	detection	NOUN
cana-2991	483	15	data	data	NOUN
cana-2991	483	16	-	-	PUNCT
cana-2991	483	17	augmentation	augmentation	NOUN
cana-2991	483	18	approach	approach	NOUN
cana-2991	483	19	.	.	PUNCT
cana-2991	484	1	applied	apply	VERB
cana-2991	484	2	sciences	science	NOUN
cana-2991	484	3	,	,	PUNCT
cana-2991	484	4	14(8):3532	14(8):3532	NUM
cana-2991	484	5	,	,	PUNCT
cana-2991	484	6	2024	2024	NUM
cana-2991	484	7	.	.	PUNCT
cana-2991	485	1	[	[	X
cana-2991	485	2	11	11	NUM
cana-2991	485	3	]	]	X
cana-2991	485	4	kai	kai	PROPN
cana-2991	485	5	nakamura	nakamura	PROPN
cana-2991	485	6	,	,	PUNCT
cana-2991	485	7	sharon	sharon	PROPN
cana-2991	485	8	levy	levy	PROPN
cana-2991	485	9	,	,	PUNCT
cana-2991	485	10	and	and	CCONJ
cana-2991	485	11	william	william	PROPN
cana-2991	485	12	yang	yang	PROPN
cana-2991	485	13	wang	wang	PROPN
cana-2991	485	14	.	.	PUNCT
cana-2991	486	1	fakeddit	fakeddit	PROPN
cana-2991	486	2	:	:	PUNCT
cana-2991	486	3	a	a	DET
cana-2991	486	4	new	new	ADJ
cana-2991	486	5	multimodal	multimodal	ADJ
cana-2991	486	6	benchmark	benchmark	NOUN
cana-2991	486	7	dataset	dataset	NOUN
cana-2991	486	8	for	for	ADP
cana-2991	486	9	finegrained	finegraine	VERB
cana-2991	486	10	fake	fake	ADJ
cana-2991	486	11	news	news	NOUN
cana-2991	486	12	detection	detection	NOUN
cana-2991	486	13	.	.	PUNCT
cana-2991	487	1	in	in	ADP
cana-2991	487	2	nicoletta	nicoletta	PROPN
cana-2991	487	3	calzolari	calzolari	PROPN
cana-2991	487	4	,	,	PUNCT
cana-2991	487	5	frédéric	frédéric	ADJ
cana-2991	487	6	béchet	béchet	PROPN
cana-2991	487	7	,	,	PUNCT
cana-2991	487	8	philippe	philippe	PROPN
cana-2991	487	9	blache	blache	PROPN
cana-2991	487	10	,	,	PUNCT
cana-2991	487	11	khalid	khalid	PROPN
cana-2991	487	12	choukri	choukri	PROPN
cana-2991	487	13	,	,	PUNCT
cana-2991	487	14	christopher	christopher	PROPN
cana-2991	487	15	cieri	cieri	PROPN
cana-2991	487	16	,	,	PUNCT
cana-2991	487	17	thierry	thierry	PROPN
cana-2991	487	18	declerck	declerck	PROPN
cana-2991	487	19	,	,	PUNCT
cana-2991	487	20	sara	sara	PROPN
cana-2991	487	21	goggi	goggi	PROPN
cana-2991	487	22	,	,	PUNCT
cana-2991	487	23	hitoshi	hitoshi	PROPN
cana-2991	487	24	isahara	isahara	PROPN
cana-2991	487	25	,	,	PUNCT
cana-2991	487	26	bente	bente	PROPN
cana-2991	487	27	maegaard	maegaard	PROPN
cana-2991	487	28	,	,	PUNCT
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cana-2991	487	30	mariani	mariani	PROPN
cana-2991	487	31	,	,	PUNCT
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cana-2991	487	33	mazo	mazo	PROPN
cana-2991	487	34	,	,	PUNCT
cana-2991	487	35	asuncion	asuncion	PROPN
cana-2991	487	36	moreno	moreno	PROPN
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cana-2991	487	40	,	,	PUNCT
cana-2991	487	41	and	and	CCONJ
cana-2991	487	42	stelios	stelios	PROPN
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cana-2991	487	44	,	,	PUNCT
cana-2991	487	45	editors	editor	NOUN
cana-2991	487	46	,	,	PUNCT
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cana-2991	487	48	of	of	ADP
cana-2991	487	49	the	the	DET
cana-2991	487	50	twelfth	twelfth	ADJ
cana-2991	487	51	language	language	NOUN
cana-2991	487	52	resources	resource	NOUN
cana-2991	487	53	and	and	CCONJ
cana-2991	487	54	evaluation	evaluation	NOUN
cana-2991	487	55	conference	conference	NOUN
cana-2991	487	56	,	,	PUNCT
cana-2991	487	57	pages	page	NOUN
cana-2991	487	58	6149–6157	6149–6157	NOUN
cana-2991	487	59	,	,	PUNCT
cana-2991	487	60	marseille	marseille	PROPN
cana-2991	487	61	,	,	PUNCT
cana-2991	487	62	france	france	PROPN
cana-2991	487	63	,	,	PUNCT
cana-2991	487	64	may	may	AUX
cana-2991	487	65	2020	2020	NUM
cana-2991	487	66	.	.	PUNCT
cana-2991	488	1	european	european	ADJ
cana-2991	488	2	language	language	PROPN
cana-2991	488	3	resources	resource	NOUN
cana-2991	488	4	association	association	NOUN
cana-2991	488	5	.	.	PUNCT
cana-2991	489	1	[	[	X
cana-2991	489	2	12	12	NUM
cana-2991	489	3	]	]	X
cana-2991	489	4	guobiao	guobiao	PROPN
cana-2991	489	5	zhang	zhang	PROPN
cana-2991	489	6	,	,	PUNCT
cana-2991	489	7	anastasia	anastasia	PROPN
cana-2991	489	8	giachanou	giachanou	PROPN
cana-2991	489	9	,	,	PUNCT
cana-2991	489	10	and	and	CCONJ
cana-2991	489	11	paolo	paolo	PROPN
cana-2991	489	12	rosso	rosso	PROPN
cana-2991	489	13	.	.	PUNCT
cana-2991	489	14	scenefnd	scenefnd	NOUN
cana-2991	489	15	:	:	PUNCT
cana-2991	489	16	multimodal	multimodal	ADJ
cana-2991	489	17	fake	fake	ADJ
cana-2991	489	18	news	news	NOUN
cana-2991	489	19	detection	detection	NOUN
cana-2991	489	20	by	by	ADP
cana-2991	489	21	modelling	model	VERB
cana-2991	489	22	scene	scene	NOUN
cana-2991	489	23	context	context	PROPN
cana-2991	489	24	information	information	NOUN
cana-2991	489	25	.	.	PUNCT
cana-2991	490	1	journal	journal	NOUN
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cana-2991	490	4	science	science	NOUN
cana-2991	490	5	,	,	PUNCT
cana-2991	490	6	50(2):355–367	50(2):355–367	PROPN
cana-2991	490	7	,	,	PUNCT
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cana-2991	490	9	.	.	PUNCT
cana-2991	491	1	[	[	X
cana-2991	491	2	13	13	NUM
cana-2991	491	3	]	]	X
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cana-2991	491	5	,	,	PUNCT
cana-2991	491	6	b.	b.	PROPN
cana-2991	491	7	,	,	PUNCT
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cana-2991	491	9	,	,	PUNCT
cana-2991	491	10	a.	a.	PROPN
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cana-2991	491	12	,	,	PUNCT
cana-2991	491	13	&	&	CCONJ
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cana-2991	491	15	,	,	PUNCT
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cana-2991	491	17	(	(	PUNCT
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cana-2991	491	19	)	)	PUNCT
cana-2991	491	20	.	.	PUNCT
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cana-2991	492	7	butterfly	butterfly	NOUN
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cana-2991	492	9	algorithm	algorithm	NOUN
cana-2991	492	10	(	(	PUNCT
cana-2991	492	11	habc	habc	PROPN
cana-2991	492	12	-	-	PUNCT
cana-2991	492	13	mboa)-based	mboa)-base	VERB
cana-2991	492	14	cluster	cluster	NOUN
cana-2991	492	15	head	head	NOUN
cana-2991	492	16	selection	selection	NOUN
cana-2991	492	17	for	for	ADP
cana-2991	492	18	wsns	wsns	PROPN
cana-2991	492	19	.	.	PUNCT
cana-2991	493	1	journal	journal	PROPN
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cana-2991	493	6	and	and	CCONJ
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cana-2991	493	8	sciences	science	NOUN
cana-2991	493	9	,	,	PUNCT
cana-2991	493	10	34(5	34(5	PROPN
cana-2991	493	11	)	)	PUNCT
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cana-2991	493	14	-	-	SYM
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cana-2991	493	16	.	.	PUNCT
cana-2991	494	1	[	[	X
cana-2991	494	2	14	14	NUM
cana-2991	494	3	]	]	X
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cana-2991	494	5	,	,	PUNCT
cana-2991	494	6	s.	s.	PROPN
cana-2991	494	7	,	,	PUNCT
cana-2991	494	8	&	&	CCONJ
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cana-2991	494	10	,	,	PUNCT
cana-2991	494	11	b.	b.	PROPN
cana-2991	494	12	(	(	PUNCT
cana-2991	494	13	2022	2022	NUM
cana-2991	494	14	,	,	PUNCT
cana-2991	494	15	january	january	PROPN
cana-2991	494	16	)	)	PUNCT
cana-2991	494	17	.	.	PUNCT
cana-2991	495	1	improved	improve	VERB
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cana-2991	495	6	-	-	PUNCT
cana-2991	495	7	based	base	VERB
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cana-2991	495	10	for	for	ADP
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cana-2991	495	13	in	in	ADP
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cana-2991	495	17	(	(	PUNCT
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cana-2991	495	19	)	)	PUNCT
cana-2991	495	20	.	.	PUNCT
cana-2991	496	1	in	in	ADP
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cana-2991	496	5	conference	conference	NOUN
cana-2991	496	6	on	on	ADP
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cana-2991	496	9	in	in	ADP
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cana-2991	496	11	:	:	PUNCT
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cana-2991	496	18	-	-	SYM
cana-2991	496	19	808	808	NUM
cana-2991	496	20	)	)	PUNCT
cana-2991	496	21	.	.	PUNCT
cana-2991	497	1	singapore	singapore	PROPN
cana-2991	497	2	:	:	PUNCT
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cana-2991	497	6	.	.	PUNCT
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cana-2991	498	3	]	]	X
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cana-2991	498	9	,	,	PUNCT
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cana-2991	498	18	,	,	PUNCT
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cana-2991	498	21	,	,	PUNCT
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cana-2991	498	26	.	.	PUNCT
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cana-2991	499	6	in	in	ADP
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cana-2991	499	8	headlines	headline	NOUN
cana-2991	499	9	.	.	PUNCT
cana-2991	500	1	applied	apply	VERB
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cana-2991	500	3	,	,	PUNCT
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cana-2991	500	5	,	,	PUNCT
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cana-2991	500	7	.	.	PUNCT
cana-2991	501	1	[	[	X
cana-2991	501	2	16	16	NUM
cana-2991	501	3	]	]	X
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cana-2991	501	6	,	,	PUNCT
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cana-2991	501	22	.	.	PUNCT
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cana-2991	502	9	.	.	PUNCT
cana-2991	503	1	international	international	ADJ
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cana-2991	503	7	,	,	PUNCT
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cana-2991	503	9	,	,	PUNCT
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cana-2991	503	11	.	.	PUNCT
cana-2991	504	1	[	[	X
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cana-2991	504	3	]	]	X
cana-2991	504	4	olga	olga	PROPN
cana-2991	504	5	papadopoulou	papadopoulou	PROPN
cana-2991	504	6	,	,	PUNCT
cana-2991	504	7	markos	markos	PROPN
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cana-2991	504	9	,	,	PUNCT
cana-2991	504	10	symeon	symeon	NOUN
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cana-2991	504	13	and	and	CCONJ
cana-2991	504	14	ioannis	ioannis	PROPN
cana-2991	504	15	kompatsiaris	kompatsiaris	VERB
cana-2991	504	16	.	.	PUNCT
cana-2991	505	1	a	a	DET
cana-2991	505	2	corpus	corpus	NOUN
cana-2991	505	3	of	of	ADP
cana-2991	505	4	debunked	debunked	ADJ
cana-2991	505	5	and	and	CCONJ
cana-2991	505	6	verified	verified	ADJ
cana-2991	505	7	user	user	NOUN
cana-2991	505	8	-	-	PUNCT
cana-2991	505	9	generated	generate	VERB
cana-2991	505	10	videos	video	NOUN
cana-2991	505	11	.	.	PUNCT
cana-2991	506	1	online	online	PROPN
cana-2991	506	2	information	information	PROPN
cana-2991	506	3	review	review	PROPN
cana-2991	506	4	,	,	PUNCT
cana-2991	506	5	43(1):72–88	43(1):72–88	NUM
cana-2991	506	6	,	,	PUNCT
cana-2991	506	7	2019	2019	NUM
cana-2991	506	8	.	.	PUNCT
cana-2991	507	1	[	[	X
cana-2991	507	2	18	18	NUM
cana-2991	507	3	]	]	X
cana-2991	507	4	kai	kai	PROPN
cana-2991	507	5	shu	shu	PROPN
cana-2991	507	6	,	,	PUNCT
cana-2991	507	7	deepak	deepak	PROPN
cana-2991	507	8	mahudeswaran	mahudeswaran	PROPN
cana-2991	507	9	,	,	PUNCT
cana-2991	507	10	suhang	suhang	PROPN
cana-2991	507	11	wang	wang	PROPN
cana-2991	507	12	,	,	PUNCT
cana-2991	507	13	dongwon	dongwon	VERB
cana-2991	507	14	lee	lee	PROPN
cana-2991	507	15	,	,	PUNCT
cana-2991	507	16	and	and	CCONJ
cana-2991	507	17	huan	huan	PROPN
cana-2991	507	18	liu	liu	PROPN
cana-2991	507	19	.	.	PUNCT
cana-2991	508	1	fakenewsnet	fakenewsnet	PROPN
cana-2991	508	2	:	:	PUNCT
cana-2991	508	3	a	a	DET
cana-2991	508	4	data	data	NOUN
cana-2991	508	5	repository	repository	NOUN
cana-2991	508	6	with	with	ADP
cana-2991	508	7	news	news	NOUN
cana-2991	508	8	content	content	NOUN
cana-2991	508	9	,	,	PUNCT
cana-2991	508	10	social	social	ADJ
cana-2991	508	11	context	context	NOUN
cana-2991	508	12	and	and	CCONJ
cana-2991	508	13	dynamic	dynamic	ADJ
cana-2991	508	14	information	information	NOUN
cana-2991	508	15	for	for	ADP
cana-2991	508	16	studying	study	VERB
cana-2991	508	17	fake	fake	ADJ
cana-2991	508	18	news	news	NOUN
cana-2991	508	19	on	on	ADP
cana-2991	508	20	social	social	ADJ
cana-2991	508	21	media	medium	NOUN
cana-2991	508	22	.	.	PUNCT
cana-2991	509	1	arxiv	arxiv	PROPN
cana-2991	509	2	preprint	preprint	NOUN
cana-2991	509	3	arxiv:1809.01286	arxiv:1809.01286	VERB
cana-2991	509	4	,	,	PUNCT
cana-2991	509	5	2018	2018	NUM
cana-2991	509	6	.	.	PUNCT
cana-2991	510	1	[	[	X
cana-2991	510	2	19	19	NUM
cana-2991	510	3	]	]	PUNCT
cana-2991	510	4	dmytro	dmytro	NOUN
cana-2991	510	5	valiaiev	valiaiev	PROPN
cana-2991	510	6	.	.	PUNCT
cana-2991	511	1	detection	detection	NOUN
cana-2991	511	2	of	of	ADP
cana-2991	511	3	machine	machine	NOUN
cana-2991	511	4	-	-	PUNCT
cana-2991	511	5	generated	generate	VERB
cana-2991	511	6	text	text	NOUN
cana-2991	511	7	:	:	PUNCT
cana-2991	511	8	literature	literature	NOUN
cana-2991	511	9	survey	survey	NOUN
cana-2991	511	10	.	.	PUNCT
cana-2991	512	1	arxiv	arxiv	PROPN
cana-2991	512	2	preprint	preprint	NOUN
cana-2991	512	3	arxiv:2402.01642	arxiv:2402.01642	VERB
cana-2991	512	4	,	,	PUNCT
cana-2991	512	5	2024	2024	NUM
cana-2991	512	6	.	.	PUNCT
cana-2991	513	1	[	[	X
cana-2991	513	2	20	20	NUM
cana-2991	513	3	]	]	PUNCT
cana-2991	513	4	yuxia	yuxia	PROPN
cana-2991	513	5	wang	wang	PROPN
cana-2991	513	6	,	,	PUNCT
cana-2991	513	7	jonibek	jonibek	PROPN
cana-2991	513	8	mansurov	mansurov	PROPN
cana-2991	513	9	,	,	PUNCT
cana-2991	513	10	petar	petar	PROPN
cana-2991	513	11	ivanov	ivanov	PROPN
cana-2991	513	12	,	,	PUNCT
cana-2991	513	13	jinyan	jinyan	PROPN
cana-2991	513	14	su	su	PROPN
cana-2991	513	15	,	,	PUNCT
cana-2991	513	16	artem	artem	PROPN
cana-2991	513	17	shelmanov	shelmanov	NOUN
cana-2991	513	18	,	,	PUNCT
cana-2991	513	19	akim	akim	PROPN
cana-2991	513	20	tsvigun	tsvigun	PROPN
cana-2991	513	21	,	,	PUNCT
cana-2991	513	22	chenxi	chenxi	NOUN
cana-2991	513	23	whitehouse	whitehouse	NOUN
cana-2991	513	24	,	,	PUNCT
cana-2991	513	25	osama	osama	PROPN
cana-2991	513	26	mohammed	mohammed	PROPN
cana-2991	513	27	afzal	afzal	PROPN
cana-2991	513	28	,	,	PUNCT
cana-2991	513	29	tarek	tarek	PROPN
cana-2991	513	30	mahmoud	mahmoud	PROPN
cana-2991	513	31	,	,	PUNCT
cana-2991	513	32	toru	toru	PROPN
cana-2991	513	33	sasaki	sasaki	PROPN
cana-2991	513	34	,	,	PUNCT
cana-2991	513	35	thomas	thomas	PROPN
cana-2991	513	36	arnold	arnold	PROPN
cana-2991	513	37	,	,	PUNCT
cana-2991	513	38	alham	alham	PROPN
cana-2991	513	39	aji	aji	PROPN
cana-2991	513	40	,	,	PUNCT
cana-2991	513	41	nizar	nizar	PROPN
cana-2991	513	42	habash	habash	PROPN
cana-2991	513	43	,	,	PUNCT
cana-2991	513	44	iryna	iryna	NOUN
cana-2991	513	45	gurevych	gurevych	NOUN
cana-2991	513	46	,	,	PUNCT
cana-2991	513	47	and	and	CCONJ
cana-2991	513	48	preslav	preslav	NOUN
cana-2991	513	49	nakov	nakov	NOUN
cana-2991	513	50	.	.	PUNCT
cana-2991	514	1	m4	m4	VERB
cana-2991	514	2	:	:	PUNCT
cana-2991	514	3	multi	multi	ADJ
cana-2991	514	4	-	-	NOUN
cana-2991	514	5	generator	generator	ADJ
cana-2991	514	6	,	,	PUNCT
cana-2991	514	7	multi	multi	ADJ
cana-2991	514	8	-	-	NOUN
cana-2991	514	9	domain	domain	ADJ
cana-2991	514	10	,	,	PUNCT
cana-2991	514	11	and	and	CCONJ
cana-2991	514	12	multilingual	multilingual	ADJ
cana-2991	514	13	black	black	ADJ
cana-2991	514	14	-	-	PUNCT
cana-2991	514	15	box	box	NOUN
cana-2991	514	16	machine	machine	NOUN
cana-2991	514	17	-	-	PUNCT
cana-2991	514	18	generated	generate	VERB
cana-2991	514	19	text	text	NOUN
cana-2991	514	20	detection	detection	NOUN
cana-2991	514	21	.	.	PUNCT
cana-2991	515	1	in	in	ADP
cana-2991	515	2	yvette	yvette	PROPN
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cana-2991	515	4	and	and	CCONJ
cana-2991	515	5	matthew	matthew	PROPN
cana-2991	515	6	purver	purver	PROPN
cana-2991	515	7	,	,	PUNCT
cana-2991	515	8	editors	editor	NOUN
cana-2991	515	9	,	,	PUNCT
cana-2991	515	10	proceedings	proceeding	NOUN
cana-2991	515	11	of	of	ADP
cana-2991	515	12	the	the	DET
cana-2991	515	13	18th	18th	ADJ
cana-2991	515	14	conference	conference	NOUN
cana-2991	515	15	of	of	ADP
cana-2991	515	16	the	the	DET
cana-2991	515	17	european	european	ADJ
cana-2991	515	18	chapter	chapter	NOUN
cana-2991	515	19	of	of	ADP
cana-2991	515	20	the	the	DET
cana-2991	515	21	association	association	NOUN
cana-2991	515	22	for	for	ADP
cana-2991	515	23	computational	computational	ADJ
cana-2991	515	24	linguistics	linguistic	NOUN
cana-2991	515	25	(	(	PUNCT
cana-2991	515	26	volume	volume	NOUN
cana-2991	515	27	1	1	NUM
cana-2991	515	28	:	:	PUNCT
cana-2991	515	29	long	long	ADJ
cana-2991	515	30	papers	paper	NOUN
cana-2991	515	31	)	)	PUNCT
cana-2991	515	32	,	,	PUNCT
cana-2991	515	33	pages	page	NOUN
cana-2991	515	34	1369–1407	1369–1407	NUM
cana-2991	515	35	,	,	PUNCT
cana-2991	515	36	st	st	PROPN
cana-2991	515	37	.	.	PROPN
cana-2991	515	38	julian	julian	PROPN
cana-2991	515	39	’s	’s	PROPN
cana-2991	515	40	,	,	PUNCT
cana-2991	515	41	malta	malta	PROPN
cana-2991	515	42	,	,	PUNCT
cana-2991	515	43	march	march	PROPN
cana-2991	515	44	2024	2024	NUM
cana-2991	515	45	.	.	PUNCT
cana-2991	516	1	association	association	NOUN
cana-2991	516	2	for	for	ADP
cana-2991	516	3	computational	computational	ADJ
cana-2991	516	4	linguistics	linguistic	NOUN
cana-2991	516	5	.	.	PUNCT
cana-2991	517	1	[	[	X
cana-2991	517	2	21	21	NUM
cana-2991	517	3	]	]	SYM
cana-2991	517	4	medeswara	medeswara	PROPN
cana-2991	517	5	rao	rao	PROPN
cana-2991	517	6	kondamudi	kondamudi	PROPN
cana-2991	517	7	,	,	PUNCT
cana-2991	517	8	somya	somya	PROPN
cana-2991	517	9	ranjan	ranjan	PROPN
cana-2991	517	10	sahoo	sahoo	PROPN
cana-2991	517	11	,	,	PUNCT
cana-2991	517	12	lokesh	lokesh	PROPN
cana-2991	517	13	chouhan	chouhan	PROPN
cana-2991	517	14	,	,	PUNCT
cana-2991	517	15	and	and	CCONJ
cana-2991	517	16	nandakishor	nandakishor	PROPN
cana-2991	517	17	yadav	yadav	PROPN
cana-2991	517	18	.	.	PUNCT
cana-2991	518	1	a	a	DET
cana-2991	518	2	comprehensive	comprehensive	ADJ
cana-2991	518	3	survey	survey	NOUN
cana-2991	518	4	of	of	ADP
cana-2991	518	5	fake	fake	ADJ
cana-2991	518	6	news	news	NOUN
cana-2991	518	7	in	in	ADP
cana-2991	518	8	social	social	ADJ
cana-2991	518	9	networks	network	NOUN
cana-2991	518	10	:	:	PUNCT
cana-2991	518	11	attributes	attribute	NOUN
cana-2991	518	12	,	,	PUNCT
cana-2991	518	13	features	feature	NOUN
cana-2991	518	14	,	,	PUNCT
cana-2991	518	15	and	and	CCONJ
cana-2991	518	16	detection	detection	NOUN
cana-2991	518	17	approaches	approach	NOUN
cana-2991	518	18	.	.	PUNCT
cana-2991	519	1	journal	journal	NOUN
cana-2991	519	2	of	of	ADP
cana-2991	519	3	king	king	PROPN
cana-2991	519	4	saud	saud	PROPN
cana-2991	519	5	university	university	PROPN
cana-2991	519	6	-	-	PUNCT
cana-2991	519	7	computer	computer	NOUN
cana-2991	519	8	and	and	CCONJ
cana-2991	519	9	information	information	NOUN
cana-2991	519	10	sciences	science	NOUN
cana-2991	519	11	,	,	PUNCT
cana-2991	519	12	35(6):101571	35(6):101571	NUM
cana-2991	519	13	,	,	PUNCT
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cana-2991	519	15	.	.	PUNCT
cana-2991	520	1	[	[	X
cana-2991	520	2	22	22	NUM
cana-2991	520	3	]	]	X
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cana-2991	520	5	garg	garg	PROPN
cana-2991	520	6	and	and	CCONJ
cana-2991	520	7	dilip	dilip	PROPN
cana-2991	520	8	kumar	kumar	PROPN
cana-2991	520	9	sharma	sharma	PROPN
cana-2991	520	10	.	.	PUNCT
cana-2991	521	1	linguistic	linguistic	ADJ
cana-2991	521	2	features	feature	NOUN
cana-2991	521	3	based	base	VERB
cana-2991	521	4	framework	framework	NOUN
cana-2991	521	5	for	for	ADP
cana-2991	521	6	automatic	automatic	ADJ
cana-2991	521	7	fake	fake	ADJ
cana-2991	521	8	news	news	NOUN
cana-2991	521	9	detection	detection	NOUN
cana-2991	521	10	.	.	PUNCT
cana-2991	522	1	computers	computer	NOUN
cana-2991	522	2	&	&	CCONJ
cana-2991	522	3	industrial	industrial	ADJ
cana-2991	522	4	engineering	engineering	NOUN
cana-2991	522	5	,	,	PUNCT
cana-2991	522	6	172:108432	172:108432	NUM
cana-2991	522	7	,	,	PUNCT
cana-2991	522	8	2022	2022	NUM
cana-2991	522	9	.	.	PUNCT
cana-2991	523	1	[	[	X
cana-2991	523	2	23	23	NUM
cana-2991	523	3	]	]	X
cana-2991	523	4	anshika	anshika	PROPN
cana-2991	523	5	choudhary	choudhary	PROPN
cana-2991	523	6	and	and	CCONJ
cana-2991	523	7	anuja	anuja	PROPN
cana-2991	523	8	arora	arora	PROPN
cana-2991	523	9	.	.	PUNCT
cana-2991	524	1	linguistic	linguistic	ADJ
cana-2991	524	2	feature	feature	NOUN
cana-2991	524	3	based	base	VERB
cana-2991	524	4	learning	learn	VERB
cana-2991	524	5	model	model	NOUN
cana-2991	524	6	for	for	ADP
cana-2991	524	7	fake	fake	ADJ
cana-2991	524	8	news	news	NOUN
cana-2991	524	9	detection	detection	NOUN
cana-2991	524	10	and	and	CCONJ
cana-2991	524	11	classification	classification	NOUN
cana-2991	524	12	.	.	PUNCT
cana-2991	525	1	expert	expert	NOUN
cana-2991	525	2	systems	system	NOUN
cana-2991	525	3	with	with	ADP
cana-2991	525	4	applications	application	NOUN
cana-2991	525	5	,	,	PUNCT
cana-2991	525	6	169:114171	169:114171	NUM
cana-2991	525	7	,	,	PUNCT
cana-2991	525	8	2021	2021	NUM
cana-2991	525	9	.	.	PUNCT
cana-2991	526	1	[	[	X
cana-2991	526	2	24	24	NUM
cana-2991	526	3	]	]	PUNCT
cana-2991	526	4	abhijnan	abhijnan	NOUN
cana-2991	526	5	chakraborty	chakraborty	PROPN
cana-2991	526	6	,	,	PUNCT
cana-2991	526	7	bhargavi	bhargavi	NOUN
cana-2991	526	8	paranjape	paranjape	NOUN
cana-2991	526	9	,	,	PUNCT
cana-2991	526	10	sourya	sourya	NOUN
cana-2991	526	11	kakarla	kakarla	NOUN
cana-2991	526	12	,	,	PUNCT
cana-2991	526	13	and	and	CCONJ
cana-2991	526	14	niloy	niloy	PROPN
cana-2991	526	15	ganguly	ganguly	PROPN
cana-2991	526	16	.	.	PUNCT
cana-2991	527	1	stop	stop	AUX
cana-2991	527	2	clickbait	clickbait	PROPN
cana-2991	527	3	:	:	PUNCT
cana-2991	527	4	detecting	detect	VERB
cana-2991	527	5	and	and	CCONJ
cana-2991	527	6	preventing	prevent	VERB
cana-2991	527	7	clickbaits	clickbait	NOUN
cana-2991	527	8	in	in	ADP
cana-2991	527	9	online	online	ADJ
cana-2991	527	10	news	news	NOUN
cana-2991	527	11	media	medium	NOUN
cana-2991	527	12	.	.	PUNCT
cana-2991	528	1	in	in	ADP
cana-2991	528	2	2016	2016	NUM
cana-2991	528	3	ieee	ieee	NOUN
cana-2991	528	4	/	/	SYM
cana-2991	528	5	acm	acm	PROPN
cana-2991	528	6	international	international	ADJ
cana-2991	528	7	conference	conference	NOUN
cana-2991	528	8	on	on	ADP
cana-2991	528	9	advances	advance	NOUN
cana-2991	528	10	in	in	ADP
cana-2991	528	11	social	social	ADJ
cana-2991	528	12	networks	network	NOUN
cana-2991	528	13	analysis	analysis	NOUN
cana-2991	528	14	and	and	CCONJ
cana-2991	528	15	mining	mining	NOUN
cana-2991	528	16	(	(	PUNCT
cana-2991	528	17	asonam	asonam	PROPN
cana-2991	528	18	)	)	PUNCT
cana-2991	528	19	,	,	PUNCT
cana-2991	528	20	pages	page	VERB
cana-2991	528	21	9–16	9–16	PROPN
cana-2991	528	22	.	.	PUNCT
cana-2991	529	1	ieee	ieee	PROPN
cana-2991	529	2	,	,	PUNCT
cana-2991	529	3	2016	2016	NUM
cana-2991	529	4	.	.	PUNCT
cana-2991	530	1	[	[	X
cana-2991	530	2	25	25	NUM
cana-2991	530	3	]	]	PUNCT
cana-2991	530	4	arkaitz	arkaitz	PROPN
cana-2991	530	5	zubiaga	zubiaga	PROPN
cana-2991	530	6	,	,	PUNCT
cana-2991	530	7	maria	maria	PROPN
cana-2991	530	8	liakata	liakata	PROPN
cana-2991	530	9	,	,	PUNCT
cana-2991	530	10	rob	rob	PROPN
cana-2991	530	11	procter	procter	PROPN
cana-2991	530	12	,	,	PUNCT
cana-2991	530	13	geraldine	geraldine	PROPN
cana-2991	530	14	wong	wong	PROPN
cana-2991	530	15	sak	sak	PROPN
cana-2991	530	16	hoi	hoi	PROPN
cana-2991	530	17	,	,	PUNCT
cana-2991	530	18	and	and	CCONJ
cana-2991	530	19	peter	peter	PROPN
cana-2991	530	20	tolmie	tolmie	PROPN
cana-2991	530	21	.	.	PUNCT
cana-2991	531	1	analysing	analyse	VERB
cana-2991	531	2	how	how	SCONJ
cana-2991	531	3	people	people	NOUN
cana-2991	531	4	orient	orient	VERB
cana-2991	531	5	to	to	ADP
cana-2991	531	6	and	and	CCONJ
cana-2991	531	7	spread	spread	VERB
cana-2991	531	8	rumours	rumour	NOUN
cana-2991	531	9	in	in	ADP
cana-2991	531	10	social	social	ADJ
cana-2991	531	11	media	medium	NOUN
cana-2991	531	12	by	by	ADP
cana-2991	531	13	looking	look	VERB
cana-2991	531	14	at	at	ADP
cana-2991	531	15	conversational	conversational	ADJ
cana-2991	531	16	threads	thread	NOUN
cana-2991	531	17	.	.	PUNCT
cana-2991	532	1	plos	plos	PROPN
cana-2991	532	2	one	one	NUM
cana-2991	532	3	,	,	PUNCT
cana-2991	532	4	11(3):e0150989	11(3):e0150989	NUM
cana-2991	532	5	,	,	PUNCT
cana-2991	532	6	2016	2016	NUM
cana-2991	532	7	.	.	PUNCT
cana-2991	533	1	communications	communication	NOUN
cana-2991	533	2	on	on	ADP
cana-2991	533	3	applied	apply	VERB
cana-2991	533	4	nonlinear	nonlinear	ADJ
cana-2991	533	5	analysis	analysis	NOUN
cana-2991	533	6	issn	issn	NOUN
cana-2991	533	7	:	:	PUNCT
cana-2991	533	8	1074	1074	NUM
cana-2991	533	9	-	-	PUNCT
cana-2991	533	10	133x	133x	NUM
cana-2991	533	11	vol	vol	NOUN
cana-2991	533	12	32	32	NUM
cana-2991	533	13	no	no	NOUN
cana-2991	533	14	.	.	PUNCT
cana-2991	534	1	5s	5s	NUM
cana-2991	534	2	(	(	PUNCT
cana-2991	534	3	2025	2025	NUM
cana-2991	534	4	)	)	PUNCT
cana-2991	534	5	177	177	NUM
cana-2991	534	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2991	535	1	[	[	X
cana-2991	535	2	26	26	NUM
cana-2991	535	3	]	]	X
cana-2991	535	4	zhiwei	zhiwei	PROPN
cana-2991	535	5	jin	jin	PROPN
cana-2991	535	6	,	,	PUNCT
cana-2991	535	7	juan	juan	PROPN
cana-2991	535	8	cao	cao	PROPN
cana-2991	535	9	,	,	PUNCT
cana-2991	535	10	han	han	PROPN
cana-2991	535	11	guo	guo	PROPN
cana-2991	535	12	,	,	PUNCT
cana-2991	535	13	yongdong	yongdong	PROPN
cana-2991	535	14	zhang	zhang	PROPN
cana-2991	535	15	,	,	PUNCT
cana-2991	535	16	and	and	CCONJ
cana-2991	535	17	jiebo	jiebo	PROPN
cana-2991	535	18	luo	luo	PROPN
cana-2991	535	19	.	.	PUNCT
cana-2991	535	20	multimodal	multimodal	ADJ
cana-2991	535	21	fusion	fusion	NOUN
cana-2991	535	22	with	with	ADP
cana-2991	535	23	recurrent	recurrent	ADJ
cana-2991	535	24	neural	neural	ADJ
cana-2991	535	25	networks	network	NOUN
cana-2991	535	26	for	for	ADP
cana-2991	535	27	rumor	rumor	NOUN
cana-2991	535	28	detection	detection	NOUN
cana-2991	535	29	on	on	ADP
cana-2991	535	30	microblogs	microblog	NOUN
cana-2991	535	31	.	.	PUNCT
cana-2991	536	1	in	in	ADP
cana-2991	536	2	proceedings	proceeding	NOUN
cana-2991	536	3	of	of	ADP
cana-2991	536	4	the	the	DET
cana-2991	536	5	25th	25th	ADJ
cana-2991	536	6	acm	acm	PROPN
cana-2991	536	7	international	international	ADJ
cana-2991	536	8	conference	conference	NOUN
cana-2991	536	9	on	on	ADP
cana-2991	536	10	multimedia	multimedia	NOUN
cana-2991	536	11	,	,	PUNCT
cana-2991	536	12	pages	page	NOUN
cana-2991	536	13	795–816	795–816	NUM
cana-2991	536	14	,	,	PUNCT
cana-2991	536	15	2017	2017	NUM
cana-2991	536	16	.	.	PUNCT
cana-2991	537	1	[	[	X
cana-2991	537	2	27	27	NUM
cana-2991	537	3	]	]	X
cana-2991	537	4	bande	bande	X
cana-2991	537	5	,	,	PUNCT
cana-2991	537	6	v.	v.	PROPN
cana-2991	537	7	,	,	PUNCT
cana-2991	537	8	raju	raju	PROPN
cana-2991	537	9	,	,	PUNCT
cana-2991	537	10	b.	b.	PROPN
cana-2991	537	11	d.	d.	PROPN
cana-2991	537	12	,	,	PUNCT
cana-2991	537	13	rao	rao	PROPN
cana-2991	537	14	,	,	PUNCT
cana-2991	537	15	k.	k.	PROPN
cana-2991	537	16	p.	p.	PROPN
cana-2991	537	17	,	,	PUNCT
cana-2991	537	18	joshi	joshi	PROPN
cana-2991	537	19	,	,	PUNCT
cana-2991	537	20	s.	s.	PROPN
cana-2991	537	21	,	,	PUNCT
cana-2991	537	22	bajaj	bajaj	PROPN
cana-2991	537	23	,	,	PUNCT
cana-2991	537	24	s.	s.	PROPN
cana-2991	537	25	h.	h.	PROPN
cana-2991	537	26	,	,	PUNCT
cana-2991	537	27	&	&	CCONJ
cana-2991	537	28	sarala	sarala	PROPN
cana-2991	537	29	,	,	PUNCT
cana-2991	537	30	v.	v.	PROPN
cana-2991	537	31	(	(	PUNCT
cana-2991	537	32	2024	2024	NUM
cana-2991	537	33	)	)	PUNCT
cana-2991	537	34	.	.	PUNCT
cana-2991	538	1	designing	design	VERB
cana-2991	538	2	confidential	confidential	ADJ
cana-2991	538	3	cloud	cloud	NOUN
cana-2991	538	4	computing	computing	NOUN
cana-2991	538	5	for	for	ADP
cana-2991	538	6	multi	multi	ADJ
cana-2991	538	7	-	-	ADJ
cana-2991	538	8	dimensional	dimensional	ADJ
cana-2991	538	9	threats	threat	NOUN
cana-2991	538	10	and	and	CCONJ
cana-2991	538	11	safeguarding	safeguard	VERB
cana-2991	538	12	data	datum	NOUN
cana-2991	538	13	security	security	NOUN
cana-2991	538	14	in	in	ADP
cana-2991	538	15	a	a	DET
cana-2991	538	16	robust	robust	ADJ
cana-2991	538	17	framework	framework	NOUN
cana-2991	538	18	.	.	PUNCT
cana-2991	539	1	int	int	NOUN
cana-2991	539	2	.	.	PUNCT
cana-2991	540	1	j.	j.	PROPN
cana-2991	540	2	intell	intell	PROPN
cana-2991	540	3	.	.	PUNCT
cana-2991	541	1	syst	syst	PROPN
cana-2991	541	2	.	.	PUNCT
cana-2991	542	1	appl	appl	PROPN
cana-2991	542	2	.	.	PUNCT
cana-2991	543	1	eng	eng	PROPN
cana-2991	543	2	,	,	PUNCT
cana-2991	543	3	12(11s	12(11s	NUM
cana-2991	543	4	)	)	PUNCT
cana-2991	543	5	,	,	PUNCT
cana-2991	543	6	246	246	NUM
cana-2991	543	7	-	-	SYM
cana-2991	543	8	255	255	NUM
cana-2991	544	1	[	[	X
cana-2991	544	2	28	28	NUM
cana-2991	544	3	]	]	X
cana-2991	544	4	eugenio	eugenio	PROPN
cana-2991	544	5	tacchini	tacchini	PROPN
cana-2991	544	6	,	,	PUNCT
cana-2991	544	7	gabriele	gabriele	PROPN
cana-2991	544	8	ballarin	ballarin	PROPN
cana-2991	544	9	,	,	PUNCT
cana-2991	544	10	marco	marco	PROPN
cana-2991	544	11	l	l	PROPN
cana-2991	544	12	della	della	PROPN
cana-2991	544	13	vedova	vedova	PROPN
cana-2991	544	14	,	,	PUNCT
cana-2991	544	15	stefano	stefano	PROPN
cana-2991	544	16	moret	moret	PROPN
cana-2991	544	17	,	,	PUNCT
cana-2991	544	18	and	and	CCONJ
cana-2991	544	19	luca	luca	PROPN
cana-2991	544	20	de	de	X
cana-2991	544	21	alfaro	alfaro	PROPN
cana-2991	544	22	.	.	PUNCT
cana-2991	545	1	some	some	PRON
cana-2991	545	2	like	like	ADP
cana-2991	545	3	it	it	PRON
cana-2991	545	4	hoax	hoax	ADV
cana-2991	545	5	:	:	PUNCT
cana-2991	545	6	automated	automate	VERB
cana-2991	545	7	fake	fake	ADJ
cana-2991	545	8	news	news	NOUN
cana-2991	545	9	detection	detection	NOUN
cana-2991	545	10	in	in	ADP
cana-2991	545	11	social	social	ADJ
cana-2991	545	12	networks	network	NOUN
cana-2991	545	13	.	.	PUNCT
cana-2991	546	1	arxiv	arxiv	PROPN
cana-2991	546	2	preprint	preprint	PROPN
cana-2991	546	3	arxiv:1704.07506	arxiv:1704.07506	PROPN
cana-2991	546	4	,	,	PUNCT
cana-2991	546	5	2017	2017	NUM
cana-2991	546	6	.	.	PUNCT
cana-2991	547	1	[	[	X
cana-2991	547	2	29	29	NUM
cana-2991	547	3	]	]	X
cana-2991	547	4	benjamin	benjamin	PROPN
cana-2991	547	5	horne	horne	PROPN
cana-2991	547	6	and	and	CCONJ
cana-2991	547	7	sibel	sibel	PROPN
cana-2991	547	8	adali	adali	VERB
cana-2991	547	9	.	.	PUNCT
cana-2991	548	1	this	this	PRON
cana-2991	548	2	just	just	ADV
cana-2991	548	3	in	in	ADP
cana-2991	548	4	:	:	PUNCT
cana-2991	548	5	fake	fake	ADJ
cana-2991	548	6	news	news	NOUN
cana-2991	548	7	packs	pack	VERB
cana-2991	548	8	a	a	DET
cana-2991	548	9	lot	lot	NOUN
cana-2991	548	10	in	in	ADP
cana-2991	548	11	title	title	NOUN
cana-2991	548	12	,	,	PUNCT
cana-2991	548	13	uses	use	VERB
cana-2991	548	14	simpler	simple	ADJ
cana-2991	548	15	,	,	PUNCT
cana-2991	548	16	repetitive	repetitive	ADJ
cana-2991	548	17	content	content	NOUN
cana-2991	548	18	in	in	ADP
cana-2991	548	19	text	text	NOUN
cana-2991	548	20	body	body	NOUN
cana-2991	548	21	,	,	PUNCT
cana-2991	548	22	more	more	ADV
cana-2991	548	23	similar	similar	ADJ
cana-2991	548	24	to	to	ADP
cana-2991	548	25	satire	satire	VERB
cana-2991	548	26	than	than	ADP
cana-2991	548	27	real	real	ADJ
cana-2991	548	28	news	news	NOUN
cana-2991	548	29	.	.	PUNCT
cana-2991	549	1	in	in	ADP
cana-2991	549	2	proceedings	proceeding	NOUN
cana-2991	549	3	of	of	ADP
cana-2991	549	4	the	the	DET
cana-2991	549	5	international	international	ADJ
cana-2991	549	6	aaai	aaai	PROPN
cana-2991	549	7	conference	conference	PROPN
cana-2991	549	8	on	on	ADP
cana-2991	549	9	web	web	NOUN
cana-2991	549	10	and	and	CCONJ
cana-2991	549	11	social	social	ADJ
cana-2991	549	12	media	medium	NOUN
cana-2991	549	13	,	,	PUNCT
cana-2991	549	14	volume	volume	NOUN
cana-2991	549	15	11	11	NUM
cana-2991	549	16	,	,	PUNCT
cana-2991	549	17	pages	page	NOUN
cana-2991	549	18	759–766	759–766	NUM
cana-2991	549	19	,	,	PUNCT
cana-2991	549	20	2017	2017	NUM
cana-2991	549	21	.	.	PUNCT
cana-2991	550	1	[	[	X
cana-2991	550	2	30	30	NUM
cana-2991	550	3	]	]	X
cana-2991	550	4	giovanni	giovanni	PROPN
cana-2991	550	5	santia	santia	PROPN
cana-2991	550	6	and	and	CCONJ
cana-2991	550	7	jake	jake	PROPN
cana-2991	550	8	williams	williams	PROPN
cana-2991	550	9	.	.	PUNCT
cana-2991	551	1	buzzface	buzzface	NOUN
cana-2991	551	2	:	:	PUNCT
cana-2991	551	3	a	a	DET
cana-2991	551	4	news	news	NOUN
cana-2991	551	5	veracity	veracity	NOUN
cana-2991	551	6	dataset	dataset	VERB
cana-2991	551	7	with	with	ADP
cana-2991	551	8	facebook	facebook	PROPN
cana-2991	551	9	user	user	NOUN
cana-2991	551	10	commentary	commentary	NOUN
cana-2991	551	11	and	and	CCONJ
cana-2991	551	12	egos	ego	NOUN
cana-2991	551	13	.	.	PUNCT
cana-2991	552	1	in	in	ADP
cana-2991	552	2	proceedings	proceeding	NOUN
cana-2991	552	3	of	of	ADP
cana-2991	552	4	the	the	DET
cana-2991	552	5	international	international	ADJ
cana-2991	552	6	aaai	aaai	PROPN
cana-2991	552	7	conference	conference	PROPN
cana-2991	552	8	on	on	ADP
cana-2991	552	9	web	web	NOUN
cana-2991	552	10	and	and	CCONJ
cana-2991	552	11	social	social	ADJ
cana-2991	552	12	media	medium	NOUN
cana-2991	552	13	,	,	PUNCT
cana-2991	552	14	volume	volume	NOUN
cana-2991	552	15	12	12	NUM
cana-2991	552	16	,	,	PUNCT
cana-2991	552	17	pages	page	NOUN
cana-2991	552	18	531–540	531–540	NUM
cana-2991	552	19	,	,	PUNCT
cana-2991	552	20	2018	2018	NUM
cana-2991	552	21	.	.	PUNCT
cana-2991	553	1	[	[	X
cana-2991	553	2	31	31	NUM
cana-2991	553	3	]	]	PUNCT
cana-2991	553	4	a.	a.	NOUN
cana-2991	553	5	trivedi	trivedi	PROPN
cana-2991	553	6	,	,	PUNCT
cana-2991	553	7	e.	e.	PROPN
cana-2991	553	8	k.	k.	PROPN
cana-2991	553	9	kaur	kaur	PROPN
cana-2991	553	10	,	,	PUNCT
cana-2991	553	11	c.	c.	PROPN
cana-2991	553	12	choudhary	choudhary	PROPN
cana-2991	553	13	,	,	PUNCT
cana-2991	553	14	kunal	kunal	PROPN
cana-2991	553	15	and	and	CCONJ
cana-2991	553	16	p.	p.	NOUN
cana-2991	553	17	barnwal	barnwal	NOUN
cana-2991	553	18	,	,	PUNCT
cana-2991	553	19	"	"	PUNCT
cana-2991	553	20	should	should	AUX
cana-2991	553	21	ai	ai	VERB
cana-2991	553	22	technologies	technology	NOUN
cana-2991	553	23	replace	replace	VERB
cana-2991	553	24	the	the	DET
cana-2991	553	25	human	human	ADJ
cana-2991	553	26	jobs	job	NOUN
cana-2991	553	27	?	?	PUNCT
cana-2991	553	28	,	,	PUNCT
cana-2991	553	29	"	"	PUNCT
cana-2991	553	30	2023	2023	NUM
cana-2991	553	31	2nd	2nd	ADJ
cana-2991	553	32	international	international	ADJ
cana-2991	553	33	conference	conference	NOUN
cana-2991	553	34	for	for	ADP
cana-2991	553	35	innovation	innovation	NOUN
cana-2991	553	36	in	in	ADP
cana-2991	553	37	technology	technology	NOUN
cana-2991	553	38	(	(	PUNCT
cana-2991	553	39	inocon	inocon	NOUN
cana-2991	553	40	)	)	PUNCT
cana-2991	553	41	,	,	PUNCT
cana-2991	553	42	bangalore	bangalore	PROPN
cana-2991	553	43	,	,	PUNCT
cana-2991	553	44	india	india	PROPN
cana-2991	553	45	,	,	PUNCT
cana-2991	553	46	2023	2023	NUM
cana-2991	553	47	,	,	PUNCT
cana-2991	553	48	pp	pp	ADJ
cana-2991	553	49	.	.	PUNCT
cana-2991	554	1	16	16	NUM
cana-2991	554	2	,	,	PUNCT
cana-2991	554	3	doi	doi	NOUN
cana-2991	554	4	:	:	PUNCT
cana-2991	554	5	10.1109	10.1109	NUM
cana-2991	554	6	/	/	SYM
cana-2991	554	7	inocon57975.2023.10101202	inocon57975.2023.10101202	PROPN
cana-2991	554	8	.	.	PUNCT
cana-2991	555	1	[	[	X
cana-2991	555	2	32	32	NUM
cana-2991	555	3	]	]	PUNCT
cana-2991	555	4	jeppe	jeppe	PROPN
cana-2991	555	5	nørregaard	nørregaard	PROPN
cana-2991	555	6	,	,	PUNCT
cana-2991	555	7	benjamin	benjamin	PROPN
cana-2991	555	8	d	d	PROPN
cana-2991	555	9	horne	horne	PROPN
cana-2991	555	10	,	,	PUNCT
cana-2991	555	11	and	and	CCONJ
cana-2991	555	12	sibel	sibel	PROPN
cana-2991	555	13	adalı	adalı	PROPN
cana-2991	555	14	.	.	PUNCT
cana-2991	556	1	nela	nela	PROPN
cana-2991	556	2	-	-	PUNCT
cana-2991	556	3	gt-2018	gt-2018	PROPN
cana-2991	556	4	:	:	PUNCT
cana-2991	556	5	a	a	DET
cana-2991	556	6	large	large	ADJ
cana-2991	556	7	multi	multi	ADJ
cana-2991	556	8	-	-	ADJ
cana-2991	556	9	labelled	label	VERB
cana-2991	556	10	news	news	NOUN
cana-2991	556	11	dataset	dataset	NOUN
cana-2991	556	12	for	for	ADP
cana-2991	556	13	the	the	DET
cana-2991	556	14	study	study	NOUN
cana-2991	556	15	of	of	ADP
cana-2991	556	16	misinformation	misinformation	NOUN
cana-2991	556	17	in	in	ADP
cana-2991	556	18	news	news	NOUN
cana-2991	556	19	articles	article	NOUN
cana-2991	556	20	.	.	PUNCT
cana-2991	557	1	in	in	ADP
cana-2991	557	2	proceedings	proceeding	NOUN
cana-2991	557	3	of	of	ADP
cana-2991	557	4	the	the	DET
cana-2991	557	5	international	international	ADJ
cana-2991	557	6	aaai	aaai	PROPN
cana-2991	557	7	conference	conference	PROPN
cana-2991	557	8	on	on	ADP
cana-2991	557	9	web	web	NOUN
cana-2991	557	10	and	and	CCONJ
cana-2991	557	11	social	social	ADJ
cana-2991	557	12	media	medium	NOUN
cana-2991	557	13	,	,	PUNCT
cana-2991	557	14	volume	volume	NOUN
cana-2991	557	15	13	13	NUM
cana-2991	557	16	,	,	PUNCT
cana-2991	557	17	pages	page	NOUN
cana-2991	557	18	630–638	630–638	NUM
cana-2991	557	19	,	,	PUNCT
cana-2991	557	20	2019	2019	NUM
cana-2991	557	21	.	.	PUNCT
cana-2991	558	1	[	[	X
cana-2991	558	2	33	33	NUM
cana-2991	558	3	]	]	X
cana-2991	558	4	kunal	kunal	PROPN
cana-2991	558	5	,	,	PUNCT
cana-2991	558	6	p.	p.	NOUN
cana-2991	558	7	singh	singh	PROPN
cana-2991	558	8	and	and	CCONJ
cana-2991	558	9	n.	n.	PROPN
cana-2991	558	10	hirani	hirani	PROPN
cana-2991	558	11	,	,	PUNCT
cana-2991	558	12	"	"	PUNCT
cana-2991	558	13	a	a	DET
cana-2991	558	14	cohesive	cohesive	ADJ
cana-2991	558	15	relation	relation	NOUN
cana-2991	558	16	between	between	ADP
cana-2991	558	17	cybersecurity	cybersecurity	NOUN
cana-2991	558	18	and	and	CCONJ
cana-2991	558	19	information	information	NOUN
cana-2991	558	20	security	security	NOUN
cana-2991	558	21	,	,	PUNCT
cana-2991	558	22	"	"	PUNCT
cana-2991	558	23	2022	2022	NUM
cana-2991	558	24	ieee	ieee	NOUN
cana-2991	558	25	3rd	3rd	PROPN
cana-2991	558	26	global	global	ADJ
cana-2991	558	27	conference	conference	NOUN
cana-2991	558	28	for	for	ADP
cana-2991	558	29	advancement	advancement	NOUN
cana-2991	558	30	in	in	ADP
cana-2991	558	31	technology	technology	NOUN
cana-2991	558	32	(	(	PUNCT
cana-2991	558	33	gcat	gcat	NOUN
cana-2991	558	34	)	)	PUNCT
cana-2991	558	35	,	,	PUNCT
cana-2991	558	36	bangalore	bangalore	PROPN
cana-2991	558	37	,	,	PUNCT
cana-2991	558	38	india	india	PROPN
cana-2991	558	39	,	,	PUNCT
cana-2991	558	40	2022	2022	NUM
cana-2991	558	41	,	,	PUNCT
cana-2991	558	42	pp	pp	ADJ
cana-2991	558	43	.	.	PUNCT
cana-2991	559	1	1	1	NUM
cana-2991	559	2	-	-	SYM
cana-2991	559	3	6	6	NUM
cana-2991	559	4	,	,	PUNCT
cana-2991	559	5	doi	doi	NOUN
cana-2991	559	6	:	:	PUNCT
cana-2991	559	7	10.1109	10.1109	NUM
cana-2991	559	8	/	/	SYM
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cana-2991	559	10	.	.	PUNCT
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cana-2991	560	3	]	]	X
cana-2991	560	4	ramy	ramy	PROPN
cana-2991	560	5	baly	baly	PROPN
cana-2991	560	6	,	,	PUNCT
cana-2991	560	7	georgi	georgi	PROPN
cana-2991	560	8	karadzhov	karadzhov	PROPN
cana-2991	560	9	,	,	PUNCT
cana-2991	560	10	dimitar	dimitar	PROPN
cana-2991	560	11	alexandrov	alexandrov	PROPN
cana-2991	560	12	,	,	PUNCT
cana-2991	560	13	james	james	PROPN
cana-2991	560	14	glass	glass	PROPN
cana-2991	560	15	,	,	PUNCT
cana-2991	560	16	and	and	CCONJ
cana-2991	560	17	preslav	preslav	NOUN
cana-2991	560	18	nakov	nakov	NOUN
cana-2991	560	19	.	.	PUNCT
cana-2991	561	1	predicting	predict	VERB
cana-2991	561	2	factuality	factuality	NOUN
cana-2991	561	3	of	of	ADP
cana-2991	561	4	reporting	reporting	NOUN
cana-2991	561	5	and	and	CCONJ
cana-2991	561	6	bias	bias	NOUN
cana-2991	561	7	of	of	ADP
cana-2991	561	8	news	news	NOUN
cana-2991	561	9	media	medium	NOUN
cana-2991	561	10	sources	source	NOUN
cana-2991	561	11	.	.	PUNCT
cana-2991	562	1	arxiv	arxiv	PROPN
cana-2991	562	2	preprint	preprint	VERB
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cana-2991	562	4	,	,	PUNCT
cana-2991	562	5	2018	2018	NUM
cana-2991	562	6	.	.	PUNCT
cana-2991	563	1	[	[	X
cana-2991	563	2	35	35	NUM
cana-2991	563	3	]	]	X
cana-2991	563	4	arkadipta	arkadipta	PROPN
cana-2991	563	5	de	de	X
cana-2991	563	6	,	,	PUNCT
cana-2991	563	7	dibyanayan	dibyanayan	NOUN
cana-2991	563	8	bandyopadhyay	bandyopadhyay	NOUN
cana-2991	563	9	,	,	PUNCT
cana-2991	563	10	baban	baban	NOUN
cana-2991	563	11	gain	gain	NOUN
cana-2991	563	12	,	,	PUNCT
cana-2991	563	13	and	and	CCONJ
cana-2991	563	14	asif	asif	PROPN
cana-2991	563	15	ekbal	ekbal	PROPN
cana-2991	563	16	.	.	PUNCT
cana-2991	564	1	a	a	DET
cana-2991	564	2	transformer	transformer	NOUN
cana-2991	564	3	-	-	PUNCT
cana-2991	564	4	based	base	VERB
cana-2991	564	5	approach	approach	NOUN
cana-2991	564	6	to	to	ADP
cana-2991	564	7	multilingual	multilingual	ADJ
cana-2991	564	8	fake	fake	ADJ
cana-2991	564	9	news	news	NOUN
cana-2991	564	10	detection	detection	NOUN
cana-2991	564	11	in	in	ADP
cana-2991	564	12	low	low	ADJ
cana-2991	564	13	-	-	PUNCT
cana-2991	564	14	resource	resource	NOUN
cana-2991	564	15	languages	language	NOUN
cana-2991	564	16	.	.	PUNCT
cana-2991	565	1	acm	acm	PROPN
cana-2991	565	2	trans	trans	PROPN
cana-2991	565	3	.	.	PUNCT
cana-2991	566	1	asian	asian	ADJ
cana-2991	566	2	low	low	ADJ
cana-2991	566	3	-	-	PUNCT
cana-2991	566	4	resour	resour	NOUN
cana-2991	566	5	.	.	PUNCT
cana-2991	567	1	lang	lang	PROPN
cana-2991	567	2	.	.	PUNCT
cana-2991	567	3	inf	inf	PROPN
cana-2991	567	4	.	.	PUNCT
cana-2991	567	5	process	process	NOUN
cana-2991	567	6	.	.	PUNCT
cana-2991	567	7	,	,	PUNCT
cana-2991	567	8	21(1	21(1	NUM
cana-2991	567	9	)	)	PUNCT
cana-2991	567	10	,	,	PUNCT
cana-2991	567	11	nov	nov	NOUN
cana-2991	567	12	2021	2021	NUM
cana-2991	567	13	.	.	PUNCT
cana-2991	568	1	[	[	X
cana-2991	568	2	36	36	NUM
cana-2991	568	3	]	]	X
cana-2991	568	4	georgios	georgios	PROPN
cana-2991	568	5	gravanis	gravanis	PROPN
cana-2991	568	6	,	,	PUNCT
cana-2991	568	7	athena	athena	PROPN
cana-2991	568	8	vakali	vakali	PROPN
cana-2991	568	9	,	,	PUNCT
cana-2991	568	10	konstantinos	konstantinos	PROPN
cana-2991	568	11	diamantaras	diamantaras	PROPN
cana-2991	568	12	,	,	PUNCT
cana-2991	568	13	and	and	CCONJ
cana-2991	568	14	panagiotis	panagiotis	NOUN
cana-2991	568	15	karadais	karadais	PROPN
cana-2991	568	16	.	.	PUNCT
cana-2991	569	1	behind	behind	ADP
cana-2991	569	2	the	the	DET
cana-2991	569	3	cues	cue	NOUN
cana-2991	569	4	:	:	PUNCT
cana-2991	569	5	a	a	DET
cana-2991	569	6	benchmarking	benchmarke	VERB
cana-2991	569	7	study	study	NOUN
cana-2991	569	8	for	for	ADP
cana-2991	569	9	fake	fake	ADJ
cana-2991	569	10	news	news	NOUN
cana-2991	569	11	detection	detection	NOUN
cana-2991	569	12	.	.	PUNCT
cana-2991	570	1	expert	expert	NOUN
cana-2991	570	2	systems	system	NOUN
cana-2991	570	3	with	with	ADP
cana-2991	570	4	applications	application	NOUN
cana-2991	570	5	,	,	PUNCT
cana-2991	570	6	128:201–213	128:201–213	NUM
cana-2991	570	7	,	,	PUNCT
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cana-2991	570	9	.	.	PUNCT
cana-2991	571	1	[	[	X
cana-2991	571	2	37	37	NUM
cana-2991	571	3	]	]	X
cana-2991	571	4	faraz	faraz	PROPN
cana-2991	571	5	ahmad	ahmad	PROPN
cana-2991	571	6	and	and	CCONJ
cana-2991	571	7	r	r	NOUN
cana-2991	571	8	lokeshkumar	lokeshkumar	NOUN
cana-2991	571	9	.	.	PUNCT
cana-2991	572	1	a	a	DET
cana-2991	572	2	comparison	comparison	NOUN
cana-2991	572	3	of	of	ADP
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cana-2991	572	5	learning	learn	VERB
cana-2991	572	6	algorithms	algorithm	NOUN
cana-2991	572	7	in	in	ADP
cana-2991	572	8	fake	fake	ADJ
cana-2991	572	9	news	news	NOUN
cana-2991	572	10	detection	detection	NOUN
cana-2991	572	11	.	.	PUNCT
cana-2991	573	1	international	international	ADJ
cana-2991	573	2	journal	journal	NOUN
cana-2991	573	3	on	on	ADP
cana-2991	573	4	emerging	emerge	VERB
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cana-2991	573	6	,	,	PUNCT
cana-2991	573	7	10(4):177–183	10(4):177–183	NUM
cana-2991	573	8	,	,	PUNCT
cana-2991	573	9	2019	2019	NUM
cana-2991	573	10	.	.	PUNCT
cana-2991	574	1	[	[	X
cana-2991	574	2	38	38	NUM
cana-2991	574	3	]	]	PUNCT
cana-2991	574	4	pedro	pedro	PROPN
cana-2991	574	5	henrique	henrique	PROPN
cana-2991	574	6	arruda	arruda	PROPN
cana-2991	574	7	faustini	faustini	PROPN
cana-2991	574	8	and	and	CCONJ
cana-2991	574	9	thiago	thiago	PROPN
cana-2991	574	10	ferreira	ferreira	PROPN
cana-2991	574	11	covoes	covoes	PROPN
cana-2991	574	12	.	.	PUNCT
cana-2991	575	1	fake	fake	ADJ
cana-2991	575	2	news	news	NOUN
cana-2991	575	3	detection	detection	NOUN
cana-2991	575	4	in	in	ADP
cana-2991	575	5	multiple	multiple	ADJ
cana-2991	575	6	platforms	platform	NOUN
cana-2991	575	7	and	and	CCONJ
cana-2991	575	8	languages	language	NOUN
cana-2991	575	9	.	.	PUNCT
cana-2991	576	1	expert	expert	NOUN
cana-2991	576	2	systems	system	NOUN
cana-2991	576	3	with	with	ADP
cana-2991	576	4	applications	application	NOUN
cana-2991	576	5	,	,	PUNCT
cana-2991	576	6	158:113503	158:113503	NUM
cana-2991	576	7	,	,	PUNCT
cana-2991	576	8	2020	2020	NUM
cana-2991	576	9	.	.	PUNCT
cana-2991	577	1	[	[	X
cana-2991	577	2	39	39	NUM
cana-2991	577	3	]	]	PUNCT
cana-2991	577	4	apoorva	apoorva	PROPN
cana-2991	577	5	dhawan	dhawan	PROPN
cana-2991	577	6	,	,	PUNCT
cana-2991	577	7	malvika	malvika	NOUN
cana-2991	577	8	bhalla	bhalla	PROPN
cana-2991	577	9	,	,	PUNCT
cana-2991	577	10	deeksha	deeksha	PROPN
cana-2991	577	11	arora	arora	PROPN
cana-2991	577	12	,	,	PUNCT
cana-2991	577	13	rishabh	rishabh	PROPN
cana-2991	577	14	kaushal	kaushal	PROPN
cana-2991	577	15	,	,	PUNCT
cana-2991	577	16	and	and	CCONJ
cana-2991	577	17	ponnurangam	ponnurangam	NOUN
cana-2991	577	18	kumaraguru	kumaraguru	PROPN
cana-2991	577	19	.	.	PUNCT
cana-2991	578	1	fakenewsindia	fakenewsindia	PROPN
cana-2991	578	2	:	:	PUNCT
cana-2991	578	3	a	a	DET
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cana-2991	578	7	fake	fake	ADJ
cana-2991	578	8	news	news	NOUN
cana-2991	578	9	incidents	incident	NOUN
cana-2991	578	10	in	in	ADP
cana-2991	578	11	india	india	PROPN
cana-2991	578	12	,	,	PUNCT
cana-2991	578	13	collection	collection	NOUN
cana-2991	578	14	methodology	methodology	NOUN
cana-2991	578	15	and	and	CCONJ
cana-2991	578	16	impact	impact	NOUN
cana-2991	578	17	assessment	assessment	NOUN
cana-2991	578	18	in	in	ADP
cana-2991	578	19	social	social	ADJ
cana-2991	578	20	media	medium	NOUN
cana-2991	578	21	.	.	PUNCT
cana-2991	579	1	computer	computer	NOUN
cana-2991	579	2	communications	communication	NOUN
cana-2991	579	3	,	,	PUNCT
cana-2991	579	4	185:130–141	185:130–141	NUM
cana-2991	579	5	,	,	PUNCT
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cana-2991	579	7	.	.	PUNCT
cana-2991	580	1	[	[	X
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cana-2991	580	3	]	]	X
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cana-2991	580	5	shu	shu	PROPN
cana-2991	580	6	,	,	PUNCT
cana-2991	580	7	xinyi	xinyi	PROPN
cana-2991	580	8	zhou	zhou	PROPN
cana-2991	580	9	,	,	PUNCT
cana-2991	580	10	suhang	suhang	PROPN
cana-2991	580	11	wang	wang	PROPN
cana-2991	580	12	,	,	PUNCT
cana-2991	580	13	reza	reza	PROPN
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cana-2991	580	15	,	,	PUNCT
cana-2991	580	16	and	and	CCONJ
cana-2991	580	17	huan	huan	PROPN
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cana-2991	580	19	.	.	PUNCT
cana-2991	581	1	the	the	DET
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cana-2991	581	3	of	of	ADP
cana-2991	581	4	user	user	NOUN
cana-2991	581	5	profiles	profile	NOUN
cana-2991	581	6	for	for	ADP
cana-2991	581	7	fake	fake	ADJ
cana-2991	581	8	news	news	NOUN
cana-2991	581	9	detection	detection	NOUN
cana-2991	581	10	.	.	PUNCT
cana-2991	582	1	in	in	ADP
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cana-2991	582	3	of	of	ADP
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cana-2991	582	5	2019	2019	NUM
cana-2991	582	6	ieee	ieee	NOUN
cana-2991	582	7	/	/	SYM
cana-2991	582	8	acm	acm	PROPN
cana-2991	582	9	international	international	ADJ
cana-2991	582	10	conference	conference	NOUN
cana-2991	582	11	on	on	ADP
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cana-2991	582	13	in	in	ADP
cana-2991	582	14	social	social	ADJ
cana-2991	582	15	networks	network	NOUN
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cana-2991	582	17	and	and	CCONJ
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cana-2991	582	19	,	,	PUNCT
cana-2991	582	20	pages	page	NOUN
cana-2991	582	21	436–439	436–439	NUM
cana-2991	582	22	,	,	PUNCT
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cana-2991	582	24	.	.	PUNCT
cana-2991	583	1	[	[	X
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cana-2991	583	3	]	]	PUNCT
cana-2991	583	4	yaqing	yaqing	PROPN
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cana-2991	583	6	,	,	PUNCT
cana-2991	583	7	weifeng	weifeng	PROPN
cana-2991	583	8	yang	yang	PROPN
cana-2991	583	9	,	,	PUNCT
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cana-2991	583	11	ma	ma	PROPN
cana-2991	583	12	,	,	PUNCT
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cana-2991	583	14	xu	xu	PROPN
cana-2991	583	15	,	,	PUNCT
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cana-2991	583	17	zhong	zhong	PROPN
cana-2991	583	18	,	,	PUNCT
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cana-2991	583	21	,	,	PUNCT
cana-2991	583	22	and	and	CCONJ
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cana-2991	583	25	.	.	PUNCT
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cana-2991	583	29	fake	fake	ADJ
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cana-2991	583	31	detection	detection	NOUN
cana-2991	583	32	via	via	ADP
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cana-2991	583	34	learning	learning	NOUN
cana-2991	583	35	.	.	PUNCT
cana-2991	584	1	in	in	ADP
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cana-2991	584	3	of	of	ADP
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cana-2991	584	5	aaai	aaai	PROPN
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cana-2991	584	7	on	on	ADP
cana-2991	584	8	artificial	artificial	ADJ
cana-2991	584	9	intelligence	intelligence	NOUN
cana-2991	584	10	,	,	PUNCT
cana-2991	584	11	volume	volume	NOUN
cana-2991	584	12	34	34	NUM
cana-2991	584	13	,	,	PUNCT
cana-2991	584	14	pages	page	NOUN
cana-2991	584	15	516–523	516–523	NUM
cana-2991	584	16	,	,	PUNCT
cana-2991	584	17	2020	2020	NUM
cana-2991	584	18	.	.	PUNCT
cana-2991	585	1	[	[	X
cana-2991	585	2	42	42	NUM
cana-2991	585	3	]	]	PUNCT
cana-2991	585	4	taichi	taichi	PROPN
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cana-2991	585	6	.	.	PUNCT
cana-2991	586	1	dataset	dataset	NOUN
cana-2991	586	2	of	of	ADP
cana-2991	586	3	fake	fake	ADJ
cana-2991	586	4	news	news	NOUN
cana-2991	586	5	detection	detection	NOUN
cana-2991	586	6	and	and	CCONJ
cana-2991	586	7	fact	fact	NOUN
cana-2991	586	8	verification	verification	NOUN
cana-2991	586	9	:	:	PUNCT
cana-2991	586	10	a	a	DET
cana-2991	586	11	survey	survey	NOUN
cana-2991	586	12	.	.	PUNCT
cana-2991	587	1	arxiv	arxiv	PROPN
cana-2991	587	2	preprint	preprint	PROPN
cana-2991	587	3	arxiv:2111.03299	arxiv:2111.03299	NOUN
cana-2991	587	4	,	,	PUNCT
cana-2991	587	5	2021	2021	NUM
cana-2991	587	6	.	.	PUNCT
cana-2991	588	1	[	[	X
cana-2991	588	2	43	43	NUM
cana-2991	588	3	]	]	X
cana-2991	588	4	arianna	arianna	PROPN
cana-2991	588	5	d’ulizia	d’ulizia	PROPN
cana-2991	588	6	,	,	PUNCT
cana-2991	588	7	maria	maria	PROPN
cana-2991	588	8	chiara	chiara	PROPN
cana-2991	588	9	caschera	caschera	PROPN
cana-2991	588	10	,	,	PUNCT
cana-2991	588	11	fernando	fernando	PROPN
cana-2991	588	12	ferri	ferri	PROPN
cana-2991	588	13	,	,	PUNCT
cana-2991	588	14	and	and	CCONJ
cana-2991	588	15	patrizia	patrizia	PROPN
cana-2991	588	16	grifoni	grifoni	NOUN
cana-2991	588	17	.	.	PUNCT
cana-2991	589	1	fake	fake	ADJ
cana-2991	589	2	news	news	NOUN
cana-2991	589	3	detection	detection	NOUN
cana-2991	589	4	:	:	PUNCT
cana-2991	589	5	a	a	DET
cana-2991	589	6	survey	survey	NOUN
cana-2991	589	7	of	of	ADP
cana-2991	589	8	evaluation	evaluation	NOUN
cana-2991	589	9	datasets	dataset	NOUN
cana-2991	589	10	.	.	PUNCT
cana-2991	590	1	peerj	peerj	PROPN
cana-2991	590	2	computer	computer	NOUN
cana-2991	590	3	science	science	NOUN
cana-2991	590	4	,	,	PUNCT
cana-2991	590	5	7	7	NUM
cana-2991	590	6	:	:	PUNCT
cana-2991	590	7	e518	e518	PROPN
cana-2991	590	8	,	,	PUNCT
cana-2991	590	9	2021	2021	NUM
cana-2991	590	10	.	.	PUNCT
cana-2991	591	1	[	[	X
cana-2991	591	2	44	44	NUM
cana-2991	591	3	]	]	PUNCT
cana-2991	591	4	tahniat	tahniat	PROPN
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cana-2991	591	16	and	and	CCONJ
cana-2991	591	17	shaina	shaina	PROPN
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cana-2991	592	3	:	:	PUNCT
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cana-2991	592	11	for	for	ADP
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cana-2991	592	13	us	us	PROPN
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cana-2991	592	15	.	.	PUNCT
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cana-2991	593	4	,	,	PUNCT
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cana-2991	593	6	.	.	PUNCT
cana-2991	594	1	[	[	X
cana-2991	594	2	45	45	NUM
cana-2991	594	3	]	]	X
cana-2991	594	4	sara	sara	PROPN
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cana-2991	594	6	.	.	PUNCT
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cana-2991	595	6	:	:	PUNCT
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cana-2991	596	2	,	,	PUNCT
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cana-2991	596	4	and	and	CCONJ
cana-2991	596	5	opportunities	opportunity	NOUN
cana-2991	596	6	.	.	PUNCT
cana-2991	597	1	arxiv	arxiv	PROPN
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cana-2991	597	4	,	,	PUNCT
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cana-2991	597	6	.	.	PUNCT
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cana-2991	598	6	issn	issn	NOUN
cana-2991	598	7	:	:	PUNCT
cana-2991	598	8	1074	1074	NUM
cana-2991	598	9	-	-	PUNCT
cana-2991	598	10	133x	133x	NUM
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cana-2991	598	14	.	.	PUNCT
cana-2991	599	1	5s	5s	NUM
cana-2991	599	2	(	(	PUNCT
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cana-2991	599	4	)	)	PUNCT
cana-2991	599	5	178	178	NUM
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cana-2991	600	1	[	[	X
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cana-2991	600	3	]	]	X
cana-2991	600	4	yixuan	yixuan	PROPN
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cana-2991	600	6	,	,	PUNCT
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cana-2991	600	12	,	,	PUNCT
cana-2991	600	13	jie	jie	PROPN
cana-2991	600	14	sui	sui	PROPN
cana-2991	600	15	,	,	PUNCT
cana-2991	600	16	qin	qin	PROPN
cana-2991	600	17	lv	lv	PROPN
cana-2991	600	18	,	,	PUNCT
cana-2991	600	19	lu	lu	PROPN
cana-2991	600	20	tun	tun	PROPN
cana-2991	600	21	,	,	PUNCT
cana-2991	600	22	and	and	CCONJ
cana-2991	600	23	li	li	PROPN
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cana-2991	600	25	.	.	PUNCT
cana-2991	601	1	cross	cross	ADJ
cana-2991	601	2	-	-	ADJ
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cana-2991	601	4	ambiguity	ambiguity	NOUN
cana-2991	601	5	learning	learn	VERB
cana-2991	601	6	for	for	ADP
cana-2991	601	7	multimodal	multimodal	ADJ
cana-2991	601	8	fake	fake	ADJ
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cana-2991	601	11	.	.	PUNCT
cana-2991	602	1	in	in	ADP
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cana-2991	602	5	acm	acm	PROPN
cana-2991	602	6	web	web	NOUN
cana-2991	602	7	conference	conference	NOUN
cana-2991	602	8	2022	2022	NUM
cana-2991	602	9	,	,	PUNCT
cana-2991	602	10	pages	page	NOUN
cana-2991	602	11	2897–2905	2897–2905	NUM
cana-2991	602	12	,	,	PUNCT
cana-2991	602	13	2022	2022	NUM
cana-2991	602	14	.	.	PUNCT
cana-2991	603	1	[	[	X
cana-2991	603	2	47	47	NUM
cana-2991	603	3	]	]	PUNCT
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cana-2991	603	5	choraś	choraś	PROPN
cana-2991	603	6	,	,	PUNCT
cana-2991	603	7	konstantinos	konstantinos	PROPN
cana-2991	603	8	demestichas	demestichas	PROPN
cana-2991	603	9	,	,	PUNCT
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cana-2991	603	11	giełczyk	giełczyk	PROPN
cana-2991	603	12	,	,	PUNCT
cana-2991	603	13	álvaro	álvaro	PROPN
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cana-2991	603	15	,	,	PUNCT
cana-2991	603	16	paweł	paweł	NOUN
cana-2991	603	17	ksieniewicz	ksieniewicz	NOUN
cana-2991	603	18	,	,	PUNCT
cana-2991	603	19	konstantina	konstantina	PROPN
cana-2991	603	20	remoundou	remoundou	PROPN
cana-2991	603	21	,	,	PUNCT
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cana-2991	603	25	and	and	CCONJ
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cana-2991	603	28	.	.	PUNCT
cana-2991	604	1	advanced	advanced	ADJ
cana-2991	604	2	machine	machine	NOUN
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cana-2991	604	5	for	for	ADP
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cana-2991	604	8	(	(	PUNCT
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cana-2991	604	11	)	)	PUNCT
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cana-2991	604	13	:	:	PUNCT
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cana-2991	605	1	[	[	X
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cana-2991	605	3	]	]	X
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cana-2991	605	22	.	.	PUNCT
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cana-2991	608	1	[	[	X
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cana-2991	611	2	:	:	PUNCT
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cana-2991	614	4	:	:	PUNCT
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cana-2991	615	10	.	.	PUNCT
cana-2991	616	1	[	[	X
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cana-2991	617	11	.	.	PUNCT
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cana-2991	618	9	.	.	PUNCT
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cana-2991	619	3	]	]	PUNCT
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cana-2991	619	6	and	and	CCONJ
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cana-2991	619	8	arora	arora	PROPN
cana-2991	619	9	.	.	PUNCT
cana-2991	620	1	combating	combat	VERB
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cana-2991	620	5	on	on	ADP
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cana-2991	620	8	:	:	PUNCT
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cana-2991	620	10	,	,	PUNCT
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cana-2991	620	12	,	,	PUNCT
cana-2991	620	13	and	and	CCONJ
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cana-2991	620	16	.	.	PUNCT
cana-2991	621	1	multimedia	multimedia	NOUN
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cana-2991	621	3	,	,	PUNCT
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cana-2991	621	5	,	,	PUNCT
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cana-2991	621	7	.	.	PUNCT
cana-2991	622	1	[	[	X
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cana-2991	622	3	]	]	X
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cana-2991	622	6	,	,	PUNCT
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cana-2991	622	9	,	,	PUNCT
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cana-2991	622	12	,	,	PUNCT
cana-2991	622	13	and	and	CCONJ
cana-2991	622	14	abdellatif	abdellatif	NOUN
cana-2991	622	15	mtibaa	mtibaa	PROPN
cana-2991	622	16	.	.	PUNCT
cana-2991	623	1	a	a	DET
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cana-2991	623	5	multimodal	multimodal	NOUN
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cana-2991	623	7	for	for	ADP
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cana-2991	623	9	vision	vision	NOUN
cana-2991	623	10	:	:	PUNCT
cana-2991	623	11	advances	advance	NOUN
cana-2991	623	12	,	,	PUNCT
cana-2991	623	13	trends	trend	NOUN
cana-2991	623	14	,	,	PUNCT
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cana-2991	623	19	.	.	PUNCT
cana-2991	624	1	the	the	DET
cana-2991	624	2	visual	visual	ADJ
cana-2991	624	3	computer	computer	NOUN
cana-2991	624	4	,	,	PUNCT
cana-2991	624	5	38(8):2939–2970	38(8):2939–2970	PROPN
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cana-2991	625	3	]	]	PUNCT
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cana-2991	625	9	,	,	PUNCT
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cana-2991	625	13	and	and	CCONJ
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cana-2991	626	14	and	and	CCONJ
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cana-2991	626	16	:	:	PUNCT
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cana-2991	626	19	,	,	PUNCT
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cana-2991	627	7	.	.	PUNCT
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cana-2991	629	8	.	.	PUNCT
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cana-2991	630	5	,	,	PUNCT
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cana-2991	630	7	.	.	PUNCT
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cana-2991	631	6	and	and	CCONJ
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cana-2991	632	4	of	of	ADP
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cana-2991	632	6	in	in	ADP
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cana-2991	632	9	:	:	PUNCT
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cana-2991	632	11	in	in	ADP
cana-2991	632	12	-	-	PUNCT
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cana-2991	632	14	exploration	exploration	NOUN
cana-2991	632	15	in	in	ADP
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cana-2991	632	17	,	,	PUNCT
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cana-2991	632	19	and	and	CCONJ
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cana-2991	632	21	.	.	PUNCT
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cana-2991	633	4	,	,	PUNCT
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cana-2991	633	6	.	.	PUNCT
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cana-2991	634	3	]	]	X
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cana-2991	634	6	and	and	CCONJ
cana-2991	634	7	halima	halima	PROPN
cana-2991	634	8	sadia	sadia	PROPN
cana-2991	634	9	.	.	PUNCT
cana-2991	635	1	a	a	DET
cana-2991	635	2	comprehensive	comprehensive	ADJ
cana-2991	635	3	analysis	analysis	NOUN
cana-2991	635	4	of	of	ADP
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cana-2991	635	7	detection	detection	NOUN
cana-2991	635	8	models	model	NOUN
cana-2991	635	9	:	:	PUNCT
cana-2991	635	10	a	a	DET
cana-2991	635	11	systematic	systematic	ADJ
cana-2991	635	12	literature	literature	NOUN
cana-2991	635	13	review	review	NOUN
cana-2991	635	14	and	and	CCONJ
cana-2991	635	15	current	current	ADJ
cana-2991	635	16	challenges	challenge	NOUN
cana-2991	635	17	.	.	PUNCT
cana-2991	636	1	engineering	engineering	NOUN
cana-2991	636	2	proceedings	proceeding	NOUN
cana-2991	636	3	,	,	PUNCT
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cana-2991	636	5	,	,	PUNCT
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cana-2991	636	7	.	.	PUNCT
cana-2991	637	1	[	[	X
cana-2991	637	2	59	59	NUM
cana-2991	637	3	]	]	PUNCT
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cana-2991	637	6	,	,	PUNCT
cana-2991	637	7	mikhail	mikhail	PROPN
cana-2991	637	8	alexandrov	alexandrov	PROPN
cana-2991	637	9	,	,	PUNCT
cana-2991	637	10	and	and	CCONJ
cana-2991	637	11	john	john	PROPN
cana-2991	637	12	cardiff	cardiff	PROPN
cana-2991	637	13	.	.	PUNCT
cana-2991	638	1	improving	improve	VERB
cana-2991	638	2	multiclass	multiclass	ADJ
cana-2991	638	3	classification	classification	NOUN
cana-2991	638	4	of	of	ADP
cana-2991	638	5	fake	fake	ADJ
cana-2991	638	6	news	news	NOUN
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cana-2991	638	8	bert	bert	NOUN
cana-2991	638	9	-	-	PUNCT
cana-2991	638	10	based	base	VERB
cana-2991	638	11	models	model	NOUN
cana-2991	638	12	and	and	CCONJ
cana-2991	638	13	chatgpt	chatgpt	NOUN
cana-2991	638	14	-	-	PUNCT
cana-2991	638	15	augmented	augment	VERB
cana-2991	638	16	data	datum	NOUN
cana-2991	638	17	.	.	PUNCT
cana-2991	639	1	inventions	invention	NOUN
cana-2991	639	2	,	,	PUNCT
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cana-2991	639	4	,	,	PUNCT
cana-2991	639	5	2023	2023	NUM
cana-2991	639	6	.	.	PUNCT