id	sid	tid	token	lemma	pos
aiti-13523	1	1	microsoft	microsoft	PROPN
aiti-13523	1	2	word	word	NOUN
aiti-13523	1	3	4	4	NUM
aiti-13523	1	4	-	-	PUNCT
aiti-13523	1	5	v9n2(2024)-aiti#13523(129	v9n2(2024)-aiti#13523(129	ADJ
aiti-13523	1	6	-	-	PUNCT
aiti-13523	1	7	142).docx	142).docx	NUM
aiti-13523	1	8	advances	advance	NOUN
aiti-13523	1	9	in	in	ADP
aiti-13523	1	10	technology	technology	NOUN
aiti-13523	1	11	innovation	innovation	NOUN
aiti-13523	1	12	,	,	PUNCT
aiti-13523	1	13	vol	vol	NOUN
aiti-13523	1	14	.	.	PROPN
aiti-13523	1	15	9	9	NUM
aiti-13523	1	16	,	,	PUNCT
aiti-13523	1	17	no	no	INTJ
aiti-13523	1	18	.	.	NOUN
aiti-13523	1	19	2	2	NUM
aiti-13523	1	20	,	,	PUNCT
aiti-13523	1	21	2024	2024	NUM
aiti-13523	1	22	,	,	PUNCT
aiti-13523	1	23	pp	pp	ADJ
aiti-13523	1	24	.	.	PUNCT
aiti-13523	2	1	129	129	NUM
aiti-13523	2	2	-	-	SYM
aiti-13523	2	3	142	142	NUM
aiti-13523	2	4	english	english	ADJ
aiti-13523	2	5	language	language	NOUN
aiti-13523	2	6	proofreader	proofreader	NOUN
aiti-13523	2	7	:	:	PUNCT
aiti-13523	2	8	chih	chih	PROPN
aiti-13523	2	9	-	-	PUNCT
aiti-13523	2	10	wen	wen	PROPN
aiti-13523	2	11	teng	teng	PROPN
aiti-13523	2	12	improving	improve	VERB
aiti-13523	2	13	healthcare	healthcare	NOUN
aiti-13523	2	14	communication	communication	NOUN
aiti-13523	2	15	:	:	PUNCT
aiti-13523	2	16	ai	ai	VERB
aiti-13523	2	17	-	-	PUNCT
aiti-13523	2	18	driven	drive	VERB
aiti-13523	2	19	emotion	emotion	NOUN
aiti-13523	2	20	classification	classification	NOUN
aiti-13523	2	21	in	in	ADP
aiti-13523	2	22	imbalanced	imbalanced	ADJ
aiti-13523	2	23	patient	patient	ADJ
aiti-13523	2	24	text	text	NOUN
aiti-13523	2	25	data	datum	NOUN
aiti-13523	2	26	with	with	ADP
aiti-13523	2	27	explainable	explainable	ADJ
aiti-13523	2	28	models	model	NOUN
aiti-13523	2	29	souaad	souaad	VERB
aiti-13523	2	30	hamza	hamza	PROPN
aiti-13523	2	31	-	-	PUNCT
aiti-13523	2	32	cherif1	cherif1	PROPN
aiti-13523	2	33	,	,	PUNCT
aiti-13523	2	34	*	*	PUNCT
aiti-13523	2	35	,	,	PUNCT
aiti-13523	2	36	lamia	lamia	PROPN
aiti-13523	2	37	fatiha	fatiha	PROPN
aiti-13523	2	38	kazi	kazi	PROPN
aiti-13523	2	39	tani1	tani1	PROPN
aiti-13523	2	40	,	,	PUNCT
aiti-13523	2	41	nesma	nesma	ADP
aiti-13523	2	42	settouti2	settouti2	NOUN
aiti-13523	2	43	1biomedical	1biomedical	NUM
aiti-13523	2	44	engineering	engineering	NOUN
aiti-13523	2	45	laboratory	laboratory	NOUN
aiti-13523	2	46	,	,	PUNCT
aiti-13523	2	47	university	university	NOUN
aiti-13523	2	48	of	of	ADP
aiti-13523	2	49	tlemcen	tlemcen	PROPN
aiti-13523	2	50	,	,	PUNCT
aiti-13523	2	51	tlemcen	tlemcen	PROPN
aiti-13523	2	52	,	,	PUNCT
aiti-13523	2	53	algeria	algeria	PROPN
aiti-13523	2	54	2labisen	2labisen	PROPN
aiti-13523	2	55	yncréa	yncréa	PROPN
aiti-13523	2	56	ouest	ouest	PROPN
aiti-13523	2	57	,	,	PUNCT
aiti-13523	2	58	caen	caen	PROPN
aiti-13523	2	59	,	,	PUNCT
aiti-13523	2	60	france	france	PROPN
aiti-13523	2	61	received	receive	VERB
aiti-13523	2	62	31	31	NUM
aiti-13523	2	63	march	march	NOUN
aiti-13523	2	64	2024	2024	NUM
aiti-13523	2	65	;	;	PUNCT
aiti-13523	2	66	received	receive	VERB
aiti-13523	2	67	in	in	ADP
aiti-13523	2	68	revised	revise	VERB
aiti-13523	2	69	form	form	NOUN
aiti-13523	2	70	29	29	NUM
aiti-13523	2	71	april	april	PROPN
aiti-13523	2	72	2024	2024	NUM
aiti-13523	2	73	;	;	PUNCT
aiti-13523	2	74	accepted	accept	VERB
aiti-13523	2	75	30	30	NUM
aiti-13523	2	76	april	april	PROPN
aiti-13523	2	77	2024	2024	NUM
aiti-13523	2	78	doi	doi	NOUN
aiti-13523	2	79	:	:	PUNCT
aiti-13523	2	80	https://doi.org/10.46604/aiti.2024.13523	https://doi.org/10.46604/aiti.2024.13523	PROPN
aiti-13523	2	81	abstract	abstract	ADJ
aiti-13523	2	82	sentiment	sentiment	NOUN
aiti-13523	2	83	analysis	analysis	NOUN
aiti-13523	2	84	is	be	AUX
aiti-13523	2	85	crucial	crucial	ADJ
aiti-13523	2	86	in	in	ADP
aiti-13523	2	87	healthcare	healthcare	PROPN
aiti-13523	2	88	to	to	PART
aiti-13523	2	89	understand	understand	VERB
aiti-13523	2	90	patients	patient	NOUN
aiti-13523	2	91	’	'	PUNCT
aiti-13523	2	92	emotions	emotion	NOUN
aiti-13523	2	93	,	,	PUNCT
aiti-13523	2	94	automatically	automatically	ADV
aiti-13523	2	95	identifying	identify	VERB
aiti-13523	2	96	the	the	DET
aiti-13523	2	97	feelings	feeling	NOUN
aiti-13523	2	98	of	of	ADP
aiti-13523	2	99	patients	patient	NOUN
aiti-13523	2	100	suffering	suffer	VERB
aiti-13523	2	101	from	from	ADP
aiti-13523	2	102	serious	serious	ADJ
aiti-13523	2	103	illnesses	illness	NOUN
aiti-13523	2	104	(	(	PUNCT
aiti-13523	2	105	cancer	cancer	NOUN
aiti-13523	2	106	,	,	PUNCT
aiti-13523	2	107	aids	aid	NOUN
aiti-13523	2	108	,	,	PUNCT
aiti-13523	2	109	or	or	CCONJ
aiti-13523	2	110	ebola	ebola	NOUN
aiti-13523	2	111	)	)	PUNCT
aiti-13523	2	112	with	with	ADP
aiti-13523	2	113	an	an	DET
aiti-13523	2	114	artificial	artificial	ADJ
aiti-13523	2	115	intelligence	intelligence	NOUN
aiti-13523	2	116	model	model	NOUN
aiti-13523	2	117	that	that	PRON
aiti-13523	2	118	constitutes	constitute	VERB
aiti-13523	2	119	a	a	DET
aiti-13523	2	120	major	major	ADJ
aiti-13523	2	121	challenge	challenge	NOUN
aiti-13523	2	122	to	to	PART
aiti-13523	2	123	help	help	VERB
aiti-13523	2	124	health	health	NOUN
aiti-13523	2	125	professionals	professional	NOUN
aiti-13523	2	126	.	.	PUNCT
aiti-13523	3	1	this	this	DET
aiti-13523	3	2	study	study	NOUN
aiti-13523	3	3	presents	present	VERB
aiti-13523	3	4	a	a	DET
aiti-13523	3	5	comparative	comparative	ADJ
aiti-13523	3	6	study	study	NOUN
aiti-13523	3	7	on	on	ADP
aiti-13523	3	8	different	different	ADJ
aiti-13523	3	9	machine	machine	NOUN
aiti-13523	3	10	learning	learning	NOUN
aiti-13523	3	11	(	(	PUNCT
aiti-13523	3	12	logistic	logistic	ADJ
aiti-13523	3	13	regression	regression	NOUN
aiti-13523	3	14	,	,	PUNCT
aiti-13523	3	15	naive	naive	ADJ
aiti-13523	3	16	bayes	bayes	NOUN
aiti-13523	3	17	,	,	PUNCT
aiti-13523	3	18	and	and	CCONJ
aiti-13523	3	19	lightgbm	lightgbm	ADJ
aiti-13523	3	20	)	)	PUNCT
aiti-13523	3	21	and	and	CCONJ
aiti-13523	3	22	deep	deep	ADJ
aiti-13523	3	23	learning	learning	NOUN
aiti-13523	3	24	models	model	NOUN
aiti-13523	3	25	:	:	PUNCT
aiti-13523	3	26	long	long	ADJ
aiti-13523	3	27	short	short	ADJ
aiti-13523	3	28	-	-	PUNCT
aiti-13523	3	29	term	term	NOUN
aiti-13523	3	30	memory	memory	NOUN
aiti-13523	3	31	(	(	PUNCT
aiti-13523	3	32	lstm	lstm	NOUN
aiti-13523	3	33	)	)	PUNCT
aiti-13523	3	34	and	and	CCONJ
aiti-13523	3	35	bidirectional	bidirectional	ADJ
aiti-13523	3	36	encoder	encoder	NOUN
aiti-13523	3	37	representations	representation	VERB
aiti-13523	3	38	from	from	ADP
aiti-13523	3	39	transformers	transformer	NOUN
aiti-13523	3	40	(	(	PUNCT
aiti-13523	3	41	bert	bert	PROPN
aiti-13523	3	42	)	)	PUNCT
aiti-13523	3	43	for	for	ADP
aiti-13523	3	44	classify	classify	VERB
aiti-13523	3	45	health	health	NOUN
aiti-13523	3	46	feelings	feeling	NOUN
aiti-13523	3	47	thanks	thank	NOUN
aiti-13523	3	48	to	to	ADP
aiti-13523	3	49	textual	textual	ADJ
aiti-13523	3	50	data	datum	NOUN
aiti-13523	3	51	related	relate	VERB
aiti-13523	3	52	to	to	ADP
aiti-13523	3	53	patients	patient	NOUN
aiti-13523	3	54	with	with	ADP
aiti-13523	3	55	serious	serious	ADJ
aiti-13523	3	56	illnesses	illness	NOUN
aiti-13523	3	57	.	.	PUNCT
aiti-13523	4	1	considering	consider	VERB
aiti-13523	4	2	the	the	DET
aiti-13523	4	3	class	class	NOUN
aiti-13523	4	4	imbalance	imbalance	NOUN
aiti-13523	4	5	of	of	ADP
aiti-13523	4	6	the	the	DET
aiti-13523	4	7	dataset	dataset	NOUN
aiti-13523	4	8	,	,	PUNCT
aiti-13523	4	9	various	various	ADJ
aiti-13523	4	10	resampling	resample	VERB
aiti-13523	4	11	techniques	technique	NOUN
aiti-13523	4	12	are	be	AUX
aiti-13523	4	13	investigated	investigate	VERB
aiti-13523	4	14	.	.	PUNCT
aiti-13523	5	1	the	the	DET
aiti-13523	5	2	approach	approach	NOUN
aiti-13523	5	3	is	be	AUX
aiti-13523	5	4	complemented	complement	VERB
aiti-13523	5	5	by	by	ADP
aiti-13523	5	6	an	an	DET
aiti-13523	5	7	explainable	explainable	ADJ
aiti-13523	5	8	model	model	NOUN
aiti-13523	5	9	,	,	PUNCT
aiti-13523	5	10	lime	lime	NOUN
aiti-13523	5	11	,	,	PUNCT
aiti-13523	5	12	to	to	PART
aiti-13523	5	13	understand	understand	VERB
aiti-13523	5	14	the	the	DET
aiti-13523	5	15	shortcomings	shortcoming	NOUN
aiti-13523	5	16	of	of	ADP
aiti-13523	5	17	the	the	DET
aiti-13523	5	18	classification	classification	NOUN
aiti-13523	5	19	results	result	NOUN
aiti-13523	5	20	.	.	PUNCT
aiti-13523	6	1	the	the	DET
aiti-13523	6	2	results	result	NOUN
aiti-13523	6	3	highlight	highlight	VERB
aiti-13523	6	4	the	the	DET
aiti-13523	6	5	superior	superior	ADJ
aiti-13523	6	6	performance	performance	NOUN
aiti-13523	6	7	of	of	ADP
aiti-13523	6	8	the	the	DET
aiti-13523	6	9	bert	bert	PROPN
aiti-13523	6	10	and	and	CCONJ
aiti-13523	6	11	lstm	lstm	NOUN
aiti-13523	6	12	models	model	NOUN
aiti-13523	6	13	with	with	ADP
aiti-13523	6	14	an	an	DET
aiti-13523	6	15	f1	f1	NOUN
aiti-13523	6	16	-	-	PUNCT
aiti-13523	6	17	score	score	NOUN
aiti-13523	6	18	of	of	ADP
aiti-13523	6	19	89	89	NUM
aiti-13523	6	20	%	%	NOUN
aiti-13523	6	21	.	.	PUNCT
aiti-13523	7	1	keywords	keyword	NOUN
aiti-13523	7	2	:	:	PUNCT
aiti-13523	7	3	sentiment	sentiment	NOUN
aiti-13523	7	4	analysis	analysis	NOUN
aiti-13523	7	5	,	,	PUNCT
aiti-13523	7	6	data	datum	NOUN
aiti-13523	7	7	re	re	NOUN
aiti-13523	7	8	-	-	NOUN
aiti-13523	7	9	sampling	sample	VERB
aiti-13523	7	10	,	,	PUNCT
aiti-13523	7	11	lstm	lstm	ADJ
aiti-13523	7	12	,	,	PUNCT
aiti-13523	7	13	bert	bert	PROPN
aiti-13523	7	14	,	,	PUNCT
aiti-13523	7	15	lime	lime	NOUN
aiti-13523	7	16	1	1	NUM
aiti-13523	7	17	.	.	PUNCT
aiti-13523	8	1	introduction	introduction	NOUN
aiti-13523	8	2	sentiment	sentiment	NOUN
aiti-13523	8	3	analysis	analysis	NOUN
aiti-13523	8	4	has	have	AUX
aiti-13523	8	5	become	become	VERB
aiti-13523	8	6	an	an	DET
aiti-13523	8	7	important	important	ADJ
aiti-13523	8	8	area	area	NOUN
aiti-13523	8	9	of	of	ADP
aiti-13523	8	10	research	research	NOUN
aiti-13523	8	11	in	in	ADP
aiti-13523	8	12	natural	natural	ADJ
aiti-13523	8	13	language	language	NOUN
aiti-13523	8	14	processing	processing	NOUN
aiti-13523	8	15	(	(	PUNCT
aiti-13523	8	16	nlp	nlp	NOUN
aiti-13523	8	17	)	)	PUNCT
aiti-13523	8	18	,	,	PUNCT
aiti-13523	8	19	driven	drive	VERB
aiti-13523	8	20	by	by	ADP
aiti-13523	8	21	the	the	DET
aiti-13523	8	22	proliferation	proliferation	NOUN
aiti-13523	8	23	of	of	ADP
aiti-13523	8	24	social	social	ADJ
aiti-13523	8	25	media	medium	NOUN
aiti-13523	8	26	platforms	platform	NOUN
aiti-13523	8	27	and	and	CCONJ
aiti-13523	8	28	online	online	ADJ
aiti-13523	8	29	tools	tool	NOUN
aiti-13523	8	30	for	for	ADP
aiti-13523	8	31	sharing	share	VERB
aiti-13523	8	32	information	information	NOUN
aiti-13523	8	33	.	.	PUNCT
aiti-13523	9	1	these	these	DET
aiti-13523	9	2	platforms	platform	NOUN
aiti-13523	9	3	have	have	AUX
aiti-13523	9	4	revolutionized	revolutionize	VERB
aiti-13523	9	5	modern	modern	ADJ
aiti-13523	9	6	communication	communication	NOUN
aiti-13523	9	7	,	,	PUNCT
aiti-13523	9	8	allowing	allow	VERB
aiti-13523	9	9	individuals	individual	NOUN
aiti-13523	9	10	to	to	PART
aiti-13523	9	11	express	express	VERB
aiti-13523	9	12	their	their	PRON
aiti-13523	9	13	emotions	emotion	NOUN
aiti-13523	9	14	and	and	CCONJ
aiti-13523	9	15	opinions	opinion	NOUN
aiti-13523	9	16	online	online	ADV
aiti-13523	9	17	and	and	CCONJ
aiti-13523	9	18	providing	provide	VERB
aiti-13523	9	19	valuable	valuable	ADJ
aiti-13523	9	20	information	information	NOUN
aiti-13523	9	21	about	about	ADP
aiti-13523	9	22	their	their	PRON
aiti-13523	9	23	thoughts	thought	NOUN
aiti-13523	9	24	and	and	CCONJ
aiti-13523	9	25	attitudes	attitude	NOUN
aiti-13523	9	26	.	.	PUNCT
aiti-13523	10	1	consequently	consequently	ADV
aiti-13523	10	2	,	,	PUNCT
aiti-13523	10	3	several	several	ADJ
aiti-13523	10	4	works	work	NOUN
aiti-13523	10	5	have	have	AUX
aiti-13523	10	6	focused	focus	VERB
aiti-13523	10	7	on	on	ADP
aiti-13523	10	8	the	the	DET
aiti-13523	10	9	analysis	analysis	NOUN
aiti-13523	10	10	of	of	ADP
aiti-13523	10	11	sentiments	sentiment	NOUN
aiti-13523	10	12	from	from	ADP
aiti-13523	10	13	data	datum	NOUN
aiti-13523	10	14	extracted	extract	VERB
aiti-13523	10	15	from	from	ADP
aiti-13523	10	16	the	the	DET
aiti-13523	10	17	web	web	NOUN
aiti-13523	10	18	:	:	PUNCT
aiti-13523	10	19	for	for	ADP
aiti-13523	10	20	example	example	NOUN
aiti-13523	10	21	,	,	PUNCT
aiti-13523	10	22	during	during	ADP
aiti-13523	10	23	the	the	DET
aiti-13523	10	24	covid	covid	PROPN
aiti-13523	10	25	pandemic	pandemic	NOUN
aiti-13523	10	26	,	,	PUNCT
aiti-13523	10	27	as	as	SCONJ
aiti-13523	10	28	studied	study	VERB
aiti-13523	10	29	by	by	ADP
aiti-13523	10	30	madani	madani	PROPN
aiti-13523	10	31	et	et	PROPN
aiti-13523	10	32	al	al	PROPN
aiti-13523	10	33	.	.	PUNCT
aiti-13523	11	1	[	[	X
aiti-13523	11	2	1	1	NUM
aiti-13523	11	3	]	]	PUNCT
aiti-13523	11	4	,	,	PUNCT
aiti-13523	11	5	chakraborty	chakraborty	PROPN
aiti-13523	11	6	et	et	PROPN
aiti-13523	11	7	al	al	PROPN
aiti-13523	11	8	.	.	PUNCT
aiti-13523	12	1	[	[	X
aiti-13523	12	2	2	2	NUM
aiti-13523	12	3	]	]	PUNCT
aiti-13523	12	4	,	,	PUNCT
aiti-13523	12	5	xu	xu	PROPN
aiti-13523	12	6	et	et	PROPN
aiti-13523	12	7	al	al	PROPN
aiti-13523	12	8	.	.	PUNCT
aiti-13523	13	1	[	[	X
aiti-13523	13	2	3	3	NUM
aiti-13523	13	3	]	]	PUNCT
aiti-13523	13	4	focused	focus	VERB
aiti-13523	13	5	on	on	ADP
aiti-13523	13	6	the	the	DET
aiti-13523	13	7	analysis	analysis	NOUN
aiti-13523	13	8	of	of	ADP
aiti-13523	13	9	the	the	DET
aiti-13523	13	10	emotions	emotion	NOUN
aiti-13523	13	11	of	of	ADP
aiti-13523	13	12	people	people	NOUN
aiti-13523	13	13	faced	face	VERB
aiti-13523	13	14	with	with	ADP
aiti-13523	13	15	the	the	DET
aiti-13523	13	16	virus	virus	NOUN
aiti-13523	13	17	,	,	PUNCT
aiti-13523	13	18	vaccination	vaccination	NOUN
aiti-13523	13	19	or	or	CCONJ
aiti-13523	13	20	the	the	DET
aiti-13523	13	21	popularity	popularity	NOUN
aiti-13523	13	22	of	of	ADP
aiti-13523	13	23	the	the	DET
aiti-13523	13	24	type	type	NOUN
aiti-13523	13	25	of	of	ADP
aiti-13523	13	26	vaccine	vaccine	NOUN
aiti-13523	13	27	and	and	CCONJ
aiti-13523	13	28	were	be	AUX
aiti-13523	13	29	able	able	ADJ
aiti-13523	13	30	to	to	PART
aiti-13523	13	31	provide	provide	VERB
aiti-13523	13	32	interesting	interesting	ADJ
aiti-13523	13	33	information	information	NOUN
aiti-13523	13	34	on	on	ADP
aiti-13523	13	35	the	the	DET
aiti-13523	13	36	ground	ground	NOUN
aiti-13523	13	37	.	.	PUNCT
aiti-13523	14	1	in	in	ADP
aiti-13523	14	2	addition	addition	NOUN
aiti-13523	14	3	,	,	PUNCT
aiti-13523	14	4	analyzing	analyze	VERB
aiti-13523	14	5	people	people	NOUN
aiti-13523	14	6	’s	’s	PART
aiti-13523	14	7	emotions	emotion	NOUN
aiti-13523	14	8	,	,	PUNCT
aiti-13523	14	9	especially	especially	ADV
aiti-13523	14	10	those	those	PRON
aiti-13523	14	11	facing	face	VERB
aiti-13523	14	12	serious	serious	ADJ
aiti-13523	14	13	health	health	NOUN
aiti-13523	14	14	problems	problem	NOUN
aiti-13523	14	15	such	such	ADJ
aiti-13523	14	16	as	as	ADP
aiti-13523	14	17	cancer	cancer	NOUN
aiti-13523	14	18	,	,	PUNCT
aiti-13523	14	19	dementia	dementia	NOUN
aiti-13523	14	20	,	,	PUNCT
aiti-13523	14	21	and	and	CCONJ
aiti-13523	14	22	aids	aids	PROPN
aiti-13523	14	23	,	,	PUNCT
aiti-13523	14	24	proves	prove	VERB
aiti-13523	14	25	to	to	PART
aiti-13523	14	26	be	be	AUX
aiti-13523	14	27	very	very	ADV
aiti-13523	14	28	important	important	ADJ
aiti-13523	14	29	in	in	ADP
aiti-13523	14	30	the	the	DET
aiti-13523	14	31	fields	field	NOUN
aiti-13523	14	32	of	of	ADP
aiti-13523	14	33	mental	mental	ADJ
aiti-13523	14	34	health	health	NOUN
aiti-13523	14	35	and	and	CCONJ
aiti-13523	14	36	cognitive	cognitive	ADJ
aiti-13523	14	37	psychology	psychology	NOUN
aiti-13523	14	38	.	.	PUNCT
aiti-13523	15	1	many	many	ADJ
aiti-13523	15	2	professionals	professional	NOUN
aiti-13523	15	3	in	in	ADP
aiti-13523	15	4	the	the	DET
aiti-13523	15	5	field	field	NOUN
aiti-13523	15	6	highlight	highlight	VERB
aiti-13523	15	7	the	the	DET
aiti-13523	15	8	fact	fact	NOUN
aiti-13523	15	9	that	that	SCONJ
aiti-13523	15	10	emotional	emotional	ADJ
aiti-13523	15	11	health	health	NOUN
aiti-13523	15	12	is	be	AUX
aiti-13523	15	13	a	a	DET
aiti-13523	15	14	crucial	crucial	ADJ
aiti-13523	15	15	aspect	aspect	NOUN
aiti-13523	15	16	of	of	ADP
aiti-13523	15	17	overall	overall	ADJ
aiti-13523	15	18	well	well	ADV
aiti-13523	15	19	-	-	PUNCT
aiti-13523	15	20	being	being	NOUN
aiti-13523	15	21	.	.	PUNCT
aiti-13523	16	1	positive	positive	ADJ
aiti-13523	16	2	emotions	emotion	NOUN
aiti-13523	16	3	can	can	AUX
aiti-13523	16	4	promote	promote	VERB
aiti-13523	16	5	the	the	DET
aiti-13523	16	6	healing	healing	NOUN
aiti-13523	16	7	process	process	NOUN
aiti-13523	16	8	,	,	PUNCT
aiti-13523	16	9	whereas	whereas	SCONJ
aiti-13523	16	10	negative	negative	ADJ
aiti-13523	16	11	emotions	emotion	NOUN
aiti-13523	16	12	may	may	AUX
aiti-13523	16	13	worsen	worsen	VERB
aiti-13523	16	14	both	both	DET
aiti-13523	16	15	the	the	DET
aiti-13523	16	16	emotional	emotional	ADJ
aiti-13523	16	17	and	and	CCONJ
aiti-13523	16	18	physical	physical	ADJ
aiti-13523	16	19	state	state	NOUN
aiti-13523	16	20	of	of	ADP
aiti-13523	16	21	patients	patient	NOUN
aiti-13523	16	22	.	.	PUNCT
aiti-13523	17	1	thus	thus	ADV
aiti-13523	17	2	,	,	PUNCT
aiti-13523	17	3	automatically	automatically	ADV
aiti-13523	17	4	analyzing	analyze	VERB
aiti-13523	17	5	patient	patient	ADJ
aiti-13523	17	6	feelings	feeling	NOUN
aiti-13523	17	7	using	use	VERB
aiti-13523	17	8	robust	robust	ADJ
aiti-13523	17	9	artificial	artificial	ADJ
aiti-13523	17	10	intelligence	intelligence	NOUN
aiti-13523	17	11	(	(	PUNCT
aiti-13523	17	12	ai	ai	NOUN
aiti-13523	17	13	)	)	PUNCT
aiti-13523	17	14	models	model	NOUN
aiti-13523	17	15	on	on	ADP
aiti-13523	17	16	textual	textual	ADJ
aiti-13523	17	17	data	datum	NOUN
aiti-13523	17	18	is	be	AUX
aiti-13523	17	19	a	a	DET
aiti-13523	17	20	major	major	ADJ
aiti-13523	17	21	challenge	challenge	NOUN
aiti-13523	17	22	:	:	PUNCT
aiti-13523	17	23	on	on	ADP
aiti-13523	17	24	one	one	NUM
aiti-13523	17	25	hand	hand	NOUN
aiti-13523	17	26	,	,	PUNCT
aiti-13523	17	27	the	the	DET
aiti-13523	17	28	data	datum	NOUN
aiti-13523	17	29	relating	relate	VERB
aiti-13523	17	30	to	to	ADP
aiti-13523	17	31	patients	patient	NOUN
aiti-13523	17	32	with	with	ADP
aiti-13523	17	33	serious	serious	ADJ
aiti-13523	17	34	illnesses	illness	NOUN
aiti-13523	17	35	are	be	AUX
aiti-13523	17	36	few	few	ADJ
aiti-13523	17	37	.	.	PUNCT
aiti-13523	18	1	identifying	identify	VERB
aiti-13523	18	2	the	the	DET
aiti-13523	18	3	polarity	polarity	NOUN
aiti-13523	18	4	of	of	ADP
aiti-13523	18	5	a	a	DET
aiti-13523	18	6	feeling	feeling	NOUN
aiti-13523	18	7	remains	remain	VERB
aiti-13523	18	8	difficult	difficult	ADJ
aiti-13523	18	9	because	because	SCONJ
aiti-13523	18	10	of	of	ADP
aiti-13523	18	11	the	the	DET
aiti-13523	18	12	ambiguity	ambiguity	NOUN
aiti-13523	18	13	that	that	SCONJ
aiti-13523	18	14	an	an	DET
aiti-13523	18	15	emotion	emotion	NOUN
aiti-13523	18	16	can	can	AUX
aiti-13523	18	17	produce	produce	VERB
aiti-13523	18	18	in	in	ADP
aiti-13523	18	19	textual	textual	ADJ
aiti-13523	18	20	data	datum	NOUN
aiti-13523	18	21	format	format	NOUN
aiti-13523	18	22	.	.	PUNCT
aiti-13523	19	1	in	in	ADP
aiti-13523	19	2	this	this	DET
aiti-13523	19	3	context	context	NOUN
aiti-13523	19	4	,	,	PUNCT
aiti-13523	19	5	producing	produce	VERB
aiti-13523	19	6	models	model	NOUN
aiti-13523	19	7	from	from	ADP
aiti-13523	19	8	ai	ai	NOUN
aiti-13523	19	9	for	for	ADP
aiti-13523	19	10	sentiment	sentiment	NOUN
aiti-13523	19	11	analysis	analysis	NOUN
aiti-13523	19	12	is	be	AUX
aiti-13523	19	13	a	a	DET
aiti-13523	19	14	major	major	ADJ
aiti-13523	19	15	asset	asset	NOUN
aiti-13523	19	16	to	to	PART
aiti-13523	19	17	help	help	VERB
aiti-13523	19	18	professionals	professional	NOUN
aiti-13523	19	19	in	in	ADP
aiti-13523	19	20	the	the	DET
aiti-13523	19	21	field	field	NOUN
aiti-13523	19	22	improve	improve	VERB
aiti-13523	19	23	the	the	DET
aiti-13523	19	24	emotional	emotional	ADJ
aiti-13523	19	25	well	well	NOUN
aiti-13523	19	26	-	-	PUNCT
aiti-13523	19	27	being	being	NOUN
aiti-13523	19	28	of	of	ADP
aiti-13523	19	29	patients	patient	NOUN
aiti-13523	19	30	during	during	ADP
aiti-13523	19	31	the	the	DET
aiti-13523	19	32	healing	healing	NOUN
aiti-13523	19	33	process	process	NOUN
aiti-13523	19	34	,	,	PUNCT
aiti-13523	19	35	by	by	ADP
aiti-13523	19	36	detecting	detect	VERB
aiti-13523	19	37	their	their	PRON
aiti-13523	19	38	feelings	feeling	NOUN
aiti-13523	19	39	whatever	whatever	PRON
aiti-13523	19	40	they	they	PRON
aiti-13523	19	41	are	be	AUX
aiti-13523	19	42	.	.	PUNCT
aiti-13523	20	1	*	*	PUNCT
aiti-13523	20	2	corresponding	correspond	VERB
aiti-13523	20	3	author	author	NOUN
aiti-13523	20	4	.	.	PUNCT
aiti-13523	21	1	e	e	X
aiti-13523	21	2	-	-	NOUN
aiti-13523	21	3	mail	mail	NOUN
aiti-13523	21	4	address	address	NOUN
aiti-13523	21	5	:	:	PUNCT
aiti-13523	21	6	souad.hamzacherif@univ-tlemcen.dz	souad.hamzacherif@univ-tlemcen.dz	PROPN
aiti-13523	21	7	130	130	NUM
aiti-13523	21	8	advances	advance	NOUN
aiti-13523	21	9	in	in	ADP
aiti-13523	21	10	technology	technology	NOUN
aiti-13523	21	11	innovation	innovation	NOUN
aiti-13523	21	12	,	,	PUNCT
aiti-13523	21	13	vol	vol	NOUN
aiti-13523	21	14	.	.	PROPN
aiti-13523	22	1	9	9	NUM
aiti-13523	22	2	,	,	PUNCT
aiti-13523	22	3	no	no	INTJ
aiti-13523	22	4	.	.	NOUN
aiti-13523	22	5	2	2	NUM
aiti-13523	22	6	,	,	PUNCT
aiti-13523	22	7	2024	2024	NUM
aiti-13523	22	8	,	,	PUNCT
aiti-13523	22	9	pp	pp	ADJ
aiti-13523	22	10	.	.	PUNCT
aiti-13523	23	1	129	129	NUM
aiti-13523	23	2	-	-	SYM
aiti-13523	23	3	142	142	NUM
aiti-13523	23	4	however	however	ADV
aiti-13523	23	5	,	,	PUNCT
aiti-13523	23	6	some	some	DET
aiti-13523	23	7	people	people	NOUN
aiti-13523	23	8	,	,	PUNCT
aiti-13523	23	9	particularly	particularly	ADV
aiti-13523	23	10	healthcare	healthcare	NOUN
aiti-13523	23	11	professionals	professional	NOUN
aiti-13523	23	12	,	,	PUNCT
aiti-13523	23	13	are	be	AUX
aiti-13523	23	14	somehow	somehow	ADV
aiti-13523	23	15	hostile	hostile	ADJ
aiti-13523	23	16	to	to	ADP
aiti-13523	23	17	the	the	DET
aiti-13523	23	18	idea	idea	NOUN
aiti-13523	23	19	of	of	ADP
aiti-13523	23	20	using	use	VERB
aiti-13523	23	21	ai	ai	NOUN
aiti-13523	23	22	;	;	PUNCT
aiti-13523	23	23	because	because	SCONJ
aiti-13523	23	24	ai	ai	NOUN
aiti-13523	23	25	models	model	NOUN
aiti-13523	23	26	can	can	AUX
aiti-13523	23	27	be	be	AUX
aiti-13523	23	28	seen	see	VERB
aiti-13523	23	29	as	as	ADP
aiti-13523	23	30	black	black	ADJ
aiti-13523	23	31	boxes	box	NOUN
aiti-13523	23	32	,	,	PUNCT
aiti-13523	23	33	that	that	PRON
aiti-13523	23	34	distrust	distrust	VERB
aiti-13523	23	35	its	its	PRON
aiti-13523	23	36	performance	performance	NOUN
aiti-13523	23	37	.	.	PUNCT
aiti-13523	24	1	understanding	understand	VERB
aiti-13523	24	2	the	the	DET
aiti-13523	24	3	mechanisms	mechanism	NOUN
aiti-13523	24	4	underlying	underlie	VERB
aiti-13523	24	5	these	these	DET
aiti-13523	24	6	predictions	prediction	NOUN
aiti-13523	24	7	,	,	PUNCT
aiti-13523	24	8	particularly	particularly	ADV
aiti-13523	24	9	in	in	ADP
aiti-13523	24	10	health	health	NOUN
aiti-13523	24	11	applications	application	NOUN
aiti-13523	24	12	,	,	PUNCT
aiti-13523	24	13	is	be	AUX
aiti-13523	24	14	a	a	DET
aiti-13523	24	15	major	major	ADJ
aiti-13523	24	16	asset	asset	NOUN
aiti-13523	24	17	for	for	ADP
aiti-13523	24	18	the	the	DET
aiti-13523	24	19	usability	usability	NOUN
aiti-13523	24	20	of	of	ADP
aiti-13523	24	21	diagnostic	diagnostic	ADJ
aiti-13523	24	22	support	support	NOUN
aiti-13523	24	23	and	and	CCONJ
aiti-13523	24	24	data	datum	NOUN
aiti-13523	24	25	analysis	analysis	NOUN
aiti-13523	24	26	systems	system	NOUN
aiti-13523	24	27	that	that	PRON
aiti-13523	24	28	use	use	VERB
aiti-13523	24	29	ai	ai	NOUN
aiti-13523	24	30	models	model	NOUN
aiti-13523	24	31	.	.	PUNCT
aiti-13523	25	1	ensuring	ensure	VERB
aiti-13523	25	2	transparency	transparency	NOUN
aiti-13523	25	3	and	and	CCONJ
aiti-13523	25	4	explaining	explain	VERB
aiti-13523	25	5	the	the	DET
aiti-13523	25	6	results	result	NOUN
aiti-13523	25	7	of	of	ADP
aiti-13523	25	8	the	the	DET
aiti-13523	25	9	inference	inference	NOUN
aiti-13523	25	10	produced	produce	VERB
aiti-13523	25	11	by	by	ADP
aiti-13523	25	12	artificial	artificial	ADJ
aiti-13523	25	13	learning	learning	NOUN
aiti-13523	25	14	models	model	NOUN
aiti-13523	25	15	is	be	AUX
aiti-13523	25	16	a	a	DET
aiti-13523	25	17	factor	factor	NOUN
aiti-13523	25	18	of	of	ADP
aiti-13523	25	19	confidence	confidence	NOUN
aiti-13523	25	20	in	in	ADP
aiti-13523	25	21	the	the	DET
aiti-13523	25	22	developed	develop	VERB
aiti-13523	25	23	tool	tool	NOUN
aiti-13523	25	24	,	,	PUNCT
aiti-13523	25	25	and	and	CCONJ
aiti-13523	25	26	a	a	DET
aiti-13523	25	27	pillar	pillar	NOUN
aiti-13523	25	28	of	of	ADP
aiti-13523	25	29	ai	ai	PROPN
aiti-13523	25	30	ethics	ethic	NOUN
aiti-13523	25	31	,	,	PUNCT
aiti-13523	25	32	particularly	particularly	ADV
aiti-13523	25	33	for	for	ADP
aiti-13523	25	34	the	the	DET
aiti-13523	25	35	classification	classification	NOUN
aiti-13523	25	36	of	of	ADP
aiti-13523	25	37	textual	textual	ADJ
aiti-13523	25	38	data	datum	NOUN
aiti-13523	25	39	which	which	PRON
aiti-13523	25	40	have	have	VERB
aiti-13523	25	41	the	the	DET
aiti-13523	25	42	disadvantage	disadvantage	NOUN
aiti-13523	25	43	of	of	ADP
aiti-13523	25	44	often	often	ADV
aiti-13523	25	45	being	be	AUX
aiti-13523	25	46	ambiguous	ambiguous	ADJ
aiti-13523	25	47	and	and	CCONJ
aiti-13523	25	48	can	can	AUX
aiti-13523	25	49	lead	lead	VERB
aiti-13523	25	50	to	to	ADP
aiti-13523	25	51	confusion	confusion	NOUN
aiti-13523	25	52	.	.	PUNCT
aiti-13523	26	1	in	in	ADP
aiti-13523	26	2	this	this	DET
aiti-13523	26	3	paper	paper	NOUN
aiti-13523	26	4	,	,	PUNCT
aiti-13523	26	5	emotion	emotion	NOUN
aiti-13523	26	6	classification	classification	NOUN
aiti-13523	26	7	is	be	AUX
aiti-13523	26	8	delved	delve	VERB
aiti-13523	26	9	deeper	deeply	ADV
aiti-13523	26	10	into	into	ADP
aiti-13523	26	11	health	health	NOUN
aiti-13523	26	12	-	-	PUNCT
aiti-13523	26	13	related	relate	VERB
aiti-13523	26	14	text	text	NOUN
aiti-13523	26	15	data	datum	NOUN
aiti-13523	26	16	,	,	PUNCT
aiti-13523	26	17	specifically	specifically	ADV
aiti-13523	26	18	the	the	DET
aiti-13523	26	19	emohd	emohd	NOUN
aiti-13523	26	20	dataset	dataset	VERB
aiti-13523	26	21	[	[	X
aiti-13523	26	22	4	4	NUM
aiti-13523	26	23	]	]	PUNCT
aiti-13523	26	24	,	,	PUNCT
aiti-13523	26	25	using	use	VERB
aiti-13523	26	26	learning	learning	NOUN
aiti-13523	26	27	models	model	NOUN
aiti-13523	26	28	based	base	VERB
aiti-13523	26	29	on	on	ADP
aiti-13523	26	30	neural	neural	ADJ
aiti-13523	26	31	networks	network	NOUN
aiti-13523	26	32	and	and	CCONJ
aiti-13523	26	33	deep	deep	ADJ
aiti-13523	26	34	neural	neural	ADJ
aiti-13523	26	35	networks	network	NOUN
aiti-13523	26	36	.	.	PUNCT
aiti-13523	27	1	this	this	DET
aiti-13523	27	2	dataset	dataset	NOUN
aiti-13523	27	3	includes	include	VERB
aiti-13523	27	4	4,202	4,202	NUM
aiti-13523	27	5	text	text	NOUN
aiti-13523	27	6	samples	sample	NOUN
aiti-13523	27	7	,	,	PUNCT
aiti-13523	27	8	collected	collect	VERB
aiti-13523	27	9	from	from	ADP
aiti-13523	27	10	different	different	ADJ
aiti-13523	27	11	online	online	ADJ
aiti-13523	27	12	sites	site	NOUN
aiti-13523	27	13	,	,	PUNCT
aiti-13523	27	14	containing	contain	VERB
aiti-13523	27	15	information	information	NOUN
aiti-13523	27	16	related	relate	VERB
aiti-13523	27	17	to	to	ADP
aiti-13523	27	18	more	more	ADJ
aiti-13523	27	19	than	than	ADP
aiti-13523	27	20	eight	eight	NUM
aiti-13523	27	21	classes	class	NOUN
aiti-13523	27	22	of	of	ADP
aiti-13523	27	23	serious	serious	ADJ
aiti-13523	27	24	diseases	disease	NOUN
aiti-13523	27	25	such	such	ADJ
aiti-13523	27	26	as	as	ADP
aiti-13523	27	27	hiv	hiv	PROPN
aiti-13523	27	28	/	/	SYM
aiti-13523	27	29	aids	aids	PROPN
aiti-13523	27	30	,	,	PUNCT
aiti-13523	27	31	dengue	dengue	NOUN
aiti-13523	27	32	,	,	PUNCT
aiti-13523	27	33	hepatitis	hepatitis	NOUN
aiti-13523	27	34	,	,	PUNCT
aiti-13523	27	35	malaria	malaria	NOUN
aiti-13523	27	36	,	,	PUNCT
aiti-13523	27	37	influenza	influenza	NOUN
aiti-13523	27	38	,	,	PUNCT
aiti-13523	27	39	coronavirus	coronavirus	NOUN
aiti-13523	27	40	,	,	PUNCT
aiti-13523	27	41	cancer	cancer	NOUN
aiti-13523	27	42	,	,	PUNCT
aiti-13523	27	43	etc	etc	X
aiti-13523	27	44	.	.	X
aiti-13523	28	1	this	this	DET
aiti-13523	28	2	data	data	NOUN
aiti-13523	28	3	is	be	AUX
aiti-13523	28	4	classified	classify	VERB
aiti-13523	28	5	into	into	ADP
aiti-13523	28	6	six	six	NUM
aiti-13523	28	7	different	different	ADJ
aiti-13523	28	8	categories	category	NOUN
aiti-13523	28	9	.	.	PUNCT
aiti-13523	29	1	the	the	DET
aiti-13523	29	2	course	course	NOUN
aiti-13523	29	3	of	of	ADP
aiti-13523	29	4	emotions	emotion	NOUN
aiti-13523	29	5	(	(	PUNCT
aiti-13523	29	6	happy	happy	ADJ
aiti-13523	29	7	,	,	PUNCT
aiti-13523	29	8	sad	sad	ADJ
aiti-13523	29	9	,	,	PUNCT
aiti-13523	29	10	angry	angry	ADJ
aiti-13523	29	11	,	,	PUNCT
aiti-13523	29	12	excited	excited	ADJ
aiti-13523	29	13	,	,	PUNCT
aiti-13523	29	14	bored	bored	ADJ
aiti-13523	29	15	,	,	PUNCT
aiti-13523	29	16	scared	scared	ADJ
aiti-13523	29	17	)	)	PUNCT
aiti-13523	29	18	.	.	PUNCT
aiti-13523	30	1	the	the	DET
aiti-13523	30	2	importance	importance	NOUN
aiti-13523	30	3	of	of	ADP
aiti-13523	30	4	studying	study	VERB
aiti-13523	30	5	such	such	DET
aiti-13523	30	6	a	a	DET
aiti-13523	30	7	dataset	dataset	NOUN
aiti-13523	30	8	is	be	AUX
aiti-13523	30	9	obvious	obvious	ADJ
aiti-13523	30	10	,	,	PUNCT
aiti-13523	30	11	as	as	SCONJ
aiti-13523	30	12	automated	automate	VERB
aiti-13523	30	13	emotion	emotion	NOUN
aiti-13523	30	14	recognition	recognition	NOUN
aiti-13523	30	15	in	in	ADP
aiti-13523	30	16	patient	patient	ADJ
aiti-13523	30	17	health	health	NOUN
aiti-13523	30	18	data	datum	NOUN
aiti-13523	30	19	is	be	AUX
aiti-13523	30	20	essential	essential	ADJ
aiti-13523	30	21	for	for	ADP
aiti-13523	30	22	advancing	advance	VERB
aiti-13523	30	23	to	to	PART
aiti-13523	30	24	improve	improve	VERB
aiti-13523	30	25	research	research	NOUN
aiti-13523	30	26	in	in	ADP
aiti-13523	30	27	this	this	DET
aiti-13523	30	28	area	area	NOUN
aiti-13523	30	29	but	but	CCONJ
aiti-13523	30	30	can	can	AUX
aiti-13523	30	31	also	also	ADV
aiti-13523	30	32	be	be	AUX
aiti-13523	30	33	an	an	DET
aiti-13523	30	34	interesting	interesting	ADJ
aiti-13523	30	35	diagnostic	diagnostic	ADJ
aiti-13523	30	36	aid	aid	NOUN
aiti-13523	30	37	tool	tool	NOUN
aiti-13523	30	38	.	.	PUNCT
aiti-13523	31	1	for	for	ADP
aiti-13523	31	2	cognitive	cognitive	ADJ
aiti-13523	31	3	psychology	psychology	NOUN
aiti-13523	31	4	,	,	PUNCT
aiti-13523	31	5	favoring	favor	VERB
aiti-13523	31	6	the	the	DET
aiti-13523	31	7	analysis	analysis	NOUN
aiti-13523	31	8	of	of	ADP
aiti-13523	31	9	the	the	DET
aiti-13523	31	10	emotional	emotional	ADJ
aiti-13523	31	11	impact	impact	NOUN
aiti-13523	31	12	of	of	ADP
aiti-13523	31	13	patients	patient	NOUN
aiti-13523	31	14	.	.	PUNCT
aiti-13523	32	1	suffering	suffer	VERB
aiti-13523	32	2	from	from	ADP
aiti-13523	32	3	a	a	DET
aiti-13523	32	4	serious	serious	ADJ
aiti-13523	32	5	illness	illness	NOUN
aiti-13523	32	6	in	in	ADP
aiti-13523	32	7	the	the	DET
aiti-13523	32	8	healing	healing	NOUN
aiti-13523	32	9	process	process	NOUN
aiti-13523	32	10	.	.	PUNCT
aiti-13523	33	1	such	such	DET
aiti-13523	33	2	an	an	DET
aiti-13523	33	3	analysis	analysis	NOUN
aiti-13523	33	4	could	could	AUX
aiti-13523	33	5	offer	offer	VERB
aiti-13523	33	6	an	an	DET
aiti-13523	33	7	ideal	ideal	ADJ
aiti-13523	33	8	framework	framework	NOUN
aiti-13523	33	9	to	to	PART
aiti-13523	33	10	follow	follow	VERB
aiti-13523	33	11	the	the	DET
aiti-13523	33	12	emotional	emotional	ADJ
aiti-13523	33	13	evolution	evolution	NOUN
aiti-13523	33	14	of	of	ADP
aiti-13523	33	15	patients	patient	NOUN
aiti-13523	33	16	about	about	ADP
aiti-13523	33	17	the	the	DET
aiti-13523	33	18	progression	progression	NOUN
aiti-13523	33	19	of	of	ADP
aiti-13523	33	20	their	their	PRON
aiti-13523	33	21	illness	illness	NOUN
aiti-13523	33	22	.	.	PUNCT
aiti-13523	34	1	hence	hence	ADV
aiti-13523	34	2	the	the	DET
aiti-13523	34	3	importance	importance	NOUN
aiti-13523	34	4	.	.	PUNCT
aiti-13523	35	1	to	to	PART
aiti-13523	35	2	analyze	analyze	VERB
aiti-13523	35	3	sentiments	sentiment	NOUN
aiti-13523	35	4	in	in	ADP
aiti-13523	35	5	such	such	DET
aiti-13523	35	6	a	a	DET
aiti-13523	35	7	context	context	NOUN
aiti-13523	35	8	,	,	PUNCT
aiti-13523	35	9	especially	especially	ADV
aiti-13523	35	10	since	since	SCONJ
aiti-13523	35	11	datasets	dataset	NOUN
aiti-13523	35	12	related	relate	VERB
aiti-13523	35	13	to	to	ADP
aiti-13523	35	14	sentiments	sentiment	NOUN
aiti-13523	35	15	related	relate	VERB
aiti-13523	35	16	to	to	ADP
aiti-13523	35	17	serious	serious	ADJ
aiti-13523	35	18	illnesses	illness	NOUN
aiti-13523	35	19	are	be	AUX
aiti-13523	35	20	not	not	PART
aiti-13523	35	21	available	available	ADJ
aiti-13523	35	22	.	.	PUNCT
aiti-13523	36	1	this	this	DET
aiti-13523	36	2	work	work	NOUN
aiti-13523	36	3	aims	aim	VERB
aiti-13523	36	4	to	to	PART
aiti-13523	36	5	compare	compare	VERB
aiti-13523	36	6	the	the	DET
aiti-13523	36	7	performance	performance	NOUN
aiti-13523	36	8	of	of	ADP
aiti-13523	36	9	different	different	ADJ
aiti-13523	36	10	machine	machine	NOUN
aiti-13523	36	11	learning	learn	VERB
aiti-13523	36	12	with	with	ADP
aiti-13523	36	13	deep	deep	ADJ
aiti-13523	36	14	learning	learning	NOUN
aiti-13523	36	15	models	model	NOUN
aiti-13523	36	16	:	:	PUNCT
aiti-13523	36	17	logistic	logistic	ADJ
aiti-13523	36	18	regression	regression	NOUN
aiti-13523	36	19	,	,	PUNCT
aiti-13523	36	20	naive	naive	ADJ
aiti-13523	36	21	bayes	bayes	NOUN
aiti-13523	36	22	(	(	PUNCT
aiti-13523	36	23	nb	nb	NOUN
aiti-13523	36	24	)	)	PUNCT
aiti-13523	36	25	,	,	PUNCT
aiti-13523	36	26	lightgbm	lightgbm	ADJ
aiti-13523	36	27	,	,	PUNCT
aiti-13523	36	28	long	long	ADJ
aiti-13523	36	29	short	short	ADJ
aiti-13523	36	30	-	-	PUNCT
aiti-13523	36	31	term	term	NOUN
aiti-13523	36	32	memory	memory	NOUN
aiti-13523	36	33	(	(	PUNCT
aiti-13523	36	34	lstm	lstm	NOUN
aiti-13523	36	35	)	)	PUNCT
aiti-13523	36	36	,	,	PUNCT
aiti-13523	36	37	and	and	CCONJ
aiti-13523	36	38	bidirectional	bidirectional	ADJ
aiti-13523	36	39	encoder	encoder	NOUN
aiti-13523	36	40	representations	representation	VERB
aiti-13523	36	41	from	from	ADP
aiti-13523	36	42	transformers	transformer	NOUN
aiti-13523	36	43	(	(	PUNCT
aiti-13523	36	44	bert	bert	PROPN
aiti-13523	36	45	)	)	PUNCT
aiti-13523	36	46	,	,	PUNCT
aiti-13523	36	47	which	which	PRON
aiti-13523	36	48	are	be	AUX
aiti-13523	36	49	often	often	ADV
aiti-13523	36	50	used	use	VERB
aiti-13523	36	51	in	in	ADP
aiti-13523	36	52	the	the	DET
aiti-13523	36	53	field	field	NOUN
aiti-13523	36	54	of	of	ADP
aiti-13523	36	55	sentiment	sentiment	NOUN
aiti-13523	36	56	analysis	analysis	NOUN
aiti-13523	36	57	.	.	PUNCT
aiti-13523	37	1	and	and	CCONJ
aiti-13523	37	2	explore	explore	VERB
aiti-13523	37	3	them	they	PRON
aiti-13523	37	4	on	on	ADP
aiti-13523	37	5	the	the	DET
aiti-13523	37	6	emohd	emohd	PROPN
aiti-13523	37	7	dataset	dataset	NOUN
aiti-13523	37	8	.	.	PUNCT
aiti-13523	38	1	the	the	DET
aiti-13523	38	2	studied	study	VERB
aiti-13523	38	3	dataset	dataset	NOUN
aiti-13523	38	4	is	be	AUX
aiti-13523	38	5	unbalanced	unbalanced	ADJ
aiti-13523	38	6	;	;	PUNCT
aiti-13523	38	7	different	different	ADJ
aiti-13523	38	8	resampling	resample	VERB
aiti-13523	38	9	methods	method	NOUN
aiti-13523	38	10	are	be	AUX
aiti-13523	38	11	considered	consider	VERB
aiti-13523	38	12	as	as	ADV
aiti-13523	38	13	well	well	ADV
aiti-13523	38	14	as	as	ADP
aiti-13523	38	15	their	their	PRON
aiti-13523	38	16	impact	impact	NOUN
aiti-13523	38	17	on	on	ADP
aiti-13523	38	18	the	the	DET
aiti-13523	38	19	classification	classification	NOUN
aiti-13523	38	20	and	and	CCONJ
aiti-13523	38	21	results	result	NOUN
aiti-13523	38	22	.	.	PUNCT
aiti-13523	39	1	additionally	additionally	ADV
aiti-13523	39	2	,	,	PUNCT
aiti-13523	39	3	the	the	DET
aiti-13523	39	4	analysis	analysis	NOUN
aiti-13523	39	5	of	of	ADP
aiti-13523	39	6	the	the	DET
aiti-13523	39	7	classification	classification	NOUN
aiti-13523	39	8	results	result	NOUN
aiti-13523	39	9	was	be	AUX
aiti-13523	39	10	obtained	obtain	VERB
aiti-13523	39	11	using	use	VERB
aiti-13523	39	12	a	a	DET
aiti-13523	39	13	local	local	ADJ
aiti-13523	39	14	interpretable	interpretable	ADJ
aiti-13523	39	15	model	model	NOUN
aiti-13523	39	16	agnostic	agnostic	ADJ
aiti-13523	39	17	explanation	explanation	NOUN
aiti-13523	39	18	(	(	PUNCT
aiti-13523	39	19	lime	lime	NOUN
aiti-13523	39	20	)	)	PUNCT
aiti-13523	39	21	local	local	ADJ
aiti-13523	39	22	explainability	explainability	NOUN
aiti-13523	39	23	model	model	NOUN
aiti-13523	39	24	to	to	PART
aiti-13523	39	25	understand	understand	VERB
aiti-13523	39	26	the	the	DET
aiti-13523	39	27	results	result	NOUN
aiti-13523	39	28	of	of	ADP
aiti-13523	39	29	the	the	DET
aiti-13523	39	30	worst	bad	ADJ
aiti-13523	39	31	classifier	classifier	NOUN
aiti-13523	39	32	,	,	PUNCT
aiti-13523	39	33	having	having	AUX
aiti-13523	39	34	obtained	obtain	VERB
aiti-13523	39	35	the	the	DET
aiti-13523	39	36	wrong	wrong	ADJ
aiti-13523	39	37	classification	classification	NOUN
aiti-13523	39	38	score	score	NOUN
aiti-13523	39	39	.	.	PUNCT
aiti-13523	40	1	the	the	DET
aiti-13523	40	2	key	key	ADJ
aiti-13523	40	3	stages	stage	NOUN
aiti-13523	40	4	of	of	ADP
aiti-13523	40	5	this	this	DET
aiti-13523	40	6	study	study	NOUN
aiti-13523	40	7	concern	concern	NOUN
aiti-13523	40	8	:	:	PUNCT
aiti-13523	40	9	(	(	PUNCT
aiti-13523	40	10	1	1	X
aiti-13523	40	11	)	)	PUNCT
aiti-13523	40	12	implementing	implement	VERB
aiti-13523	40	13	data	datum	NOUN
aiti-13523	40	14	preprocessing	preprocessing	NOUN
aiti-13523	40	15	tasks	task	NOUN
aiti-13523	40	16	and	and	CCONJ
aiti-13523	40	17	various	various	ADJ
aiti-13523	40	18	data	datum	NOUN
aiti-13523	40	19	re	re	VERB
aiti-13523	40	20	-	-	VERB
aiti-13523	40	21	sampling	sample	VERB
aiti-13523	40	22	techniques	technique	NOUN
aiti-13523	40	23	(	(	PUNCT
aiti-13523	40	24	nearmiss	nearmiss	ADJ
aiti-13523	40	25	,	,	PUNCT
aiti-13523	40	26	smote	smote	ADJ
aiti-13523	40	27	,	,	PUNCT
aiti-13523	40	28	adasyn	adasyn	PROPN
aiti-13523	40	29	)	)	PUNCT
aiti-13523	40	30	.	.	PUNCT
aiti-13523	41	1	(	(	PUNCT
aiti-13523	41	2	2	2	X
aiti-13523	41	3	)	)	PUNCT
aiti-13523	41	4	conducting	conduct	VERB
aiti-13523	41	5	sentiment	sentiment	NOUN
aiti-13523	41	6	classification	classification	NOUN
aiti-13523	41	7	on	on	ADP
aiti-13523	41	8	input	input	NOUN
aiti-13523	41	9	data	datum	NOUN
aiti-13523	41	10	using	use	VERB
aiti-13523	41	11	feature	feature	NOUN
aiti-13523	41	12	selection	selection	NOUN
aiti-13523	41	13	methods	method	NOUN
aiti-13523	41	14	(	(	PUNCT
aiti-13523	41	15	continuous	continuous	ADJ
aiti-13523	41	16	bag	bag	NOUN
aiti-13523	41	17	-	-	PUNCT
aiti-13523	41	18	of	of	ADP
aiti-13523	41	19	-	-	PUNCT
aiti-13523	41	20	words	word	NOUN
aiti-13523	41	21	(	(	PUNCT
aiti-13523	41	22	cbow	cbow	PROPN
aiti-13523	41	23	)	)	PUNCT
aiti-13523	41	24	,	,	PUNCT
aiti-13523	41	25	term	term	NOUN
aiti-13523	41	26	frequency	frequency	NOUN
aiti-13523	41	27	-	-	PUNCT
aiti-13523	41	28	inverse	inverse	NOUN
aiti-13523	41	29	document	document	NOUN
aiti-13523	41	30	frequency	frequency	NOUN
aiti-13523	41	31	(	(	PUNCT
aiti-13523	41	32	tf	tf	PROPN
aiti-13523	41	33	-	-	PUNCT
aiti-13523	41	34	idf	idf	NOUN
aiti-13523	41	35	)	)	PUNCT
aiti-13523	41	36	,	,	PUNCT
aiti-13523	41	37	word2vec	word2vec	X
aiti-13523	41	38	)	)	PUNCT
aiti-13523	41	39	and	and	CCONJ
aiti-13523	41	40	machine	machine	NOUN
aiti-13523	41	41	learning	learn	VERB
aiti-13523	41	42	classification	classification	NOUN
aiti-13523	41	43	through	through	ADP
aiti-13523	41	44	base	base	NOUN
aiti-13523	41	45	models	model	NOUN
aiti-13523	41	46	(	(	PUNCT
aiti-13523	41	47	logistic	logistic	ADJ
aiti-13523	41	48	regression	regression	NOUN
aiti-13523	41	49	,	,	PUNCT
aiti-13523	41	50	nb	nb	INTJ
aiti-13523	41	51	,	,	PUNCT
aiti-13523	41	52	lightgbm	lightgbm	ADJ
aiti-13523	41	53	)	)	PUNCT
aiti-13523	41	54	.	.	PUNCT
aiti-13523	42	1	(	(	PUNCT
aiti-13523	42	2	3	3	X
aiti-13523	42	3	)	)	PUNCT
aiti-13523	42	4	comparing	compare	VERB
aiti-13523	42	5	the	the	DET
aiti-13523	42	6	classifications	classification	NOUN
aiti-13523	42	7	obtained	obtain	VERB
aiti-13523	42	8	after	after	ADP
aiti-13523	42	9	rebalancing	rebalance	VERB
aiti-13523	42	10	the	the	DET
aiti-13523	42	11	database	database	NOUN
aiti-13523	42	12	using	use	VERB
aiti-13523	42	13	both	both	CCONJ
aiti-13523	42	14	basic	basic	ADJ
aiti-13523	42	15	models	model	NOUN
aiti-13523	42	16	and	and	CCONJ
aiti-13523	42	17	recurrent	recurrent	ADJ
aiti-13523	42	18	deep	deep	ADJ
aiti-13523	42	19	learning	learning	NOUN
aiti-13523	42	20	networks	network	NOUN
aiti-13523	42	21	,	,	PUNCT
aiti-13523	42	22	specifically	specifically	ADV
aiti-13523	42	23	lstm	lstm	ADJ
aiti-13523	42	24	and	and	CCONJ
aiti-13523	42	25	bert	bert	PROPN
aiti-13523	42	26	from	from	ADP
aiti-13523	42	27	transformers	transformer	NOUN
aiti-13523	42	28	.	.	PUNCT
aiti-13523	43	1	(	(	PUNCT
aiti-13523	43	2	4	4	X
aiti-13523	43	3	)	)	PUNCT
aiti-13523	43	4	analyzes	analyze	VERB
aiti-13523	43	5	classification	classification	NOUN
aiti-13523	43	6	predictions	prediction	NOUN
aiti-13523	43	7	utilizing	utilize	VERB
aiti-13523	43	8	word	word	NOUN
aiti-13523	43	9	embeddings	embedding	NOUN
aiti-13523	43	10	with	with	ADP
aiti-13523	43	11	lime	lime	NOUN
aiti-13523	43	12	.	.	PUNCT
aiti-13523	44	1	the	the	DET
aiti-13523	44	2	rest	rest	NOUN
aiti-13523	44	3	of	of	ADP
aiti-13523	44	4	this	this	DET
aiti-13523	44	5	article	article	NOUN
aiti-13523	44	6	is	be	AUX
aiti-13523	44	7	structured	structure	VERB
aiti-13523	44	8	as	as	SCONJ
aiti-13523	44	9	follows	follow	VERB
aiti-13523	44	10	:	:	PUNCT
aiti-13523	44	11	section	section	NOUN
aiti-13523	44	12	2	2	NUM
aiti-13523	44	13	covers	cover	VERB
aiti-13523	44	14	a	a	DET
aiti-13523	44	15	study	study	NOUN
aiti-13523	44	16	of	of	ADP
aiti-13523	44	17	related	related	ADJ
aiti-13523	44	18	work	work	NOUN
aiti-13523	44	19	in	in	ADP
aiti-13523	44	20	the	the	DET
aiti-13523	44	21	field	field	NOUN
aiti-13523	44	22	,	,	PUNCT
aiti-13523	44	23	section	section	NOUN
aiti-13523	44	24	3	3	NUM
aiti-13523	44	25	presents	present	VERB
aiti-13523	44	26	the	the	DET
aiti-13523	44	27	approach	approach	NOUN
aiti-13523	44	28	proposed	propose	VERB
aiti-13523	44	29	in	in	ADP
aiti-13523	44	30	this	this	DET
aiti-13523	44	31	study	study	NOUN
aiti-13523	44	32	covering	cover	VERB
aiti-13523	44	33	all	all	DET
aiti-13523	44	34	the	the	DET
aiti-13523	44	35	steps	step	NOUN
aiti-13523	44	36	followed	follow	VERB
aiti-13523	44	37	as	as	ADV
aiti-13523	44	38	well	well	ADV
aiti-13523	44	39	as	as	ADP
aiti-13523	44	40	the	the	DET
aiti-13523	44	41	presentation	presentation	NOUN
aiti-13523	44	42	of	of	ADP
aiti-13523	44	43	the	the	DET
aiti-13523	44	44	classification	classification	NOUN
aiti-13523	44	45	models	model	NOUN
aiti-13523	44	46	used	use	VERB
aiti-13523	44	47	and	and	CCONJ
aiti-13523	44	48	the	the	DET
aiti-13523	44	49	model	model	NOUN
aiti-13523	44	50	of	of	ADP
aiti-13523	44	51	lime	lime	NOUN
aiti-13523	44	52	explainability	explainability	NOUN
aiti-13523	44	53	.	.	PUNCT
aiti-13523	45	1	in	in	ADP
aiti-13523	45	2	section	section	NOUN
aiti-13523	45	3	4	4	NUM
aiti-13523	45	4	,	,	PUNCT
aiti-13523	45	5	the	the	DET
aiti-13523	45	6	experimental	experimental	ADJ
aiti-13523	45	7	results	result	NOUN
aiti-13523	45	8	are	be	AUX
aiti-13523	45	9	presented	present	VERB
aiti-13523	45	10	and	and	CCONJ
aiti-13523	45	11	analyzed	analyze	VERB
aiti-13523	45	12	.	.	PUNCT
aiti-13523	46	1	finally	finally	ADV
aiti-13523	46	2	,	,	PUNCT
aiti-13523	46	3	in	in	ADP
aiti-13523	46	4	the	the	DET
aiti-13523	46	5	last	last	ADJ
aiti-13523	46	6	section	section	NOUN
aiti-13523	46	7	conclusions	conclusion	NOUN
aiti-13523	46	8	and	and	CCONJ
aiti-13523	46	9	a	a	DET
aiti-13523	46	10	discussion	discussion	NOUN
aiti-13523	46	11	on	on	ADP
aiti-13523	46	12	potential	potential	ADJ
aiti-13523	46	13	directions	direction	NOUN
aiti-13523	46	14	for	for	ADP
aiti-13523	46	15	future	future	ADJ
aiti-13523	46	16	work	work	NOUN
aiti-13523	46	17	are	be	AUX
aiti-13523	46	18	drawn	draw	VERB
aiti-13523	46	19	.	.	PUNCT
aiti-13523	47	1	2	2	X
aiti-13523	47	2	.	.	NUM
aiti-13523	47	3	related	relate	VERB
aiti-13523	47	4	works	work	NOUN
aiti-13523	47	5	sentiment	sentiment	NOUN
aiti-13523	47	6	analysis	analysis	NOUN
aiti-13523	47	7	is	be	AUX
aiti-13523	47	8	a	a	DET
aiti-13523	47	9	field	field	NOUN
aiti-13523	47	10	in	in	ADP
aiti-13523	47	11	constant	constant	ADJ
aiti-13523	47	12	evolution	evolution	NOUN
aiti-13523	47	13	.	.	PUNCT
aiti-13523	48	1	several	several	ADJ
aiti-13523	48	2	current	current	ADJ
aiti-13523	48	3	works	work	NOUN
aiti-13523	48	4	have	have	AUX
aiti-13523	48	5	focused	focus	VERB
aiti-13523	48	6	on	on	ADP
aiti-13523	48	7	this	this	DET
aiti-13523	48	8	problem	problem	NOUN
aiti-13523	48	9	,	,	PUNCT
aiti-13523	48	10	especially	especially	ADV
aiti-13523	48	11	with	with	ADP
aiti-13523	48	12	the	the	DET
aiti-13523	48	13	advent	advent	NOUN
aiti-13523	48	14	of	of	ADP
aiti-13523	48	15	the	the	DET
aiti-13523	48	16	social	social	ADJ
aiti-13523	48	17	and	and	CCONJ
aiti-13523	48	18	semantic	semantic	ADJ
aiti-13523	48	19	web	web	NOUN
aiti-13523	48	20	which	which	PRON
aiti-13523	48	21	has	have	AUX
aiti-13523	48	22	offered	offer	VERB
aiti-13523	48	23	sharing	sharing	NOUN
aiti-13523	48	24	tools	tool	NOUN
aiti-13523	48	25	allowing	allow	VERB
aiti-13523	48	26	different	different	ADJ
aiti-13523	48	27	users	user	NOUN
aiti-13523	48	28	to	to	PART
aiti-13523	48	29	express	express	VERB
aiti-13523	48	30	their	their	PRON
aiti-13523	48	31	opinion	opinion	NOUN
aiti-13523	48	32	and	and	CCONJ
aiti-13523	48	33	their	their	PRON
aiti-13523	48	34	feelings	feeling	NOUN
aiti-13523	48	35	,	,	PUNCT
aiti-13523	48	36	thus	thus	ADV
aiti-13523	48	37	offering	offer	VERB
aiti-13523	48	38	the	the	DET
aiti-13523	48	39	researcher	researcher	NOUN
aiti-13523	48	40	in	in	ADP
aiti-13523	48	41	the	the	DET
aiti-13523	48	42	field	field	NOUN
aiti-13523	48	43	the	the	DET
aiti-13523	48	44	possibility	possibility	NOUN
aiti-13523	48	45	of	of	ADP
aiti-13523	48	46	extrapolating	extrapolate	VERB
aiti-13523	48	47	people	people	NOUN
aiti-13523	48	48	’s	’s	PART
aiti-13523	48	49	feelings	feeling	NOUN
aiti-13523	48	50	using	use	VERB
aiti-13523	48	51	different	different	ADJ
aiti-13523	48	52	ai	ai	NOUN
aiti-13523	48	53	and	and	CCONJ
aiti-13523	48	54	nlp	nlp	ADJ
aiti-13523	48	55	tools	tool	NOUN
aiti-13523	48	56	.	.	PUNCT
aiti-13523	49	1	the	the	DET
aiti-13523	49	2	task	task	NOUN
aiti-13523	49	3	of	of	ADP
aiti-13523	49	4	sentiment	sentiment	NOUN
aiti-13523	49	5	analysis	analysis	NOUN
aiti-13523	49	6	from	from	ADP
aiti-13523	49	7	textual	textual	ADJ
aiti-13523	49	8	data	datum	NOUN
aiti-13523	49	9	encompasses	encompass	VERB
aiti-13523	49	10	different	different	ADJ
aiti-13523	49	11	techniques	technique	NOUN
aiti-13523	49	12	such	such	ADJ
aiti-13523	49	13	as	as	ADP
aiti-13523	49	14	lexicon	lexicon	NOUN
aiti-13523	49	15	:	:	PUNCT
aiti-13523	49	16	these	these	DET
aiti-13523	49	17	approaches	approach	NOUN
aiti-13523	49	18	use	use	VERB
aiti-13523	49	19	dictionaries	dictionary	NOUN
aiti-13523	49	20	,	,	PUNCT
aiti-13523	49	21	or	or	CCONJ
aiti-13523	49	22	corpora	corpora	PROPN
aiti-13523	49	23	,	,	PUNCT
aiti-13523	49	24	to	to	PART
aiti-13523	49	25	assign	assign	VERB
aiti-13523	49	26	a	a	DET
aiti-13523	49	27	polarity	polarity	NOUN
aiti-13523	49	28	score	score	NOUN
aiti-13523	49	29	to	to	ADP
aiti-13523	49	30	each	each	DET
aiti-13523	49	31	word	word	NOUN
aiti-13523	49	32	in	in	ADP
aiti-13523	49	33	lists	list	NOUN
aiti-13523	49	34	of	of	ADP
aiti-13523	49	35	manually	manually	ADV
aiti-13523	49	36	classified	classify	VERB
aiti-13523	49	37	words	word	NOUN
aiti-13523	49	38	(	(	PUNCT
aiti-13523	49	39	positive	positive	ADJ
aiti-13523	49	40	or	or	CCONJ
aiti-13523	49	41	negative	negative	ADJ
aiti-13523	49	42	)	)	PUNCT
aiti-13523	49	43	.	.	PUNCT
aiti-13523	50	1	advances	advance	NOUN
aiti-13523	50	2	in	in	ADP
aiti-13523	50	3	technology	technology	NOUN
aiti-13523	50	4	innovation	innovation	NOUN
aiti-13523	50	5	,	,	PUNCT
aiti-13523	50	6	vol	vol	NOUN
aiti-13523	50	7	.	.	PROPN
aiti-13523	50	8	9	9	NUM
aiti-13523	50	9	,	,	PUNCT
aiti-13523	50	10	no	no	INTJ
aiti-13523	50	11	.	.	NOUN
aiti-13523	50	12	2	2	NUM
aiti-13523	50	13	,	,	PUNCT
aiti-13523	50	14	2024	2024	NUM
aiti-13523	50	15	,	,	PUNCT
aiti-13523	50	16	pp	pp	ADJ
aiti-13523	50	17	.	.	PUNCT
aiti-13523	51	1	129	129	NUM
aiti-13523	51	2	-	-	SYM
aiti-13523	51	3	142	142	NUM
aiti-13523	51	4	131	131	NUM
aiti-13523	51	5	for	for	ADP
aiti-13523	51	6	example	example	NOUN
aiti-13523	51	7	,	,	PUNCT
aiti-13523	51	8	in	in	ADP
aiti-13523	51	9	srinivasan	srinivasan	PROPN
aiti-13523	51	10	et	et	PROPN
aiti-13523	51	11	al	al	PROPN
aiti-13523	51	12	.	.	PUNCT
aiti-13523	52	1	[	[	X
aiti-13523	52	2	5	5	NUM
aiti-13523	52	3	]	]	PUNCT
aiti-13523	52	4	,	,	PUNCT
aiti-13523	52	5	researchers	researcher	NOUN
aiti-13523	52	6	used	use	VERB
aiti-13523	52	7	a	a	DET
aiti-13523	52	8	lexicon	lexicon	NOUN
aiti-13523	52	9	-	-	PUNCT
aiti-13523	52	10	based	base	VERB
aiti-13523	52	11	approach	approach	NOUN
aiti-13523	52	12	to	to	PART
aiti-13523	52	13	predict	predict	VERB
aiti-13523	52	14	election	election	NOUN
aiti-13523	52	15	results	result	NOUN
aiti-13523	52	16	using	use	VERB
aiti-13523	52	17	knowledge	knowledge	NOUN
aiti-13523	52	18	of	of	ADP
aiti-13523	52	19	emotion	emotion	NOUN
aiti-13523	52	20	classification	classification	NOUN
aiti-13523	52	21	from	from	ADP
aiti-13523	52	22	twitter	twitter	NOUN
aiti-13523	52	23	data	datum	NOUN
aiti-13523	52	24	related	relate	VERB
aiti-13523	52	25	to	to	ADP
aiti-13523	52	26	the	the	DET
aiti-13523	52	27	election	election	NOUN
aiti-13523	52	28	of	of	ADP
aiti-13523	52	29	hillary	hillary	PROPN
aiti-13523	52	30	clinton	clinton	PROPN
aiti-13523	52	31	and	and	CCONJ
aiti-13523	52	32	donald	donald	PROPN
aiti-13523	52	33	trump	trump	PROPN
aiti-13523	52	34	.	.	PUNCT
aiti-13523	53	1	lin	lin	PROPN
aiti-13523	53	2	and	and	CCONJ
aiti-13523	53	3	liao	liao	PROPN
aiti-13523	54	1	[	[	X
aiti-13523	54	2	6	6	NUM
aiti-13523	54	3	]	]	PUNCT
aiti-13523	54	4	proposed	propose	VERB
aiti-13523	54	5	a	a	DET
aiti-13523	54	6	lexicon	lexicon	NOUN
aiti-13523	54	7	-	-	PUNCT
aiti-13523	54	8	based	base	VERB
aiti-13523	54	9	method	method	NOUN
aiti-13523	54	10	for	for	ADP
aiti-13523	54	11	sentiment	sentiment	NOUN
aiti-13523	54	12	analysis	analysis	NOUN
aiti-13523	54	13	specific	specific	ADJ
aiti-13523	54	14	to	to	ADP
aiti-13523	54	15	the	the	DET
aiti-13523	54	16	financial	financial	ADJ
aiti-13523	54	17	domain	domain	NOUN
aiti-13523	54	18	.	.	PUNCT
aiti-13523	55	1	catelli	catelli	PROPN
aiti-13523	55	2	et	et	PROPN
aiti-13523	55	3	al	al	PROPN
aiti-13523	55	4	.	.	PUNCT
aiti-13523	56	1	[	[	X
aiti-13523	56	2	7	7	X
aiti-13523	56	3	]	]	PUNCT
aiti-13523	56	4	used	use	VERB
aiti-13523	56	5	the	the	DET
aiti-13523	56	6	italian	italian	ADJ
aiti-13523	56	7	sentiment	sentiment	NOUN
aiti-13523	56	8	lexicon	lexicon	NOUN
aiti-13523	56	9	containing	contain	VERB
aiti-13523	56	10	polarized	polarize	VERB
aiti-13523	56	11	words	word	NOUN
aiti-13523	56	12	,	,	PUNCT
aiti-13523	56	13	expressing	express	VERB
aiti-13523	56	14	a	a	DET
aiti-13523	56	15	semantic	semantic	ADJ
aiti-13523	56	16	orientation	orientation	NOUN
aiti-13523	56	17	,	,	PUNCT
aiti-13523	56	18	to	to	PART
aiti-13523	56	19	identify	identify	VERB
aiti-13523	56	20	the	the	DET
aiti-13523	56	21	sentiments	sentiment	NOUN
aiti-13523	56	22	of	of	ADP
aiti-13523	56	23	people	people	NOUN
aiti-13523	56	24	vaccinated	vaccinate	VERB
aiti-13523	56	25	against	against	ADP
aiti-13523	56	26	covid-19	covid-19	PROPN
aiti-13523	56	27	which	which	PRON
aiti-13523	56	28	highlighted	highlight	VERB
aiti-13523	56	29	an	an	DET
aiti-13523	56	30	overall	overall	ADJ
aiti-13523	56	31	negative	negative	ADJ
aiti-13523	56	32	sentiment	sentiment	NOUN
aiti-13523	56	33	.	.	PUNCT
aiti-13523	57	1	other	other	ADJ
aiti-13523	57	2	newswork	newswork	NOUN
aiti-13523	57	3	uses	use	VERB
aiti-13523	57	4	various	various	ADJ
aiti-13523	57	5	machine	machine	NOUN
aiti-13523	57	6	and	and	CCONJ
aiti-13523	57	7	deep	deep	ADJ
aiti-13523	57	8	learning	learning	NOUN
aiti-13523	57	9	techniques	technique	NOUN
aiti-13523	57	10	to	to	PART
aiti-13523	57	11	classify	classify	VERB
aiti-13523	57	12	sentiment	sentiment	NOUN
aiti-13523	57	13	from	from	ADP
aiti-13523	57	14	text	text	NOUN
aiti-13523	57	15	data	datum	NOUN
aiti-13523	57	16	.	.	PUNCT
aiti-13523	58	1	whatever	whatever	PRON
aiti-13523	58	2	the	the	DET
aiti-13523	58	3	method	method	NOUN
aiti-13523	58	4	used	use	VERB
aiti-13523	58	5	,	,	PUNCT
aiti-13523	58	6	it	it	PRON
aiti-13523	58	7	follows	follow	VERB
aiti-13523	58	8	a	a	DET
aiti-13523	58	9	pipeline	pipeline	NOUN
aiti-13523	58	10	of	of	ADP
aiti-13523	58	11	steps	step	NOUN
aiti-13523	58	12	ranging	range	VERB
aiti-13523	58	13	from	from	ADP
aiti-13523	58	14	preprocessing	preprocesse	VERB
aiti-13523	58	15	the	the	DET
aiti-13523	58	16	data	datum	NOUN
aiti-13523	58	17	,	,	PUNCT
aiti-13523	58	18	which	which	PRON
aiti-13523	58	19	is	be	AUX
aiti-13523	58	20	generally	generally	ADV
aiti-13523	58	21	noisy	noisy	ADJ
aiti-13523	58	22	and	and	CCONJ
aiti-13523	58	23	unstructured	unstructure	VERB
aiti-13523	58	24	,	,	PUNCT
aiti-13523	58	25	to	to	PART
aiti-13523	58	26	feature	feature	VERB
aiti-13523	58	27	selection	selection	NOUN
aiti-13523	58	28	and	and	CCONJ
aiti-13523	58	29	vectorization	vectorization	NOUN
aiti-13523	58	30	,	,	PUNCT
aiti-13523	58	31	which	which	PRON
aiti-13523	58	32	consists	consist	VERB
aiti-13523	58	33	of	of	ADP
aiti-13523	58	34	extracting	extract	VERB
aiti-13523	58	35	certain	certain	ADJ
aiti-13523	58	36	distinct	distinct	ADJ
aiti-13523	58	37	features	feature	NOUN
aiti-13523	58	38	from	from	ADP
aiti-13523	58	39	the	the	DET
aiti-13523	58	40	text	text	NOUN
aiti-13523	58	41	on	on	ADP
aiti-13523	58	42	which	which	PRON
aiti-13523	58	43	the	the	DET
aiti-13523	58	44	model	model	NOUN
aiti-13523	58	45	can	can	AUX
aiti-13523	58	46	focus	focus	VERB
aiti-13523	58	47	.	.	PUNCT
aiti-13523	59	1	training	training	NOUN
aiti-13523	59	2	,	,	PUNCT
aiti-13523	59	3	by	by	ADP
aiti-13523	59	4	converting	convert	VERB
aiti-13523	59	5	the	the	DET
aiti-13523	59	6	text	text	NOUN
aiti-13523	59	7	into	into	ADP
aiti-13523	59	8	digital	digital	ADJ
aiti-13523	59	9	vectors	vector	NOUN
aiti-13523	59	10	,	,	PUNCT
aiti-13523	59	11	this	this	DET
aiti-13523	59	12	step	step	NOUN
aiti-13523	59	13	is	be	AUX
aiti-13523	59	14	necessary	necessary	ADJ
aiti-13523	59	15	in	in	ADP
aiti-13523	59	16	the	the	DET
aiti-13523	59	17	case	case	NOUN
aiti-13523	59	18	of	of	ADP
aiti-13523	59	19	using	use	VERB
aiti-13523	59	20	machine	machine	NOUN
aiti-13523	59	21	learning	learning	NOUN
aiti-13523	59	22	models	model	NOUN
aiti-13523	59	23	,	,	PUNCT
aiti-13523	59	24	and	and	CCONJ
aiti-13523	59	25	finally	finally	ADV
aiti-13523	59	26	the	the	DET
aiti-13523	59	27	sentiment	sentiment	NOUN
aiti-13523	59	28	classification	classification	NOUN
aiti-13523	59	29	step	step	NOUN
aiti-13523	59	30	.	.	PUNCT
aiti-13523	60	1	works	work	VERB
aiti-13523	60	2	in	in	ADP
aiti-13523	60	3	this	this	DET
aiti-13523	60	4	case	case	NOUN
aiti-13523	60	5	are	be	AUX
aiti-13523	60	6	abundant	abundant	ADJ
aiti-13523	60	7	in	in	ADP
aiti-13523	60	8	the	the	DET
aiti-13523	60	9	literature	literature	NOUN
aiti-13523	60	10	,	,	PUNCT
aiti-13523	60	11	for	for	ADP
aiti-13523	60	12	example	example	NOUN
aiti-13523	60	13	,	,	PUNCT
aiti-13523	60	14	wise	wise	INTJ
aiti-13523	60	15	et	et	VERB
aiti-13523	60	16	al	al	PROPN
aiti-13523	60	17	.	.	PUNCT
aiti-13523	61	1	[	[	X
aiti-13523	61	2	8	8	NUM
aiti-13523	61	3	]	]	PUNCT
aiti-13523	61	4	proposed	propose	VERB
aiti-13523	61	5	a	a	DET
aiti-13523	61	6	method	method	NOUN
aiti-13523	61	7	based	base	VERB
aiti-13523	61	8	on	on	ADP
aiti-13523	61	9	latent	latent	ADJ
aiti-13523	61	10	semantic	semantic	ADJ
aiti-13523	61	11	analysis	analysis	NOUN
aiti-13523	61	12	(	(	PUNCT
aiti-13523	61	13	lsa	lsa	NOUN
aiti-13523	61	14	)	)	PUNCT
aiti-13523	61	15	of	of	ADP
aiti-13523	61	16	tweets	tweet	NOUN
aiti-13523	61	17	in	in	ADP
aiti-13523	61	18	social	social	ADJ
aiti-13523	61	19	media	medium	NOUN
aiti-13523	61	20	for	for	ADP
aiti-13523	61	21	the	the	DET
aiti-13523	61	22	classification	classification	NOUN
aiti-13523	61	23	of	of	ADP
aiti-13523	61	24	cyberbullying	cyberbullye	VERB
aiti-13523	61	25	texts	text	NOUN
aiti-13523	61	26	and	and	CCONJ
aiti-13523	61	27	achieved	achieve	VERB
aiti-13523	61	28	an	an	DET
aiti-13523	61	29	accuracy	accuracy	NOUN
aiti-13523	61	30	score	score	NOUN
aiti-13523	61	31	of	of	ADP
aiti-13523	61	32	91	91	NUM
aiti-13523	61	33	%	%	NOUN
aiti-13523	61	34	on	on	ADP
aiti-13523	61	35	training	training	NOUN
aiti-13523	61	36	data	datum	NOUN
aiti-13523	61	37	.	.	PUNCT
aiti-13523	62	1	bhaskaran	bhaskaran	PROPN
aiti-13523	62	2	et	et	PROPN
aiti-13523	62	3	al	al	PROPN
aiti-13523	62	4	.	.	PUNCT
aiti-13523	63	1	[	[	X
aiti-13523	63	2	9	9	NUM
aiti-13523	63	3	]	]	PUNCT
aiti-13523	63	4	presented	present	VERB
aiti-13523	63	5	a	a	DET
aiti-13523	63	6	new	new	ADJ
aiti-13523	63	7	modified	modify	VERB
aiti-13523	63	8	red	red	ADJ
aiti-13523	63	9	deer	deer	NOUN
aiti-13523	63	10	algorithm	algorithm	NOUN
aiti-13523	63	11	(	(	PUNCT
aiti-13523	63	12	mrda	mrda	NOUN
aiti-13523	63	13	)	)	PUNCT
aiti-13523	63	14	extreme	extreme	ADJ
aiti-13523	63	15	learning	learning	NOUN
aiti-13523	63	16	machine	machine	NOUN
aiti-13523	63	17	sparse	sparse	ADJ
aiti-13523	63	18	autoencoder	autoencoder	NOUN
aiti-13523	63	19	(	(	PUNCT
aiti-13523	63	20	elmsae	elmsae	PROPN
aiti-13523	63	21	)	)	PUNCT
aiti-13523	63	22	model	model	NOUN
aiti-13523	63	23	for	for	ADP
aiti-13523	63	24	sentiment	sentiment	NOUN
aiti-13523	63	25	analysis	analysis	NOUN
aiti-13523	63	26	on	on	ADP
aiti-13523	63	27	a	a	DET
aiti-13523	63	28	benchmark	benchmark	NOUN
aiti-13523	63	29	dataset	dataset	NOUN
aiti-13523	63	30	including	include	VERB
aiti-13523	63	31	d	d	PROPN
aiti-13523	63	32	mobile	mobile	ADJ
aiti-13523	63	33	applications	application	NOUN
aiti-13523	63	34	for	for	ADP
aiti-13523	63	35	google	google	NOUN
aiti-13523	63	36	,	,	PUNCT
aiti-13523	63	37	their	their	PRON
aiti-13523	63	38	classification	classification	NOUN
aiti-13523	63	39	process	process	NOUN
aiti-13523	63	40	includes	include	VERB
aiti-13523	63	41	vectorization	vectorization	NOUN
aiti-13523	63	42	by	by	ADP
aiti-13523	63	43	the	the	DET
aiti-13523	63	44	tf	tf	PROPN
aiti-13523	63	45	-	-	PUNCT
aiti-13523	63	46	idf	idf	PROPN
aiti-13523	63	47	model	model	NOUN
aiti-13523	63	48	reaching	reach	VERB
aiti-13523	63	49	an	an	DET
aiti-13523	63	50	accuracy	accuracy	NOUN
aiti-13523	63	51	score	score	NOUN
aiti-13523	63	52	of	of	ADP
aiti-13523	63	53	98	98	NUM
aiti-13523	63	54	%	%	NOUN
aiti-13523	63	55	.	.	PUNCT
aiti-13523	64	1	tan	tan	INTJ
aiti-13523	64	2	et	et	PROPN
aiti-13523	64	3	al	al	PROPN
aiti-13523	64	4	.	.	PUNCT
aiti-13523	65	1	[	[	X
aiti-13523	65	2	10	10	NUM
aiti-13523	65	3	]	]	X
aiti-13523	65	4	present	present	ADJ
aiti-13523	65	5	an	an	DET
aiti-13523	65	6	approach	approach	NOUN
aiti-13523	65	7	for	for	ADP
aiti-13523	65	8	sentiment	sentiment	NOUN
aiti-13523	65	9	analysis	analysis	NOUN
aiti-13523	65	10	and	and	CCONJ
aiti-13523	65	11	sarcasm	sarcasm	NOUN
aiti-13523	65	12	detection	detection	NOUN
aiti-13523	65	13	simultaneously	simultaneously	ADV
aiti-13523	65	14	from	from	ADP
aiti-13523	65	15	online	online	ADJ
aiti-13523	65	16	textual	textual	ADJ
aiti-13523	65	17	data	datum	NOUN
aiti-13523	65	18	using	use	VERB
aiti-13523	65	19	multi	multi	ADJ
aiti-13523	65	20	-	-	NOUN
aiti-13523	65	21	task	task	ADJ
aiti-13523	65	22	learning	learning	NOUN
aiti-13523	65	23	which	which	PRON
aiti-13523	65	24	consists	consist	VERB
aiti-13523	65	25	of	of	ADP
aiti-13523	65	26	training	training	NOUN
aiti-13523	65	27	both	both	DET
aiti-13523	65	28	tasks	task	NOUN
aiti-13523	65	29	simultaneously	simultaneously	ADV
aiti-13523	65	30	with	with	ADP
aiti-13523	65	31	a	a	DET
aiti-13523	65	32	shared	share	VERB
aiti-13523	65	33	layer	layer	NOUN
aiti-13523	65	34	of	of	ADP
aiti-13523	65	35	the	the	DET
aiti-13523	65	36	bidirectional	bidirectional	ADJ
aiti-13523	65	37	long	long	ADJ
aiti-13523	65	38	short	short	ADJ
aiti-13523	65	39	-	-	PUNCT
aiti-13523	65	40	term	term	NOUN
aiti-13523	65	41	memory	memory	NOUN
aiti-13523	65	42	(	(	PUNCT
aiti-13523	65	43	bilstm	bilstm	NOUN
aiti-13523	65	44	)	)	PUNCT
aiti-13523	65	45	model	model	NOUN
aiti-13523	65	46	.	.	PUNCT
aiti-13523	66	1	the	the	DET
aiti-13523	66	2	proposed	propose	VERB
aiti-13523	66	3	framework	framework	NOUN
aiti-13523	66	4	aims	aim	VERB
aiti-13523	66	5	to	to	PART
aiti-13523	66	6	improve	improve	VERB
aiti-13523	66	7	the	the	DET
aiti-13523	66	8	performance	performance	NOUN
aiti-13523	66	9	of	of	ADP
aiti-13523	66	10	autonomous	autonomous	ADJ
aiti-13523	66	11	sentiment	sentiment	NOUN
aiti-13523	66	12	classification	classification	NOUN
aiti-13523	66	13	by	by	ADP
aiti-13523	66	14	adding	add	VERB
aiti-13523	66	15	an	an	DET
aiti-13523	66	16	auxiliary	auxiliary	ADJ
aiti-13523	66	17	task	task	NOUN
aiti-13523	66	18	which	which	PRON
aiti-13523	66	19	is	be	AUX
aiti-13523	66	20	sarcasm	sarcasm	NOUN
aiti-13523	66	21	detection	detection	NOUN
aiti-13523	66	22	and	and	CCONJ
aiti-13523	66	23	obtained	obtain	VERB
aiti-13523	66	24	an	an	DET
aiti-13523	66	25	f1	f1	NOUN
aiti-13523	66	26	-	-	PUNCT
aiti-13523	66	27	score	score	NOUN
aiti-13523	66	28	of	of	ADP
aiti-13523	66	29	94	94	NUM
aiti-13523	66	30	%	%	NOUN
aiti-13523	66	31	.	.	PUNCT
aiti-13523	67	1	meena	meena	PROPN
aiti-13523	67	2	et	et	PROPN
aiti-13523	67	3	al	al	PROPN
aiti-13523	67	4	.	.	PUNCT
aiti-13523	68	1	[	[	X
aiti-13523	68	2	11	11	NUM
aiti-13523	68	3	]	]	PUNCT
aiti-13523	68	4	proposed	propose	VERB
aiti-13523	68	5	a	a	DET
aiti-13523	68	6	hybrid	hybrid	ADJ
aiti-13523	68	7	model	model	NOUN
aiti-13523	68	8	based	base	VERB
aiti-13523	68	9	on	on	ADP
aiti-13523	68	10	deep	deep	ADJ
aiti-13523	68	11	learning	learning	NOUN
aiti-13523	68	12	to	to	PART
aiti-13523	68	13	know	know	VERB
aiti-13523	68	14	users	user	NOUN
aiti-13523	68	15	’	’	PART
aiti-13523	68	16	opinions	opinion	NOUN
aiti-13523	68	17	on	on	ADP
aiti-13523	68	18	the	the	DET
aiti-13523	68	19	monkeypox	monkeypox	NOUN
aiti-13523	68	20	infection	infection	NOUN
aiti-13523	68	21	on	on	ADP
aiti-13523	68	22	social	social	ADJ
aiti-13523	68	23	networks	network	NOUN
aiti-13523	68	24	,	,	PUNCT
aiti-13523	68	25	combining	combine	VERB
aiti-13523	68	26	convolutional	convolutional	ADJ
aiti-13523	68	27	neural	neural	ADJ
aiti-13523	68	28	networks	network	NOUN
aiti-13523	68	29	(	(	PUNCT
aiti-13523	68	30	cnn	cnn	PROPN
aiti-13523	68	31	)	)	PUNCT
aiti-13523	68	32	and	and	CCONJ
aiti-13523	68	33	lstm	lstm	PROPN
aiti-13523	68	34	,	,	PUNCT
aiti-13523	68	35	and	and	CCONJ
aiti-13523	68	36	obtained	obtain	VERB
aiti-13523	68	37	an	an	DET
aiti-13523	68	38	f1	f1	NOUN
aiti-13523	68	39	-	-	PUNCT
aiti-13523	68	40	score	score	NOUN
aiti-13523	68	41	of	of	ADP
aiti-13523	68	42	95	95	NUM
aiti-13523	68	43	%	%	NOUN
aiti-13523	68	44	.	.	PUNCT
aiti-13523	69	1	das	das	PROPN
aiti-13523	69	2	et	et	PROPN
aiti-13523	69	3	al	al	PROPN
aiti-13523	69	4	.	.	PUNCT
aiti-13523	70	1	[	[	X
aiti-13523	70	2	12	12	NUM
aiti-13523	70	3	]	]	PUNCT
aiti-13523	70	4	compared	compare	VERB
aiti-13523	70	5	different	different	ADJ
aiti-13523	70	6	deep	deep	ADJ
aiti-13523	70	7	learning	learning	NOUN
aiti-13523	70	8	and	and	CCONJ
aiti-13523	70	9	hybrid	hybrid	NOUN
aiti-13523	70	10	models	model	NOUN
aiti-13523	70	11	for	for	ADP
aiti-13523	70	12	the	the	DET
aiti-13523	70	13	sentiment	sentiment	NOUN
aiti-13523	70	14	analysis	analysis	NOUN
aiti-13523	70	15	of	of	ADP
aiti-13523	70	16	comments	comment	NOUN
aiti-13523	70	17	on	on	ADP
aiti-13523	70	18	an	an	DET
aiti-13523	70	19	e	e	NOUN
aiti-13523	70	20	-	-	NOUN
aiti-13523	70	21	commerce	commerce	NOUN
aiti-13523	70	22	site	site	NOUN
aiti-13523	70	23	,	,	PUNCT
aiti-13523	70	24	for	for	ADP
aiti-13523	70	25	the	the	DET
aiti-13523	70	26	classification	classification	NOUN
aiti-13523	70	27	of	of	ADP
aiti-13523	70	28	texts	text	NOUN
aiti-13523	70	29	in	in	ADP
aiti-13523	70	30	english	english	PROPN
aiti-13523	70	31	and	and	CCONJ
aiti-13523	70	32	bengal	bengal	ADJ
aiti-13523	70	33	,	,	PUNCT
aiti-13523	70	34	and	and	CCONJ
aiti-13523	70	35	demonstrated	demonstrate	VERB
aiti-13523	70	36	that	that	SCONJ
aiti-13523	70	37	the	the	DET
aiti-13523	70	38	model	model	NOUN
aiti-13523	70	39	support	support	NOUN
aiti-13523	70	40	vector	vector	NOUN
aiti-13523	70	41	machine	machine	NOUN
aiti-13523	70	42	(	(	PUNCT
aiti-13523	70	43	svm	svm	PROPN
aiti-13523	70	44	)	)	PUNCT
aiti-13523	70	45	outperformed	outperform	VERB
aiti-13523	70	46	other	other	ADJ
aiti-13523	70	47	models	model	NOUN
aiti-13523	70	48	,	,	PUNCT
aiti-13523	70	49	achieving	achieve	VERB
aiti-13523	70	50	an	an	DET
aiti-13523	70	51	accuracy	accuracy	NOUN
aiti-13523	70	52	of	of	ADP
aiti-13523	70	53	82.56	82.56	NUM
aiti-13523	70	54	%	%	NOUN
aiti-13523	70	55	for	for	ADP
aiti-13523	70	56	sentiment	sentiment	NOUN
aiti-13523	70	57	analysis	analysis	NOUN
aiti-13523	70	58	of	of	ADP
aiti-13523	70	59	english	english	ADJ
aiti-13523	70	60	texts	text	NOUN
aiti-13523	70	61	and	and	CCONJ
aiti-13523	70	62	86.43	86.43	NUM
aiti-13523	70	63	%	%	NOUN
aiti-13523	70	64	for	for	ADP
aiti-13523	70	65	sentiment	sentiment	NOUN
aiti-13523	70	66	analysis	analysis	NOUN
aiti-13523	70	67	of	of	ADP
aiti-13523	70	68	bengali	bengali	NOUN
aiti-13523	70	69	texts	text	NOUN
aiti-13523	70	70	.	.	PUNCT
aiti-13523	71	1	umair	umair	NOUN
aiti-13523	71	2	et	et	PROPN
aiti-13523	71	3	al	al	PROPN
aiti-13523	71	4	.	.	PUNCT
aiti-13523	72	1	[	[	X
aiti-13523	72	2	13	13	NUM
aiti-13523	72	3	]	]	PUNCT
aiti-13523	72	4	proposed	propose	VERB
aiti-13523	72	5	an	an	DET
aiti-13523	72	6	approach	approach	NOUN
aiti-13523	72	7	to	to	PART
aiti-13523	72	8	analyze	analyze	VERB
aiti-13523	72	9	tweets	tweet	NOUN
aiti-13523	72	10	related	relate	VERB
aiti-13523	72	11	to	to	ADP
aiti-13523	72	12	covid-19	covid-19	PROPN
aiti-13523	72	13	vaccines	vaccine	NOUN
aiti-13523	72	14	and	and	CCONJ
aiti-13523	72	15	combined	combine	VERB
aiti-13523	72	16	the	the	DET
aiti-13523	72	17	bert	bert	PROPN
aiti-13523	72	18	+	+	PROPN
aiti-13523	72	19	nbsvm	nbsvm	PROPN
aiti-13523	72	20	model	model	NOUN
aiti-13523	72	21	to	to	PART
aiti-13523	72	22	classify	classify	VERB
aiti-13523	72	23	people	people	NOUN
aiti-13523	72	24	’s	’s	PART
aiti-13523	72	25	sentiments	sentiment	NOUN
aiti-13523	72	26	towards	towards	ADP
aiti-13523	72	27	vaccines	vaccine	NOUN
aiti-13523	72	28	.	.	PUNCT
aiti-13523	73	1	this	this	DET
aiti-13523	73	2	choice	choice	NOUN
aiti-13523	73	3	is	be	AUX
aiti-13523	73	4	motivated	motivate	VERB
aiti-13523	73	5	by	by	ADP
aiti-13523	73	6	taking	take	VERB
aiti-13523	73	7	advantage	advantage	NOUN
aiti-13523	73	8	of	of	ADP
aiti-13523	73	9	both	both	CCONJ
aiti-13523	73	10	bidirectional	bidirectional	ADJ
aiti-13523	73	11	bert	bert	PROPN
aiti-13523	73	12	and	and	CCONJ
aiti-13523	73	13	nbsvm	nbsvm	PROPN
aiti-13523	73	14	functionalities	functionality	NOUN
aiti-13523	73	15	from	from	ADP
aiti-13523	73	16	transformers	transformer	NOUN
aiti-13523	73	17	and	and	CCONJ
aiti-13523	73	18	circumventing	circumvent	VERB
aiti-13523	73	19	the	the	DET
aiti-13523	73	20	limitations	limitation	NOUN
aiti-13523	73	21	of	of	ADP
aiti-13523	73	22	bert	bert	NOUN
aiti-13523	73	23	-	-	PUNCT
aiti-13523	73	24	based	base	VERB
aiti-13523	73	25	approaches	approach	NOUN
aiti-13523	73	26	,	,	PUNCT
aiti-13523	73	27	which	which	PRON
aiti-13523	73	28	only	only	ADV
aiti-13523	73	29	leverage	leverage	NOUN
aiti-13523	73	30	encoder	encoder	NOUN
aiti-13523	73	31	layers	layer	NOUN
aiti-13523	73	32	,	,	PUNCT
aiti-13523	73	33	resulting	result	VERB
aiti-13523	73	34	in	in	ADP
aiti-13523	73	35	lower	low	ADJ
aiti-13523	73	36	performance	performance	NOUN
aiti-13523	73	37	on	on	ADP
aiti-13523	73	38	short	short	ADJ
aiti-13523	73	39	texts	text	NOUN
aiti-13523	73	40	.	.	PUNCT
aiti-13523	74	1	the	the	DET
aiti-13523	74	2	model	model	NOUN
aiti-13523	74	3	achieved	achieve	VERB
aiti-13523	74	4	a	a	DET
aiti-13523	74	5	performance	performance	NOUN
aiti-13523	74	6	of	of	ADP
aiti-13523	74	7	73	73	NUM
aiti-13523	74	8	%	%	NOUN
aiti-13523	74	9	accuracy	accuracy	NOUN
aiti-13523	74	10	,	,	PUNCT
aiti-13523	74	11	71	71	NUM
aiti-13523	74	12	%	%	NOUN
aiti-13523	74	13	precision	precision	NOUN
aiti-13523	74	14	,	,	PUNCT
aiti-13523	74	15	88	88	NUM
aiti-13523	74	16	%	%	NOUN
aiti-13523	74	17	recall	recall	NOUN
aiti-13523	74	18	,	,	PUNCT
aiti-13523	74	19	and	and	CCONJ
aiti-13523	74	20	73	73	NUM
aiti-13523	74	21	%	%	NOUN
aiti-13523	74	22	fmeasure	fmeasure	NOUN
aiti-13523	74	23	for	for	ADP
aiti-13523	74	24	positive	positive	ADJ
aiti-13523	74	25	sentiment	sentiment	NOUN
aiti-13523	74	26	classification	classification	NOUN
aiti-13523	74	27	,	,	PUNCT
aiti-13523	74	28	while	while	SCONJ
aiti-13523	74	29	73	73	NUM
aiti-13523	74	30	%	%	NOUN
aiti-13523	74	31	accuracy	accuracy	NOUN
aiti-13523	74	32	,	,	PUNCT
aiti-13523	74	33	71	71	NUM
aiti-13523	74	34	%	%	NOUN
aiti-13523	74	35	precision	precision	NOUN
aiti-13523	74	36	,	,	PUNCT
aiti-13523	74	37	74	74	NUM
aiti-13523	74	38	%	%	NOUN
aiti-13523	74	39	recall	recall	NOUN
aiti-13523	74	40	,	,	PUNCT
aiti-13523	74	41	and	and	CCONJ
aiti-13523	74	42	73	73	NUM
aiti-13523	74	43	%	%	NOUN
aiti-13523	74	44	f	f	NOUN
aiti-13523	74	45	-	-	PUNCT
aiti-13523	74	46	measure	measure	NOUN
aiti-13523	74	47	for	for	ADP
aiti-13523	74	48	classification	classification	NOUN
aiti-13523	74	49	of	of	ADP
aiti-13523	74	50	negative	negative	ADJ
aiti-13523	74	51	feelings	feeling	NOUN
aiti-13523	74	52	respectively	respectively	ADV
aiti-13523	74	53	.	.	PUNCT
aiti-13523	75	1	after	after	ADP
aiti-13523	75	2	comparison	comparison	NOUN
aiti-13523	75	3	with	with	ADP
aiti-13523	75	4	this	this	DET
aiti-13523	75	5	state	state	NOUN
aiti-13523	75	6	of	of	ADP
aiti-13523	75	7	the	the	DET
aiti-13523	75	8	art	art	NOUN
aiti-13523	75	9	,	,	PUNCT
aiti-13523	75	10	some	some	DET
aiti-13523	75	11	points	point	NOUN
aiti-13523	75	12	can	can	AUX
aiti-13523	75	13	be	be	AUX
aiti-13523	75	14	got	get	VERB
aiti-13523	75	15	:	:	PUNCT
aiti-13523	75	16	(	(	PUNCT
aiti-13523	75	17	1	1	X
aiti-13523	75	18	)	)	PUNCT
aiti-13523	75	19	although	although	SCONJ
aiti-13523	75	20	lexicon	lexicon	NOUN
aiti-13523	75	21	-	-	PUNCT
aiti-13523	75	22	based	base	VERB
aiti-13523	75	23	and	and	CCONJ
aiti-13523	75	24	machine	machine	NOUN
aiti-13523	75	25	-	-	PUNCT
aiti-13523	75	26	learning	learn	VERB
aiti-13523	75	27	approaches	approach	NOUN
aiti-13523	75	28	offer	offer	VERB
aiti-13523	75	29	valuable	valuable	ADJ
aiti-13523	75	30	insights	insight	NOUN
aiti-13523	75	31	into	into	ADP
aiti-13523	75	32	sentiment	sentiment	NOUN
aiti-13523	75	33	analysis	analysis	NOUN
aiti-13523	75	34	,	,	PUNCT
aiti-13523	75	35	this	this	DET
aiti-13523	75	36	study	study	NOUN
aiti-13523	75	37	does	do	AUX
aiti-13523	75	38	not	not	PART
aiti-13523	75	39	aim	aim	VERB
aiti-13523	75	40	at	at	ADP
aiti-13523	75	41	sentiment	sentiment	NOUN
aiti-13523	75	42	extrapolation	extrapolation	NOUN
aiti-13523	75	43	using	use	VERB
aiti-13523	75	44	lexicon	lexicon	NOUN
aiti-13523	75	45	as	as	SCONJ
aiti-13523	75	46	seen	see	VERB
aiti-13523	75	47	in	in	ADP
aiti-13523	75	48	previous	previous	ADJ
aiti-13523	75	49	works	work	NOUN
aiti-13523	75	50	[	[	PUNCT
aiti-13523	75	51	5	5	NUM
aiti-13523	75	52	-	-	SYM
aiti-13523	75	53	7	7	NUM
aiti-13523	75	54	]	]	PUNCT
aiti-13523	75	55	.	.	PUNCT
aiti-13523	76	1	instead	instead	ADV
aiti-13523	76	2	,	,	PUNCT
aiti-13523	76	3	it	it	PRON
aiti-13523	76	4	introduces	introduce	VERB
aiti-13523	76	5	a	a	DET
aiti-13523	76	6	unique	unique	ADJ
aiti-13523	76	7	perspective	perspective	NOUN
aiti-13523	76	8	by	by	ADP
aiti-13523	76	9	applying	apply	VERB
aiti-13523	76	10	machine	machine	NOUN
aiti-13523	76	11	learning	learning	NOUN
aiti-13523	76	12	methods	method	NOUN
aiti-13523	76	13	to	to	ADP
aiti-13523	76	14	health	health	NOUN
aiti-13523	76	15	-	-	PUNCT
aiti-13523	76	16	related	relate	VERB
aiti-13523	76	17	text	text	NOUN
aiti-13523	76	18	data	datum	NOUN
aiti-13523	76	19	.	.	PUNCT
aiti-13523	77	1	(	(	PUNCT
aiti-13523	77	2	2	2	X
aiti-13523	77	3	)	)	PUNCT
aiti-13523	77	4	furthermore	furthermore	ADV
aiti-13523	77	5	,	,	PUNCT
aiti-13523	77	6	compared	compare	VERB
aiti-13523	77	7	to	to	ADP
aiti-13523	77	8	works	work	NOUN
aiti-13523	77	9	based	base	VERB
aiti-13523	77	10	on	on	ADP
aiti-13523	77	11	artificial	artificial	ADJ
aiti-13523	77	12	learning	learning	NOUN
aiti-13523	77	13	[	[	X
aiti-13523	77	14	8	8	NUM
aiti-13523	77	15	-	-	SYM
aiti-13523	77	16	13	13	NUM
aiti-13523	77	17	]	]	PUNCT
aiti-13523	77	18	,	,	PUNCT
aiti-13523	77	19	this	this	DET
aiti-13523	77	20	study	study	NOUN
aiti-13523	77	21	not	not	PART
aiti-13523	77	22	only	only	ADV
aiti-13523	77	23	improves	improve	VERB
aiti-13523	77	24	the	the	DET
aiti-13523	77	25	transparency	transparency	NOUN
aiti-13523	77	26	of	of	ADP
aiti-13523	77	27	results	result	NOUN
aiti-13523	77	28	by	by	ADP
aiti-13523	77	29	integrating	integrate	VERB
aiti-13523	77	30	explainability	explainability	NOUN
aiti-13523	77	31	into	into	ADP
aiti-13523	77	32	analysis	analysis	NOUN
aiti-13523	77	33	but	but	CCONJ
aiti-13523	77	34	also	also	ADV
aiti-13523	77	35	contributes	contribute	VERB
aiti-13523	77	36	to	to	ADP
aiti-13523	77	37	the	the	DET
aiti-13523	77	38	growing	grow	VERB
aiti-13523	77	39	field	field	NOUN
aiti-13523	77	40	of	of	ADP
aiti-13523	77	41	explainable	explainable	ADJ
aiti-13523	77	42	ai	ai	NOUN
aiti-13523	77	43	in	in	ADP
aiti-13523	77	44	sentiment	sentiment	NOUN
aiti-13523	77	45	analysis	analysis	NOUN
aiti-13523	77	46	.	.	PUNCT
aiti-13523	78	1	this	this	DET
aiti-13523	78	2	approach	approach	NOUN
aiti-13523	78	3	not	not	PART
aiti-13523	78	4	only	only	ADV
aiti-13523	78	5	advances	advance	VERB
aiti-13523	78	6	this	this	DET
aiti-13523	78	7	understanding	understanding	NOUN
aiti-13523	78	8	of	of	ADP
aiti-13523	78	9	sentiment	sentiment	NOUN
aiti-13523	78	10	classification	classification	NOUN
aiti-13523	78	11	in	in	ADP
aiti-13523	78	12	a	a	DET
aiti-13523	78	13	critical	critical	ADJ
aiti-13523	78	14	area	area	NOUN
aiti-13523	78	15	but	but	CCONJ
aiti-13523	78	16	also	also	ADV
aiti-13523	78	17	sets	set	VERB
aiti-13523	78	18	a	a	DET
aiti-13523	78	19	precedent	precedent	NOUN
aiti-13523	78	20	for	for	ADP
aiti-13523	78	21	future	future	ADJ
aiti-13523	78	22	research	research	NOUN
aiti-13523	78	23	in	in	ADP
aiti-13523	78	24	applying	apply	VERB
aiti-13523	78	25	explainability	explainability	NOUN
aiti-13523	78	26	to	to	PART
aiti-13523	78	27	deeply	deeply	ADV
aiti-13523	78	28	understand	understand	VERB
aiti-13523	78	29	model	model	NOUN
aiti-13523	78	30	decisions	decision	NOUN
aiti-13523	78	31	.	.	PUNCT
aiti-13523	79	1	132	132	NUM
aiti-13523	79	2	advances	advance	NOUN
aiti-13523	79	3	in	in	ADP
aiti-13523	79	4	technology	technology	NOUN
aiti-13523	79	5	innovation	innovation	NOUN
aiti-13523	79	6	,	,	PUNCT
aiti-13523	79	7	vol	vol	NOUN
aiti-13523	79	8	.	.	PROPN
aiti-13523	79	9	9	9	NUM
aiti-13523	79	10	,	,	PUNCT
aiti-13523	79	11	no	no	INTJ
aiti-13523	79	12	.	.	NOUN
aiti-13523	79	13	2	2	NUM
aiti-13523	79	14	,	,	PUNCT
aiti-13523	79	15	2024	2024	NUM
aiti-13523	79	16	,	,	PUNCT
aiti-13523	79	17	pp	pp	ADJ
aiti-13523	79	18	.	.	PUNCT
aiti-13523	80	1	129	129	NUM
aiti-13523	80	2	-	-	SYM
aiti-13523	80	3	142	142	NUM
aiti-13523	80	4	based	base	VERB
aiti-13523	80	5	on	on	ADP
aiti-13523	80	6	these	these	DET
aiti-13523	80	7	expertise	expertise	NOUN
aiti-13523	80	8	,	,	PUNCT
aiti-13523	80	9	this	this	DET
aiti-13523	80	10	study	study	NOUN
aiti-13523	80	11	focuses	focus	VERB
aiti-13523	80	12	on	on	ADP
aiti-13523	80	13	the	the	DET
aiti-13523	80	14	emohd	emohd	NOUN
aiti-13523	80	15	dataset	dataset	VERB
aiti-13523	80	16	to	to	PART
aiti-13523	80	17	demonstrate	demonstrate	VERB
aiti-13523	80	18	the	the	DET
aiti-13523	80	19	practical	practical	ADJ
aiti-13523	80	20	application	application	NOUN
aiti-13523	80	21	of	of	ADP
aiti-13523	80	22	sentiment	sentiment	NOUN
aiti-13523	80	23	analysis	analysis	NOUN
aiti-13523	80	24	techniques	technique	NOUN
aiti-13523	80	25	in	in	ADP
aiti-13523	80	26	a	a	DET
aiti-13523	80	27	healthcare	healthcare	NOUN
aiti-13523	80	28	context	context	NOUN
aiti-13523	80	29	.	.	PUNCT
aiti-13523	81	1	this	this	DET
aiti-13523	81	2	study	study	NOUN
aiti-13523	81	3	framework	framework	NOUN
aiti-13523	81	4	therefore	therefore	ADV
aiti-13523	81	5	differs	differ	VERB
aiti-13523	81	6	from	from	ADP
aiti-13523	81	7	the	the	DET
aiti-13523	81	8	works	work	NOUN
aiti-13523	81	9	cited	cite	VERB
aiti-13523	81	10	[	[	PUNCT
aiti-13523	81	11	8	8	NUM
aiti-13523	81	12	-	-	SYM
aiti-13523	81	13	13	13	NUM
aiti-13523	81	14	]	]	PUNCT
aiti-13523	81	15	,	,	PUNCT
aiti-13523	81	16	as	as	SCONJ
aiti-13523	81	17	its	its	PRON
aiti-13523	81	18	focus	focus	NOUN
aiti-13523	81	19	is	be	AUX
aiti-13523	81	20	on	on	ADP
aiti-13523	81	21	applying	apply	VERB
aiti-13523	81	22	various	various	ADJ
aiti-13523	81	23	sentiment	sentiment	NOUN
aiti-13523	81	24	analysis	analysis	NOUN
aiti-13523	81	25	methodologies	methodology	NOUN
aiti-13523	81	26	to	to	ADP
aiti-13523	81	27	the	the	DET
aiti-13523	81	28	emohd	emohd	PROPN
aiti-13523	81	29	dataset	dataset	NOUN
aiti-13523	81	30	,	,	PUNCT
aiti-13523	81	31	which	which	PRON
aiti-13523	81	32	contains	contain	VERB
aiti-13523	81	33	a	a	DET
aiti-13523	81	34	unique	unique	ADJ
aiti-13523	81	35	compilation	compilation	NOUN
aiti-13523	81	36	of	of	ADP
aiti-13523	81	37	textual	textual	ADJ
aiti-13523	81	38	data	datum	NOUN
aiti-13523	81	39	.	.	PUNCT
aiti-13523	82	1	derived	derive	VERB
aiti-13523	82	2	from	from	ADP
aiti-13523	82	3	patient	patient	ADJ
aiti-13523	82	4	feedback	feedback	NOUN
aiti-13523	82	5	on	on	ADP
aiti-13523	82	6	serious	serious	ADJ
aiti-13523	82	7	illnesses	illness	NOUN
aiti-13523	82	8	.	.	PUNCT
aiti-13523	83	1	this	this	DET
aiti-13523	83	2	dataset	dataset	NOUN
aiti-13523	83	3	,	,	PUNCT
aiti-13523	83	4	originally	originally	ADV
aiti-13523	83	5	introduced	introduce	VERB
aiti-13523	83	6	by	by	ADP
aiti-13523	83	7	azam	azam	PROPN
aiti-13523	83	8	et	et	PROPN
aiti-13523	83	9	al	al	PROPN
aiti-13523	83	10	.	.	PUNCT
aiti-13523	84	1	[	[	X
aiti-13523	84	2	4	4	NUM
aiti-13523	84	3	]	]	PUNCT
aiti-13523	84	4	,	,	PUNCT
aiti-13523	84	5	encompasses	encompass	VERB
aiti-13523	84	6	feedback	feedback	NOUN
aiti-13523	84	7	from	from	ADP
aiti-13523	84	8	individuals	individual	NOUN
aiti-13523	84	9	diagnosed	diagnose	VERB
aiti-13523	84	10	with	with	ADP
aiti-13523	84	11	a	a	DET
aiti-13523	84	12	range	range	NOUN
aiti-13523	84	13	of	of	ADP
aiti-13523	84	14	diseases	disease	NOUN
aiti-13523	84	15	,	,	PUNCT
aiti-13523	84	16	including	include	VERB
aiti-13523	84	17	measles	measle	NOUN
aiti-13523	84	18	,	,	PUNCT
aiti-13523	84	19	dengue	dengue	NOUN
aiti-13523	84	20	,	,	PUNCT
aiti-13523	84	21	typhoid	typhoid	NOUN
aiti-13523	84	22	,	,	PUNCT
aiti-13523	84	23	malaria	malaria	NOUN
aiti-13523	84	24	,	,	PUNCT
aiti-13523	84	25	acute	acute	ADJ
aiti-13523	84	26	hepatitis	hepatitis	NOUN
aiti-13523	84	27	,	,	PUNCT
aiti-13523	84	28	hiv	hiv	PROPN
aiti-13523	84	29	,	,	PUNCT
aiti-13523	84	30	ebola	ebola	PROPN
aiti-13523	84	31	,	,	PUNCT
aiti-13523	84	32	and	and	CCONJ
aiti-13523	84	33	cancer	cancer	NOUN
aiti-13523	84	34	.	.	PUNCT
aiti-13523	85	1	the	the	DET
aiti-13523	85	2	pioneering	pioneer	VERB
aiti-13523	85	3	study	study	NOUN
aiti-13523	85	4	on	on	ADP
aiti-13523	85	5	emohd	emohd	PROPN
aiti-13523	85	6	achieved	achieve	VERB
aiti-13523	85	7	an	an	DET
aiti-13523	85	8	impressive	impressive	ADJ
aiti-13523	85	9	accuracy	accuracy	NOUN
aiti-13523	85	10	of	of	ADP
aiti-13523	85	11	87	87	NUM
aiti-13523	85	12	%	%	NOUN
aiti-13523	85	13	using	use	VERB
aiti-13523	85	14	the	the	DET
aiti-13523	85	15	multi	multi	ADJ
aiti-13523	85	16	-	-	ADJ
aiti-13523	85	17	layered	layered	ADJ
aiti-13523	85	18	perceptron	perceptron	NOUN
aiti-13523	85	19	algorithm	algorithm	NOUN
aiti-13523	85	20	,	,	PUNCT
aiti-13523	85	21	setting	set	VERB
aiti-13523	85	22	a	a	DET
aiti-13523	85	23	benchmark	benchmark	NOUN
aiti-13523	85	24	for	for	ADP
aiti-13523	85	25	further	further	ADJ
aiti-13523	85	26	research	research	NOUN
aiti-13523	85	27	.	.	PUNCT
aiti-13523	86	1	encouraged	encourage	VERB
aiti-13523	86	2	by	by	ADP
aiti-13523	86	3	these	these	DET
aiti-13523	86	4	early	early	ADJ
aiti-13523	86	5	successes	success	NOUN
aiti-13523	86	6	,	,	PUNCT
aiti-13523	86	7	subsequent	subsequent	ADJ
aiti-13523	86	8	research	research	NOUN
aiti-13523	86	9	has	have	AUX
aiti-13523	86	10	sought	seek	VERB
aiti-13523	86	11	to	to	PART
aiti-13523	86	12	push	push	VERB
aiti-13523	86	13	the	the	DET
aiti-13523	86	14	boundaries	boundary	NOUN
aiti-13523	86	15	of	of	ADP
aiti-13523	86	16	sentiment	sentiment	NOUN
aiti-13523	86	17	analysis	analysis	NOUN
aiti-13523	86	18	in	in	ADP
aiti-13523	86	19	healthcare	healthcare	NOUN
aiti-13523	86	20	even	even	ADV
aiti-13523	86	21	further	far	ADV
aiti-13523	86	22	.	.	PUNCT
aiti-13523	87	1	in	in	ADP
aiti-13523	87	2	mohammad	mohammad	PROPN
aiti-13523	87	3	et	et	PROPN
aiti-13523	87	4	al	al	PROPN
aiti-13523	87	5	.	.	PUNCT
aiti-13523	88	1	[	[	X
aiti-13523	88	2	14	14	NUM
aiti-13523	88	3	]	]	PUNCT
aiti-13523	88	4	,	,	PUNCT
aiti-13523	88	5	for	for	ADP
aiti-13523	88	6	example	example	NOUN
aiti-13523	88	7	,	,	PUNCT
aiti-13523	88	8	the	the	DET
aiti-13523	88	9	intelligent	intelligent	ADJ
aiti-13523	88	10	water	water	NOUN
aiti-13523	88	11	drop	drop	NOUN
aiti-13523	88	12	algorithm	algorithm	NOUN
aiti-13523	88	13	was	be	AUX
aiti-13523	88	14	used	use	VERB
aiti-13523	88	15	to	to	PART
aiti-13523	88	16	select	select	VERB
aiti-13523	88	17	informative	informative	ADJ
aiti-13523	88	18	features	feature	NOUN
aiti-13523	88	19	from	from	ADP
aiti-13523	88	20	emohd	emohd	NOUN
aiti-13523	88	21	,	,	PUNCT
aiti-13523	88	22	demonstrating	demonstrate	VERB
aiti-13523	88	23	the	the	DET
aiti-13523	88	24	potential	potential	NOUN
aiti-13523	88	25	of	of	ADP
aiti-13523	88	26	innovative	innovative	ADJ
aiti-13523	88	27	algorithms	algorithm	NOUN
aiti-13523	88	28	to	to	PART
aiti-13523	88	29	improve	improve	VERB
aiti-13523	88	30	feature	feature	NOUN
aiti-13523	88	31	selection	selection	NOUN
aiti-13523	88	32	and	and	CCONJ
aiti-13523	88	33	,	,	PUNCT
aiti-13523	88	34	therefore	therefore	ADV
aiti-13523	88	35	,	,	PUNCT
aiti-13523	88	36	feelings	feeling	NOUN
aiti-13523	88	37	of	of	ADP
aiti-13523	88	38	classification	classification	NOUN
aiti-13523	88	39	accuracy	accuracy	NOUN
aiti-13523	88	40	in	in	ADP
aiti-13523	88	41	health	health	NOUN
aiti-13523	88	42	-	-	PUNCT
aiti-13523	88	43	related	relate	VERB
aiti-13523	88	44	texts	text	NOUN
aiti-13523	88	45	.	.	PUNCT
aiti-13523	89	1	this	this	DET
aiti-13523	89	2	exploration	exploration	NOUN
aiti-13523	89	3	of	of	ADP
aiti-13523	89	4	the	the	DET
aiti-13523	89	5	emohd	emohd	NOUN
aiti-13523	89	6	dataset	dataset	NOUN
aiti-13523	89	7	is	be	AUX
aiti-13523	89	8	part	part	NOUN
aiti-13523	89	9	of	of	ADP
aiti-13523	89	10	a	a	DET
aiti-13523	89	11	broader	broad	ADJ
aiti-13523	89	12	scientific	scientific	ADJ
aiti-13523	89	13	interest	interest	NOUN
aiti-13523	89	14	,	,	PUNCT
aiti-13523	89	15	as	as	SCONJ
aiti-13523	89	16	evidenced	evidence	VERB
aiti-13523	89	17	by	by	ADP
aiti-13523	89	18	numerous	numerous	ADJ
aiti-13523	89	19	studies	study	NOUN
aiti-13523	89	20	aimed	aim	VERB
aiti-13523	89	21	at	at	ADP
aiti-13523	89	22	leveraging	leverage	VERB
aiti-13523	89	23	nlp	nlp	NOUN
aiti-13523	89	24	and	and	CCONJ
aiti-13523	89	25	machine	machine	NOUN
aiti-13523	89	26	learning	learn	VERB
aiti-13523	89	27	to	to	PART
aiti-13523	89	28	deepen	deepen	VERB
aiti-13523	89	29	this	this	DET
aiti-13523	89	30	understanding	understanding	NOUN
aiti-13523	89	31	of	of	ADP
aiti-13523	89	32	patient	patient	ADJ
aiti-13523	89	33	experiences	experience	NOUN
aiti-13523	89	34	in	in	ADP
aiti-13523	89	35	various	various	ADJ
aiti-13523	89	36	healthcare	healthcare	NOUN
aiti-13523	89	37	settings	setting	NOUN
aiti-13523	89	38	,	,	PUNCT
aiti-13523	89	39	including	include	VERB
aiti-13523	89	40	health	health	NOUN
aiti-13523	89	41	care	care	NOUN
aiti-13523	89	42	.	.	PUNCT
aiti-13523	90	1	several	several	ADJ
aiti-13523	90	2	studies	study	NOUN
aiti-13523	90	3	have	have	AUX
aiti-13523	90	4	addressed	address	VERB
aiti-13523	90	5	emotional	emotional	ADJ
aiti-13523	90	6	recognition	recognition	NOUN
aiti-13523	91	1	[	[	X
aiti-13523	91	2	15	15	NUM
aiti-13523	91	3	-	-	SYM
aiti-13523	91	4	17	17	NUM
aiti-13523	91	5	]	]	PUNCT
aiti-13523	91	6	and	and	CCONJ
aiti-13523	91	7	its	its	PRON
aiti-13523	91	8	applications	application	NOUN
aiti-13523	91	9	in	in	ADP
aiti-13523	91	10	healthcare	healthcare	NOUN
aiti-13523	91	11	[	[	X
aiti-13523	91	12	18	18	NUM
aiti-13523	91	13	]	]	PUNCT
aiti-13523	91	14	.	.	PUNCT
aiti-13523	92	1	this	this	DET
aiti-13523	92	2	work	work	NOUN
aiti-13523	92	3	highlights	highlight	VERB
aiti-13523	92	4	the	the	DET
aiti-13523	92	5	broad	broad	ADJ
aiti-13523	92	6	interest	interest	NOUN
aiti-13523	92	7	in	in	ADP
aiti-13523	92	8	leveraging	leverage	VERB
aiti-13523	92	9	nlp	nlp	NOUN
aiti-13523	92	10	and	and	CCONJ
aiti-13523	92	11	machine	machine	NOUN
aiti-13523	92	12	learning	learn	VERB
aiti-13523	92	13	techniques	technique	NOUN
aiti-13523	92	14	to	to	PART
aiti-13523	92	15	understand	understand	VERB
aiti-13523	92	16	patients	patient	NOUN
aiti-13523	92	17	’	'	PUNCT
aiti-13523	92	18	experiences	experience	NOUN
aiti-13523	92	19	,	,	PUNCT
aiti-13523	92	20	emotions	emotion	NOUN
aiti-13523	92	21	,	,	PUNCT
aiti-13523	92	22	and	and	CCONJ
aiti-13523	92	23	feelings	feeling	NOUN
aiti-13523	92	24	,	,	PUNCT
aiti-13523	92	25	which	which	PRON
aiti-13523	92	26	is	be	AUX
aiti-13523	92	27	crucial	crucial	ADJ
aiti-13523	92	28	to	to	ADP
aiti-13523	92	29	improving	improve	VERB
aiti-13523	92	30	outcomes	outcome	NOUN
aiti-13523	92	31	for	for	ADP
aiti-13523	92	32	the	the	DET
aiti-13523	92	33	patients	patient	NOUN
aiti-13523	92	34	.	.	PUNCT
aiti-13523	93	1	healthcare	healthcare	NOUN
aiti-13523	93	2	and	and	CCONJ
aiti-13523	93	3	patient	patient	ADJ
aiti-13523	93	4	support	support	NOUN
aiti-13523	93	5	.	.	PUNCT
aiti-13523	94	1	by	by	ADP
aiti-13523	94	2	leveraging	leverage	VERB
aiti-13523	94	3	insights	insight	NOUN
aiti-13523	94	4	from	from	ADP
aiti-13523	94	5	the	the	DET
aiti-13523	94	6	emohd	emohd	PROPN
aiti-13523	94	7	dataset	dataset	NOUN
aiti-13523	94	8	,	,	PUNCT
aiti-13523	94	9	this	this	DET
aiti-13523	94	10	study	study	NOUN
aiti-13523	94	11	(	(	PUNCT
aiti-13523	94	12	in	in	ADP
aiti-13523	94	13	comparison	comparison	NOUN
aiti-13523	94	14	with	with	ADP
aiti-13523	94	15	[	[	X
aiti-13523	94	16	4	4	NUM
aiti-13523	94	17	,	,	PUNCT
aiti-13523	94	18	14	14	NUM
aiti-13523	94	19	]	]	PUNCT
aiti-13523	94	20	)	)	PUNCT
aiti-13523	94	21	aims	aim	VERB
aiti-13523	94	22	to	to	PART
aiti-13523	94	23	contribute	contribute	VERB
aiti-13523	94	24	further	far	ADV
aiti-13523	94	25	by	by	ADP
aiti-13523	94	26	evaluating	evaluate	VERB
aiti-13523	94	27	the	the	DET
aiti-13523	94	28	performance	performance	NOUN
aiti-13523	94	29	of	of	ADP
aiti-13523	94	30	different	different	ADJ
aiti-13523	94	31	learning	learning	NOUN
aiti-13523	94	32	algorithms	algorithm	NOUN
aiti-13523	94	33	such	such	ADJ
aiti-13523	94	34	as	as	ADP
aiti-13523	94	35	logistic	logistic	ADJ
aiti-13523	94	36	regression	regression	NOUN
aiti-13523	94	37	,	,	PUNCT
aiti-13523	94	38	bayes	bayes	PROPN
aiti-13523	94	39	naive	naive	ADJ
aiti-13523	94	40	,	,	PUNCT
aiti-13523	94	41	and	and	CCONJ
aiti-13523	94	42	lightgbm	lightgbm	ADJ
aiti-13523	94	43	.	.	PUNCT
aiti-13523	95	1	integrating	integrate	VERB
aiti-13523	95	2	a	a	DET
aiti-13523	95	3	variety	variety	NOUN
aiti-13523	95	4	of	of	ADP
aiti-13523	95	5	metrics	metric	NOUN
aiti-13523	95	6	(	(	PUNCT
aiti-13523	95	7	cbow	cbow	VERB
aiti-13523	95	8	,	,	PUNCT
aiti-13523	95	9	tf	tf	PROPN
aiti-13523	95	10	-	-	PUNCT
aiti-13523	95	11	idf	idf	PROPN
aiti-13523	95	12	,	,	PUNCT
aiti-13523	95	13	and	and	CCONJ
aiti-13523	95	14	word2vec	word2vec	X
aiti-13523	95	15	)	)	PUNCT
aiti-13523	95	16	and	and	CCONJ
aiti-13523	95	17	comparing	compare	VERB
aiti-13523	95	18	them	they	PRON
aiti-13523	95	19	to	to	PART
aiti-13523	95	20	recurrent	recurrent	VERB
aiti-13523	95	21	deep	deep	ADJ
aiti-13523	95	22	learning	learning	NOUN
aiti-13523	95	23	networks	network	NOUN
aiti-13523	95	24	,	,	PUNCT
aiti-13523	95	25	including	include	VERB
aiti-13523	95	26	lstm	lstm	NOUN
aiti-13523	95	27	and	and	CCONJ
aiti-13523	95	28	bert	bert	PROPN
aiti-13523	95	29	models	model	NOUN
aiti-13523	95	30	which	which	PRON
aiti-13523	95	31	have	have	AUX
aiti-13523	95	32	shown	show	VERB
aiti-13523	95	33	good	good	ADJ
aiti-13523	95	34	results	result	NOUN
aiti-13523	95	35	in	in	ADP
aiti-13523	95	36	sentiment	sentiment	NOUN
aiti-13523	95	37	classification	classification	NOUN
aiti-13523	95	38	[	[	X
aiti-13523	95	39	10	10	NUM
aiti-13523	95	40	-	-	SYM
aiti-13523	95	41	11	11	NUM
aiti-13523	95	42	,	,	PUNCT
aiti-13523	95	43	13	13	NUM
aiti-13523	95	44	]	]	PUNCT
aiti-13523	95	45	.	.	PUNCT
aiti-13523	96	1	given	give	VERB
aiti-13523	96	2	the	the	DET
aiti-13523	96	3	dataset	dataset	NOUN
aiti-13523	96	4	’s	’s	PART
aiti-13523	96	5	inherent	inherent	ADJ
aiti-13523	96	6	imbalance	imbalance	NOUN
aiti-13523	96	7	across	across	ADP
aiti-13523	96	8	six	six	NUM
aiti-13523	96	9	sentiment	sentiment	NOUN
aiti-13523	96	10	classes	class	NOUN
aiti-13523	96	11	(	(	PUNCT
aiti-13523	96	12	happy	happy	ADJ
aiti-13523	96	13	,	,	PUNCT
aiti-13523	96	14	sad	sad	ADJ
aiti-13523	96	15	,	,	PUNCT
aiti-13523	96	16	scared	scared	ADJ
aiti-13523	96	17	,	,	PUNCT
aiti-13523	96	18	angry	angry	ADJ
aiti-13523	96	19	,	,	PUNCT
aiti-13523	96	20	excited	excited	ADJ
aiti-13523	96	21	,	,	PUNCT
aiti-13523	96	22	bored	bored	ADJ
aiti-13523	96	23	)	)	PUNCT
aiti-13523	96	24	,	,	PUNCT
aiti-13523	96	25	this	this	DET
aiti-13523	96	26	approach	approach	NOUN
aiti-13523	96	27	includes	include	VERB
aiti-13523	96	28	exploring	explore	VERB
aiti-13523	96	29	various	various	ADJ
aiti-13523	96	30	resampling	resample	VERB
aiti-13523	96	31	methods	method	NOUN
aiti-13523	96	32	(	(	PUNCT
aiti-13523	96	33	naive	naive	ADJ
aiti-13523	96	34	subsampling	subsampling	NOUN
aiti-13523	96	35	,	,	PUNCT
aiti-13523	96	36	nearmiss	nearmiss	ADJ
aiti-13523	96	37	,	,	PUNCT
aiti-13523	96	38	smote	smote	ADJ
aiti-13523	96	39	,	,	PUNCT
aiti-13523	96	40	and	and	CCONJ
aiti-13523	96	41	adasyn	adasyn	PROPN
aiti-13523	96	42	)	)	PUNCT
aiti-13523	96	43	to	to	PART
aiti-13523	96	44	address	address	VERB
aiti-13523	96	45	associated	associated	ADJ
aiti-13523	96	46	challenges	challenge	NOUN
aiti-13523	96	47	and	and	CCONJ
aiti-13523	96	48	evaluate	evaluate	VERB
aiti-13523	96	49	their	their	PRON
aiti-13523	96	50	impact	impact	NOUN
aiti-13523	96	51	on	on	ADP
aiti-13523	96	52	sentiment	sentiment	NOUN
aiti-13523	96	53	classification	classification	NOUN
aiti-13523	96	54	results	result	NOUN
aiti-13523	96	55	.	.	PUNCT
aiti-13523	97	1	the	the	DET
aiti-13523	97	2	other	other	ADJ
aiti-13523	97	3	contribution	contribution	NOUN
aiti-13523	97	4	of	of	ADP
aiti-13523	97	5	this	this	DET
aiti-13523	97	6	approach	approach	NOUN
aiti-13523	97	7	is	be	AUX
aiti-13523	97	8	the	the	DET
aiti-13523	97	9	incorporation	incorporation	NOUN
aiti-13523	97	10	of	of	ADP
aiti-13523	97	11	explainable	explainable	ADJ
aiti-13523	97	12	artificial	artificial	ADJ
aiti-13523	97	13	intelligence	intelligence	NOUN
aiti-13523	97	14	(	(	PUNCT
aiti-13523	97	15	xai	xai	PROPN
aiti-13523	97	16	)	)	PUNCT
aiti-13523	97	17	,	,	PUNCT
aiti-13523	97	18	a	a	DET
aiti-13523	97	19	response	response	NOUN
aiti-13523	97	20	to	to	ADP
aiti-13523	97	21	the	the	DET
aiti-13523	97	22	critical	critical	ADJ
aiti-13523	97	23	need	need	NOUN
aiti-13523	97	24	for	for	ADP
aiti-13523	97	25	transparency	transparency	NOUN
aiti-13523	97	26	and	and	CCONJ
aiti-13523	97	27	understandability	understandability	NOUN
aiti-13523	97	28	in	in	ADP
aiti-13523	97	29	healthcare	healthcare	NOUN
aiti-13523	97	30	sentiment	sentiment	NOUN
aiti-13523	97	31	analysis	analysis	NOUN
aiti-13523	97	32	,	,	PUNCT
aiti-13523	97	33	particularly	particularly	ADV
aiti-13523	97	34	when	when	SCONJ
aiti-13523	97	35	navigating	navigate	VERB
aiti-13523	97	36	nuanced	nuanced	ADJ
aiti-13523	97	37	sentiments	sentiment	NOUN
aiti-13523	97	38	within	within	ADP
aiti-13523	97	39	the	the	DET
aiti-13523	97	40	emohd	emohd	NOUN
aiti-13523	97	41	dataset	dataset	NOUN
aiti-13523	97	42	.	.	PUNCT
aiti-13523	98	1	explainability	explainability	NOUN
aiti-13523	98	2	offers	offer	VERB
aiti-13523	98	3	a	a	DET
aiti-13523	98	4	certain	certain	ADJ
aiti-13523	98	5	transparency	transparency	NOUN
aiti-13523	98	6	on	on	ADP
aiti-13523	98	7	the	the	DET
aiti-13523	98	8	behavior	behavior	NOUN
aiti-13523	98	9	of	of	ADP
aiti-13523	98	10	the	the	DET
aiti-13523	98	11	classifier	classifier	NOUN
aiti-13523	98	12	and	and	CCONJ
aiti-13523	98	13	thus	thus	ADV
aiti-13523	98	14	makes	make	VERB
aiti-13523	98	15	it	it	PRON
aiti-13523	98	16	possible	possible	ADJ
aiti-13523	98	17	to	to	PART
aiti-13523	98	18	better	well	ADV
aiti-13523	98	19	explain	explain	VERB
aiti-13523	98	20	its	its	PRON
aiti-13523	98	21	decisions	decision	NOUN
aiti-13523	98	22	and	and	CCONJ
aiti-13523	98	23	shortcomings	shortcoming	NOUN
aiti-13523	98	24	in	in	ADP
aiti-13523	98	25	its	its	PRON
aiti-13523	98	26	performance	performance	NOUN
aiti-13523	98	27	.	.	PUNCT
aiti-13523	99	1	explainability	explainability	NOUN
aiti-13523	99	2	techniques	technique	NOUN
aiti-13523	99	3	can	can	AUX
aiti-13523	99	4	be	be	AUX
aiti-13523	99	5	classified	classify	VERB
aiti-13523	99	6	based	base	VERB
aiti-13523	99	7	on	on	ADP
aiti-13523	99	8	their	their	PRON
aiti-13523	99	9	conceptual	conceptual	ADJ
aiti-13523	99	10	capacity	capacity	NOUN
aiti-13523	99	11	[	[	X
aiti-13523	99	12	19	19	NUM
aiti-13523	99	13	]	]	PUNCT
aiti-13523	99	14	.	.	PUNCT
aiti-13523	100	1	in	in	ADP
aiti-13523	100	2	this	this	DET
aiti-13523	100	3	case	case	NOUN
aiti-13523	100	4	,	,	PUNCT
aiti-13523	100	5	two	two	NUM
aiti-13523	100	6	classes	class	NOUN
aiti-13523	100	7	of	of	ADP
aiti-13523	100	8	methods	method	NOUN
aiti-13523	100	9	are	be	AUX
aiti-13523	100	10	distinguished	distinguish	VERB
aiti-13523	100	11	:	:	PUNCT
aiti-13523	100	12	ante	ante	NOUN
aiti-13523	100	13	-	-	PUNCT
aiti-13523	100	14	hoc	hoc	X
aiti-13523	100	15	(	(	PUNCT
aiti-13523	100	16	intrinsic	intrinsic	ADJ
aiti-13523	100	17	)	)	PUNCT
aiti-13523	100	18	approaches	approach	NOUN
aiti-13523	100	19	that	that	PRON
aiti-13523	100	20	automatically	automatically	ADV
aiti-13523	100	21	generate	generate	VERB
aiti-13523	100	22	the	the	DET
aiti-13523	100	23	explanation	explanation	NOUN
aiti-13523	100	24	as	as	ADP
aiti-13523	100	25	part	part	NOUN
aiti-13523	100	26	of	of	ADP
aiti-13523	100	27	the	the	DET
aiti-13523	100	28	prediction	prediction	NOUN
aiti-13523	100	29	process	process	NOUN
aiti-13523	100	30	,	,	PUNCT
aiti-13523	100	31	referring	refer	VERB
aiti-13523	100	32	to	to	ADP
aiti-13523	100	33	machine	machine	NOUN
aiti-13523	100	34	learning	learning	NOUN
aiti-13523	100	35	models	model	NOUN
aiti-13523	100	36	considered	consider	VERB
aiti-13523	100	37	interpretable	interpretable	ADJ
aiti-13523	100	38	due	due	ADP
aiti-13523	100	39	to	to	ADP
aiti-13523	100	40	their	their	PRON
aiti-13523	100	41	simple	simple	ADJ
aiti-13523	100	42	structure	structure	NOUN
aiti-13523	100	43	,	,	PUNCT
aiti-13523	100	44	such	such	ADJ
aiti-13523	100	45	as	as	ADP
aiti-13523	100	46	short	short	ADJ
aiti-13523	100	47	or	or	CCONJ
aiti-13523	100	48	sparse	sparse	ADJ
aiti-13523	100	49	linear	linear	ADJ
aiti-13523	100	50	decision	decision	NOUN
aiti-13523	100	51	trees	tree	NOUN
aiti-13523	100	52	;	;	PUNCT
aiti-13523	100	53	and	and	CCONJ
aiti-13523	100	54	post	post	VERB
aiti-13523	100	55	hoc	hoc	X
aiti-13523	100	56	models	model	NOUN
aiti-13523	100	57	and	and	CCONJ
aiti-13523	100	58	approaches	approach	NOUN
aiti-13523	100	59	that	that	PRON
aiti-13523	100	60	apply	apply	VERB
aiti-13523	100	61	interpretation	interpretation	NOUN
aiti-13523	100	62	methods	method	NOUN
aiti-13523	100	63	after	after	ADP
aiti-13523	100	64	model	model	NOUN
aiti-13523	100	65	training	training	NOUN
aiti-13523	100	66	.	.	PUNCT
aiti-13523	101	1	others	other	NOUN
aiti-13523	101	2	classify	classify	VERB
aiti-13523	101	3	xai	xai	PROPN
aiti-13523	101	4	methods	method	NOUN
aiti-13523	101	5	based	base	VERB
aiti-13523	101	6	on	on	ADP
aiti-13523	101	7	their	their	PRON
aiti-13523	101	8	scope	scope	NOUN
aiti-13523	101	9	,	,	PUNCT
aiti-13523	101	10	whether	whether	SCONJ
aiti-13523	101	11	global	global	ADJ
aiti-13523	101	12	or	or	CCONJ
aiti-13523	101	13	local	local	ADJ
aiti-13523	101	14	:	:	PUNCT
aiti-13523	101	15	local	local	ADJ
aiti-13523	101	16	explanations	explanation	NOUN
aiti-13523	101	17	focus	focus	VERB
aiti-13523	101	18	on	on	ADP
aiti-13523	101	19	the	the	DET
aiti-13523	101	20	classification	classification	NOUN
aiti-13523	101	21	result	result	NOUN
aiti-13523	101	22	of	of	ADP
aiti-13523	101	23	a	a	DET
aiti-13523	101	24	given	give	VERB
aiti-13523	101	25	instance	instance	NOUN
aiti-13523	101	26	,	,	PUNCT
aiti-13523	101	27	while	while	SCONJ
aiti-13523	101	28	global	global	ADJ
aiti-13523	101	29	explanations	explanation	NOUN
aiti-13523	101	30	provide	provide	VERB
aiti-13523	101	31	an	an	DET
aiti-13523	101	32	overview	overview	NOUN
aiti-13523	101	33	of	of	ADP
aiti-13523	101	34	the	the	DET
aiti-13523	101	35	entire	entire	ADJ
aiti-13523	101	36	model	model	NOUN
aiti-13523	101	37	.	.	PUNCT
aiti-13523	102	1	through	through	ADP
aiti-13523	102	2	this	this	DET
aiti-13523	102	3	targeted	target	VERB
aiti-13523	102	4	application	application	NOUN
aiti-13523	102	5	of	of	ADP
aiti-13523	102	6	xai	xai	PROPN
aiti-13523	102	7	techniques	technique	NOUN
aiti-13523	102	8	on	on	ADP
aiti-13523	102	9	the	the	DET
aiti-13523	102	10	emohd	emohd	PROPN
aiti-13523	102	11	dataset	dataset	NOUN
aiti-13523	102	12	,	,	PUNCT
aiti-13523	102	13	the	the	DET
aiti-13523	102	14	aim	aim	NOUN
aiti-13523	102	15	is	be	AUX
aiti-13523	102	16	not	not	PART
aiti-13523	102	17	to	to	PART
aiti-13523	102	18	only	only	ADV
aiti-13523	102	19	improve	improve	VERB
aiti-13523	102	20	the	the	DET
aiti-13523	102	21	clarity	clarity	NOUN
aiti-13523	102	22	of	of	ADP
aiti-13523	102	23	model	model	NOUN
aiti-13523	102	24	decisions	decision	NOUN
aiti-13523	102	25	but	but	CCONJ
aiti-13523	102	26	also	also	ADV
aiti-13523	102	27	to	to	PART
aiti-13523	102	28	lay	lay	VERB
aiti-13523	102	29	the	the	DET
aiti-13523	102	30	foundation	foundation	NOUN
aiti-13523	102	31	for	for	ADP
aiti-13523	102	32	future	future	ADJ
aiti-13523	102	33	explorations	exploration	NOUN
aiti-13523	102	34	of	of	ADP
aiti-13523	102	35	the	the	DET
aiti-13523	102	36	complex	complex	ADJ
aiti-13523	102	37	relationship	relationship	NOUN
aiti-13523	102	38	between	between	ADP
aiti-13523	102	39	ai	ai	PROPN
aiti-13523	102	40	decisions	decision	NOUN
aiti-13523	102	41	and	and	CCONJ
aiti-13523	102	42	healthcare	healthcare	NOUN
aiti-13523	102	43	outcomes	outcome	NOUN
aiti-13523	102	44	.	.	PUNCT
aiti-13523	103	1	in	in	ADP
aiti-13523	103	2	this	this	DET
aiti-13523	103	3	study	study	NOUN
aiti-13523	103	4	,	,	PUNCT
aiti-13523	103	5	the	the	DET
aiti-13523	103	6	understanding	understanding	NOUN
aiti-13523	103	7	of	of	ADP
aiti-13523	103	8	the	the	DET
aiti-13523	103	9	local	local	ADJ
aiti-13523	103	10	scope	scope	NOUN
aiti-13523	103	11	of	of	ADP
aiti-13523	103	12	the	the	DET
aiti-13523	103	13	learning	learning	NOUN
aiti-13523	103	14	model	model	NOUN
aiti-13523	103	15	which	which	PRON
aiti-13523	103	16	gave	give	VERB
aiti-13523	103	17	us	we	PRON
aiti-13523	103	18	the	the	DET
aiti-13523	103	19	worst	bad	ADJ
aiti-13523	103	20	result	result	NOUN
aiti-13523	103	21	in	in	ADP
aiti-13523	103	22	terms	term	NOUN
aiti-13523	103	23	of	of	ADP
aiti-13523	103	24	f1	f1	NOUN
aiti-13523	103	25	-	-	PUNCT
aiti-13523	103	26	score	score	NOUN
aiti-13523	103	27	using	use	VERB
aiti-13523	103	28	the	the	DET
aiti-13523	103	29	lime	lime	NOUN
aiti-13523	103	30	model	model	NOUN
aiti-13523	103	31	[	[	X
aiti-13523	103	32	20	20	NUM
aiti-13523	103	33	]	]	PUNCT
aiti-13523	103	34	to	to	PART
aiti-13523	103	35	have	have	VERB
aiti-13523	103	36	clear	clear	ADJ
aiti-13523	103	37	and	and	CCONJ
aiti-13523	103	38	complete	complete	ADJ
aiti-13523	103	39	explanations	explanation	NOUN
aiti-13523	103	40	of	of	ADP
aiti-13523	103	41	the	the	DET
aiti-13523	103	42	predictions	prediction	NOUN
aiti-13523	103	43	obtained	obtain	VERB
aiti-13523	103	44	and	and	CCONJ
aiti-13523	103	45	to	to	PART
aiti-13523	103	46	identify	identify	VERB
aiti-13523	103	47	gaps	gap	NOUN
aiti-13523	103	48	related	relate	VERB
aiti-13523	103	49	to	to	ADP
aiti-13523	103	50	annotation	annotation	NOUN
aiti-13523	103	51	and	and	CCONJ
aiti-13523	103	52	sentiment	sentiment	NOUN
aiti-13523	103	53	polarity	polarity	NOUN
aiti-13523	103	54	.	.	PUNCT
aiti-13523	104	1	3	3	X
aiti-13523	104	2	.	.	NUM
aiti-13523	104	3	proposed	propose	VERB
aiti-13523	104	4	approach	approach	NOUN
aiti-13523	104	5	in	in	ADP
aiti-13523	104	6	this	this	DET
aiti-13523	104	7	section	section	NOUN
aiti-13523	104	8	,	,	PUNCT
aiti-13523	104	9	a	a	DET
aiti-13523	104	10	description	description	NOUN
aiti-13523	104	11	of	of	ADP
aiti-13523	104	12	the	the	DET
aiti-13523	104	13	approach	approach	NOUN
aiti-13523	104	14	to	to	ADP
aiti-13523	104	15	sentiment	sentiment	NOUN
aiti-13523	104	16	classification	classification	NOUN
aiti-13523	104	17	in	in	ADP
aiti-13523	104	18	health	health	NOUN
aiti-13523	104	19	-	-	PUNCT
aiti-13523	104	20	related	relate	VERB
aiti-13523	104	21	text	text	NOUN
aiti-13523	104	22	data	datum	NOUN
aiti-13523	104	23	,	,	PUNCT
aiti-13523	104	24	as	as	ADV
aiti-13523	104	25	well	well	ADV
aiti-13523	104	26	as	as	ADP
aiti-13523	104	27	explaining	explain	VERB
aiti-13523	104	28	the	the	DET
aiti-13523	104	29	classifier	classifier	NOUN
aiti-13523	104	30	’s	’s	PART
aiti-13523	104	31	predictions	prediction	NOUN
aiti-13523	104	32	.	.	PUNCT
aiti-13523	105	1	this	this	DET
aiti-13523	105	2	study	study	NOUN
aiti-13523	105	3	is	be	AUX
aiti-13523	105	4	based	base	VERB
aiti-13523	105	5	on	on	ADP
aiti-13523	105	6	the	the	DET
aiti-13523	105	7	emohd	emohd	NOUN
aiti-13523	105	8	dataset	dataset	VERB
aiti-13523	106	1	[	[	X
aiti-13523	106	2	4	4	NUM
aiti-13523	106	3	]	]	PUNCT
aiti-13523	106	4	,	,	PUNCT
aiti-13523	106	5	which	which	PRON
aiti-13523	106	6	includes	include	VERB
aiti-13523	106	7	4,202	4,202	NUM
aiti-13523	106	8	text	text	NOUN
aiti-13523	106	9	samples	sample	NOUN
aiti-13523	106	10	classified	classify	VERB
aiti-13523	106	11	into	into	ADP
aiti-13523	106	12	eight	eight	NUM
aiti-13523	106	13	disease	disease	NOUN
aiti-13523	106	14	classes	class	NOUN
aiti-13523	106	15	and	and	CCONJ
aiti-13523	106	16	six	six	NUM
aiti-13523	106	17	emotion	emotion	NOUN
aiti-13523	106	18	classes	class	NOUN
aiti-13523	106	19	,	,	PUNCT
aiti-13523	106	20	from	from	ADP
aiti-13523	106	21	various	various	ADJ
aiti-13523	106	22	online	online	ADJ
aiti-13523	106	23	platforms	platform	NOUN
aiti-13523	106	24	.	.	PUNCT
aiti-13523	107	1	advances	advance	NOUN
aiti-13523	107	2	in	in	ADP
aiti-13523	107	3	technology	technology	NOUN
aiti-13523	107	4	innovation	innovation	NOUN
aiti-13523	107	5	,	,	PUNCT
aiti-13523	107	6	vol	vol	NOUN
aiti-13523	107	7	.	.	PROPN
aiti-13523	108	1	9	9	NUM
aiti-13523	108	2	,	,	PUNCT
aiti-13523	108	3	no	no	INTJ
aiti-13523	108	4	.	.	NOUN
aiti-13523	108	5	2	2	NUM
aiti-13523	108	6	,	,	PUNCT
aiti-13523	108	7	2024	2024	NUM
aiti-13523	108	8	,	,	PUNCT
aiti-13523	108	9	pp	pp	ADJ
aiti-13523	108	10	.	.	PUNCT
aiti-13523	109	1	129	129	NUM
aiti-13523	109	2	-	-	SYM
aiti-13523	109	3	142	142	NUM
aiti-13523	109	4	133	133	NUM
aiti-13523	109	5	fig	fig	NOUN
aiti-13523	109	6	.	.	PUNCT
aiti-13523	110	1	1	1	NUM
aiti-13523	110	2	illustrates	illustrate	VERB
aiti-13523	110	3	this	this	DET
aiti-13523	110	4	5	5	NUM
aiti-13523	110	5	-	-	PUNCT
aiti-13523	110	6	step	step	NOUN
aiti-13523	110	7	approach	approach	NOUN
aiti-13523	110	8	:	:	PUNCT
aiti-13523	110	9	the	the	DET
aiti-13523	110	10	first	first	ADJ
aiti-13523	110	11	is	be	AUX
aiti-13523	110	12	the	the	DET
aiti-13523	110	13	preprocessing	preprocessing	NOUN
aiti-13523	110	14	of	of	ADP
aiti-13523	110	15	the	the	DET
aiti-13523	110	16	textual	textual	ADJ
aiti-13523	110	17	data	datum	NOUN
aiti-13523	110	18	which	which	PRON
aiti-13523	110	19	is	be	AUX
aiti-13523	110	20	essential	essential	ADJ
aiti-13523	110	21	especially	especially	ADV
aiti-13523	110	22	since	since	SCONJ
aiti-13523	110	23	the	the	DET
aiti-13523	110	24	data	data	NOUN
aiti-13523	110	25	is	be	AUX
aiti-13523	110	26	often	often	ADV
aiti-13523	110	27	ambiguous	ambiguous	ADJ
aiti-13523	110	28	and	and	CCONJ
aiti-13523	110	29	noisy	noisy	ADJ
aiti-13523	110	30	,	,	PUNCT
aiti-13523	110	31	after	after	ADP
aiti-13523	110	32	that	that	PRON
aiti-13523	110	33	,	,	PUNCT
aiti-13523	110	34	a	a	DET
aiti-13523	110	35	process	process	NOUN
aiti-13523	110	36	of	of	ADP
aiti-13523	110	37	rebalancing	rebalancing	NOUN
aiti-13523	110	38	the	the	DET
aiti-13523	110	39	extremely	extremely	ADV
aiti-13523	110	40	unbalanced	unbalanced	ADJ
aiti-13523	110	41	data	datum	NOUN
aiti-13523	110	42	.	.	PUNCT
aiti-13523	111	1	this	this	PRON
aiti-13523	111	2	can	can	AUX
aiti-13523	111	3	be	be	AUX
aiti-13523	111	4	observed	observe	VERB
aiti-13523	111	5	in	in	ADP
aiti-13523	111	6	fig	fig	NOUN
aiti-13523	111	7	.	.	PUNCT
aiti-13523	112	1	2	2	NUM
aiti-13523	112	2	,	,	PUNCT
aiti-13523	112	3	which	which	PRON
aiti-13523	112	4	displays	display	VERB
aiti-13523	112	5	an	an	DET
aiti-13523	112	6	exploration	exploration	NOUN
aiti-13523	112	7	of	of	ADP
aiti-13523	112	8	different	different	ADJ
aiti-13523	112	9	re	re	ADJ
aiti-13523	112	10	-	-	ADJ
aiti-13523	112	11	sampling	sample	VERB
aiti-13523	112	12	methods	method	NOUN
aiti-13523	112	13	,	,	PUNCT
aiti-13523	112	14	then	then	ADV
aiti-13523	112	15	a	a	DET
aiti-13523	112	16	comparison	comparison	NOUN
aiti-13523	112	17	of	of	ADP
aiti-13523	112	18	basic	basic	ADJ
aiti-13523	112	19	classification	classification	NOUN
aiti-13523	112	20	models	model	NOUN
aiti-13523	112	21	(	(	PUNCT
aiti-13523	112	22	logistic	logistic	ADJ
aiti-13523	112	23	regression	regression	NOUN
aiti-13523	112	24	,	,	PUNCT
aiti-13523	112	25	nb	nb	INTJ
aiti-13523	112	26	,	,	PUNCT
aiti-13523	112	27	lightgbm	lightgbm	ADJ
aiti-13523	112	28	)	)	PUNCT
aiti-13523	112	29	with	with	ADP
aiti-13523	112	30	different	different	ADJ
aiti-13523	112	31	vectorization	vectorization	NOUN
aiti-13523	112	32	models	model	NOUN
aiti-13523	112	33	(	(	PUNCT
aiti-13523	112	34	cbow	cbow	VERB
aiti-13523	112	35	,	,	PUNCT
aiti-13523	112	36	tf	tf	PROPN
aiti-13523	112	37	-	-	PUNCT
aiti-13523	112	38	idf	idf	PROPN
aiti-13523	112	39	,	,	PUNCT
aiti-13523	112	40	and	and	CCONJ
aiti-13523	112	41	word2vec	word2vec	X
aiti-13523	112	42	)	)	PUNCT
aiti-13523	112	43	and	and	CCONJ
aiti-13523	112	44	in	in	ADP
aiti-13523	112	45	parallel	parallel	VERB
aiti-13523	112	46	an	an	DET
aiti-13523	112	47	implementation	implementation	NOUN
aiti-13523	112	48	of	of	ADP
aiti-13523	112	49	recurrent	recurrent	ADJ
aiti-13523	112	50	deep	deep	ADJ
aiti-13523	112	51	learning	learning	NOUN
aiti-13523	112	52	networks	network	NOUN
aiti-13523	112	53	is	be	AUX
aiti-13523	112	54	placed	place	VERB
aiti-13523	112	55	:	:	PUNCT
aiti-13523	112	56	the	the	DET
aiti-13523	112	57	lstm	lstm	ADJ
aiti-13523	112	58	sequential	sequential	ADJ
aiti-13523	112	59	model	model	NOUN
aiti-13523	112	60	and	and	CCONJ
aiti-13523	112	61	bert	bert	PROPN
aiti-13523	112	62	to	to	PART
aiti-13523	112	63	compare	compare	VERB
aiti-13523	112	64	the	the	DET
aiti-13523	112	65	performance	performance	NOUN
aiti-13523	112	66	of	of	ADP
aiti-13523	112	67	the	the	DET
aiti-13523	112	68	convolutional	convolutional	ADJ
aiti-13523	112	69	classifier	classifier	NOUN
aiti-13523	112	70	with	with	ADP
aiti-13523	112	71	the	the	DET
aiti-13523	112	72	base	base	NOUN
aiti-13523	112	73	models	model	NOUN
aiti-13523	112	74	.	.	PUNCT
aiti-13523	113	1	the	the	DET
aiti-13523	113	2	last	last	ADJ
aiti-13523	113	3	step	step	NOUN
aiti-13523	113	4	of	of	ADP
aiti-13523	113	5	this	this	DET
aiti-13523	113	6	approach	approach	NOUN
aiti-13523	113	7	concerns	concern	VERB
aiti-13523	113	8	the	the	DET
aiti-13523	113	9	explainability	explainability	NOUN
aiti-13523	113	10	of	of	ADP
aiti-13523	113	11	the	the	DET
aiti-13523	113	12	learning	learning	NOUN
aiti-13523	113	13	model	model	NOUN
aiti-13523	113	14	having	having	AUX
aiti-13523	113	15	obtained	obtain	VERB
aiti-13523	113	16	the	the	DET
aiti-13523	113	17	worst	bad	ADJ
aiti-13523	113	18	classification	classification	NOUN
aiti-13523	113	19	results	result	NOUN
aiti-13523	113	20	through	through	ADP
aiti-13523	113	21	the	the	DET
aiti-13523	113	22	analysis	analysis	NOUN
aiti-13523	113	23	of	of	ADP
aiti-13523	113	24	the	the	DET
aiti-13523	113	25	predictions	prediction	NOUN
aiti-13523	113	26	using	use	VERB
aiti-13523	113	27	the	the	DET
aiti-13523	113	28	lime	lime	NOUN
aiti-13523	113	29	model	model	NOUN
aiti-13523	113	30	.	.	PUNCT
aiti-13523	114	1	fig	fig	NOUN
aiti-13523	114	2	.	.	PUNCT
aiti-13523	115	1	1	1	NUM
aiti-13523	115	2	classification	classification	NOUN
aiti-13523	115	3	and	and	CCONJ
aiti-13523	115	4	analysis	analysis	NOUN
aiti-13523	115	5	of	of	ADP
aiti-13523	115	6	sentiment	sentiment	NOUN
aiti-13523	115	7	predictions	prediction	NOUN
aiti-13523	115	8	on	on	ADP
aiti-13523	115	9	health	health	NOUN
aiti-13523	115	10	-	-	PUNCT
aiti-13523	115	11	related	relate	VERB
aiti-13523	115	12	imbalanced	imbalanced	ADJ
aiti-13523	115	13	textual	textual	ADJ
aiti-13523	115	14	data	datum	NOUN
aiti-13523	115	15	approach	approach	NOUN
aiti-13523	115	16	fig	fig	NOUN
aiti-13523	115	17	.	.	PUNCT
aiti-13523	116	1	2	2	NUM
aiti-13523	116	2	emohd	emohd	NOUN
aiti-13523	116	3	dataset	dataset	NOUN
aiti-13523	116	4	class	class	NOUN
aiti-13523	116	5	distribution	distribution	NOUN
aiti-13523	116	6	3.1	3.1	NUM
aiti-13523	116	7	.	.	PUNCT
aiti-13523	117	1	data	datum	NOUN
aiti-13523	117	2	preprocessing	preprocesse	VERB
aiti-13523	117	3	to	to	PART
aiti-13523	117	4	classify	classify	VERB
aiti-13523	117	5	the	the	DET
aiti-13523	117	6	textual	textual	ADJ
aiti-13523	117	7	data	datum	NOUN
aiti-13523	117	8	in	in	ADP
aiti-13523	117	9	the	the	DET
aiti-13523	117	10	emohd	emohd	NOUN
aiti-13523	117	11	dataset	dataset	NOUN
aiti-13523	117	12	,	,	PUNCT
aiti-13523	117	13	it	it	PRON
aiti-13523	117	14	is	be	AUX
aiti-13523	117	15	necessary	necessary	ADJ
aiti-13523	117	16	to	to	PART
aiti-13523	117	17	perform	perform	VERB
aiti-13523	117	18	preprocessing	preprocesse	VERB
aiti-13523	117	19	to	to	PART
aiti-13523	117	20	remove	remove	VERB
aiti-13523	117	21	noise	noise	NOUN
aiti-13523	117	22	,	,	PUNCT
aiti-13523	117	23	and	and	CCONJ
aiti-13523	117	24	make	make	VERB
aiti-13523	117	25	it	it	PRON
aiti-13523	117	26	usable	usable	ADJ
aiti-13523	117	27	,	,	PUNCT
aiti-13523	117	28	especially	especially	ADV
aiti-13523	117	29	since	since	SCONJ
aiti-13523	117	30	this	this	DET
aiti-13523	117	31	data	data	NOUN
aiti-13523	117	32	comes	come	VERB
aiti-13523	117	33	from	from	ADP
aiti-13523	117	34	the	the	DET
aiti-13523	117	35	web	web	NOUN
aiti-13523	117	36	and	and	CCONJ
aiti-13523	117	37	is	be	AUX
aiti-13523	117	38	unstructured	unstructure	VERB
aiti-13523	117	39	.	.	PUNCT
aiti-13523	118	1	this	this	DET
aiti-13523	118	2	cleaning	cleaning	NOUN
aiti-13523	118	3	process	process	NOUN
aiti-13523	118	4	aims	aim	VERB
aiti-13523	118	5	to	to	PART
aiti-13523	118	6	improve	improve	VERB
aiti-13523	118	7	sentiment	sentiment	NOUN
aiti-13523	118	8	classification	classification	NOUN
aiti-13523	118	9	results	result	NOUN
aiti-13523	118	10	.	.	PUNCT
aiti-13523	119	1	here	here	ADV
aiti-13523	119	2	are	be	AUX
aiti-13523	119	3	the	the	DET
aiti-13523	119	4	main	main	ADJ
aiti-13523	119	5	measures	measure	NOUN
aiti-13523	119	6	taken	take	VERB
aiti-13523	119	7	:	:	PUNCT
aiti-13523	119	8	(	(	PUNCT
aiti-13523	119	9	1	1	X
aiti-13523	119	10	)	)	PUNCT
aiti-13523	119	11	lowercase	lowercase	NOUN
aiti-13523	119	12	conversion	conversion	NOUN
aiti-13523	119	13	:	:	PUNCT
aiti-13523	119	14	the	the	DET
aiti-13523	119	15	first	first	ADJ
aiti-13523	119	16	step	step	NOUN
aiti-13523	119	17	in	in	ADP
aiti-13523	119	18	preprocessing	preprocessing	NOUN
aiti-13523	119	19	is	be	AUX
aiti-13523	119	20	to	to	PART
aiti-13523	119	21	convert	convert	VERB
aiti-13523	119	22	uppercase	uppercase	ADJ
aiti-13523	119	23	terms	term	NOUN
aiti-13523	119	24	to	to	PART
aiti-13523	119	25	lowercase	lowercase	VERB
aiti-13523	119	26	to	to	PART
aiti-13523	119	27	avoid	avoid	VERB
aiti-13523	119	28	redundant	redundant	ADJ
aiti-13523	119	29	words	word	NOUN
aiti-13523	119	30	.	.	PUNCT
aiti-13523	120	1	even	even	ADV
aiti-13523	120	2	if	if	SCONJ
aiti-13523	120	3	the	the	DET
aiti-13523	120	4	spelling	spelling	NOUN
aiti-13523	120	5	of	of	ADP
aiti-13523	120	6	two	two	NUM
aiti-13523	120	7	upperand	upperand	ADV
aiti-13523	120	8	lower	low	ADJ
aiti-13523	120	9	-	-	PUNCT
aiti-13523	120	10	case	case	NOUN
aiti-13523	120	11	words	word	NOUN
aiti-13523	120	12	like	like	ADP
aiti-13523	120	13	“	"	PUNCT
aiti-13523	120	14	health	health	NOUN
aiti-13523	120	15	”	"	PUNCT
aiti-13523	120	16	and	and	CCONJ
aiti-13523	120	17	“	"	PUNCT
aiti-13523	120	18	health	health	NOUN
aiti-13523	120	19	”	"	PUNCT
aiti-13523	120	20	are	be	AUX
aiti-13523	120	21	semantically	semantically	ADV
aiti-13523	120	22	identical	identical	ADJ
aiti-13523	120	23	,	,	PUNCT
aiti-13523	120	24	they	they	PRON
aiti-13523	120	25	are	be	AUX
aiti-13523	120	26	treated	treat	VERB
aiti-13523	120	27	as	as	ADP
aiti-13523	120	28	two	two	NUM
aiti-13523	120	29	different	different	ADJ
aiti-13523	120	30	lexical	lexical	ADJ
aiti-13523	120	31	units	unit	NOUN
aiti-13523	120	32	.	.	PUNCT
aiti-13523	121	1	(	(	PUNCT
aiti-13523	121	2	2	2	X
aiti-13523	121	3	)	)	PUNCT
aiti-13523	121	4	punctuation	punctuation	NOUN
aiti-13523	121	5	removal	removal	NOUN
aiti-13523	121	6	:	:	PUNCT
aiti-13523	121	7	this	this	DET
aiti-13523	121	8	step	step	NOUN
aiti-13523	121	9	involves	involve	VERB
aiti-13523	121	10	removing	remove	VERB
aiti-13523	121	11	any	any	DET
aiti-13523	121	12	punctuation	punctuation	NOUN
aiti-13523	121	13	from	from	ADP
aiti-13523	121	14	the	the	DET
aiti-13523	121	15	text	text	NOUN
aiti-13523	121	16	that	that	PRON
aiti-13523	121	17	does	do	AUX
aiti-13523	121	18	not	not	PART
aiti-13523	121	19	provide	provide	VERB
aiti-13523	121	20	any	any	DET
aiti-13523	121	21	useful	useful	ADJ
aiti-13523	121	22	information	information	NOUN
aiti-13523	121	23	to	to	PART
aiti-13523	121	24	improve	improve	VERB
aiti-13523	121	25	data	data	NOUN
aiti-13523	121	26	classification	classification	NOUN
aiti-13523	121	27	performance	performance	NOUN
aiti-13523	121	28	.	.	PUNCT
aiti-13523	122	1	(	(	PUNCT
aiti-13523	122	2	3	3	X
aiti-13523	122	3	)	)	PUNCT
aiti-13523	122	4	delete	delete	ADJ
aiti-13523	122	5	stop	stop	NOUN
aiti-13523	122	6	words	word	NOUN
aiti-13523	122	7	:	:	PUNCT
aiti-13523	122	8	these	these	PRON
aiti-13523	122	9	are	be	AUX
aiti-13523	122	10	very	very	ADV
aiti-13523	122	11	common	common	ADJ
aiti-13523	122	12	words	word	NOUN
aiti-13523	122	13	in	in	ADP
aiti-13523	122	14	the	the	DET
aiti-13523	122	15	language	language	NOUN
aiti-13523	122	16	studied	study	VERB
aiti-13523	122	17	that	that	PRON
aiti-13523	122	18	do	do	AUX
aiti-13523	122	19	not	not	PART
aiti-13523	122	20	provide	provide	VERB
aiti-13523	122	21	any	any	DET
aiti-13523	122	22	informative	informative	ADJ
aiti-13523	122	23	value	value	NOUN
aiti-13523	122	24	for	for	ADP
aiti-13523	122	25	understanding	understand	VERB
aiti-13523	122	26	the	the	DET
aiti-13523	122	27	“	"	PUNCT
aiti-13523	122	28	meaning	meaning	NOUN
aiti-13523	122	29	”	"	PUNCT
aiti-13523	122	30	of	of	ADP
aiti-13523	122	31	a	a	DET
aiti-13523	122	32	document	document	NOUN
aiti-13523	122	33	and	and	CCONJ
aiti-13523	122	34	a	a	DET
aiti-13523	122	35	corpus	corpus	NOUN
aiti-13523	122	36	,	,	PUNCT
aiti-13523	122	37	which	which	PRON
aiti-13523	122	38	are	be	AUX
aiti-13523	122	39	isolated	isolate	VERB
aiti-13523	122	40	and	and	CCONJ
aiti-13523	122	41	deleted	delete	VERB
aiti-13523	122	42	.	.	PUNCT
aiti-13523	123	1	(	(	PUNCT
aiti-13523	123	2	4	4	X
aiti-13523	123	3	)	)	PUNCT
aiti-13523	123	4	removal	removal	NOUN
aiti-13523	123	5	of	of	ADP
aiti-13523	123	6	rare	rare	ADJ
aiti-13523	123	7	and	and	CCONJ
aiti-13523	123	8	common	common	ADJ
aiti-13523	123	9	words	word	NOUN
aiti-13523	123	10	:	:	PUNCT
aiti-13523	123	11	to	to	PART
aiti-13523	123	12	avoid	avoid	VERB
aiti-13523	123	13	the	the	DET
aiti-13523	123	14	noise	noise	NOUN
aiti-13523	123	15	that	that	SCONJ
aiti-13523	123	16	rare	rare	ADJ
aiti-13523	123	17	words	word	NOUN
aiti-13523	123	18	can	can	AUX
aiti-13523	123	19	generate	generate	VERB
aiti-13523	123	20	in	in	ADP
aiti-13523	123	21	a	a	DET
aiti-13523	123	22	text	text	NOUN
aiti-13523	123	23	and	and	CCONJ
aiti-13523	123	24	the	the	DET
aiti-13523	123	25	impact	impact	NOUN
aiti-13523	123	26	that	that	PRON
aiti-13523	123	27	too	too	ADV
aiti-13523	123	28	frequent	frequent	ADJ
aiti-13523	123	29	words	word	NOUN
aiti-13523	123	30	can	can	AUX
aiti-13523	123	31	also	also	ADV
aiti-13523	123	32	have	have	VERB
aiti-13523	123	33	in	in	ADP
aiti-13523	123	34	the	the	DET
aiti-13523	123	35	classification	classification	NOUN
aiti-13523	123	36	,	,	PUNCT
aiti-13523	123	37	remove	remove	VERB
aiti-13523	123	38	rare	rare	ADJ
aiti-13523	123	39	and	and	CCONJ
aiti-13523	123	40	common	common	ADJ
aiti-13523	123	41	terms	term	NOUN
aiti-13523	123	42	by	by	ADP
aiti-13523	123	43	counting	count	VERB
aiti-13523	123	44	their	their	PRON
aiti-13523	123	45	frequencies	frequency	NOUN
aiti-13523	123	46	in	in	ADP
aiti-13523	123	47	the	the	DET
aiti-13523	123	48	text	text	NOUN
aiti-13523	123	49	.	.	PUNCT
aiti-13523	124	1	(	(	PUNCT
aiti-13523	124	2	5	5	X
aiti-13523	124	3	)	)	PUNCT
aiti-13523	124	4	lemmatization	lemmatization	NOUN
aiti-13523	124	5	:	:	PUNCT
aiti-13523	124	6	it	it	PRON
aiti-13523	124	7	consists	consist	VERB
aiti-13523	124	8	of	of	ADP
aiti-13523	124	9	replacing	replace	VERB
aiti-13523	124	10	each	each	DET
aiti-13523	124	11	word	word	NOUN
aiti-13523	124	12	with	with	ADP
aiti-13523	124	13	its	its	PRON
aiti-13523	124	14	canonical	canonical	ADJ
aiti-13523	124	15	form	form	NOUN
aiti-13523	124	16	,	,	PUNCT
aiti-13523	124	17	for	for	ADP
aiti-13523	124	18	example	example	NOUN
aiti-13523	124	19	,	,	PUNCT
aiti-13523	124	20	the	the	DET
aiti-13523	124	21	known	know	VERB
aiti-13523	124	22	word	word	NOUN
aiti-13523	124	23	refers	refer	VERB
aiti-13523	124	24	to	to	ADP
aiti-13523	124	25	its	its	PRON
aiti-13523	124	26	canonical	canonical	ADJ
aiti-13523	124	27	form	form	NOUN
aiti-13523	124	28	namely	namely	ADV
aiti-13523	124	29	.	.	PUNCT
aiti-13523	125	1	this	this	DET
aiti-13523	125	2	step	step	NOUN
aiti-13523	125	3	is	be	AUX
aiti-13523	125	4	useful	useful	ADJ
aiti-13523	125	5	for	for	ADP
aiti-13523	125	6	the	the	DET
aiti-13523	125	7	thematic	thematic	ADJ
aiti-13523	125	8	classification	classification	NOUN
aiti-13523	125	9	of	of	ADP
aiti-13523	125	10	texts	text	NOUN
aiti-13523	125	11	because	because	SCONJ
aiti-13523	125	12	it	it	PRON
aiti-13523	125	13	allows	allow	VERB
aiti-13523	125	14	the	the	DET
aiti-13523	125	15	different	different	ADJ
aiti-13523	125	16	variants	variant	NOUN
aiti-13523	125	17	resulting	result	VERB
aiti-13523	125	18	from	from	ADP
aiti-13523	125	19	the	the	DET
aiti-13523	125	20	same	same	ADJ
aiti-13523	125	21	form	form	NOUN
aiti-13523	125	22	or	or	CCONJ
aiti-13523	125	23	canonical	canonical	ADJ
aiti-13523	125	24	root	root	NOUN
aiti-13523	125	25	to	to	PART
aiti-13523	125	26	be	be	AUX
aiti-13523	125	27	treated	treat	VERB
aiti-13523	125	28	as	as	ADP
aiti-13523	125	29	a	a	DET
aiti-13523	125	30	single	single	ADJ
aiti-13523	125	31	word	word	NOUN
aiti-13523	125	32	.	.	PUNCT
aiti-13523	126	1	(	(	PUNCT
aiti-13523	126	2	6	6	NUM
aiti-13523	126	3	)	)	PUNCT
aiti-13523	126	4	tokenization	tokenization	NOUN
aiti-13523	126	5	:	:	PUNCT
aiti-13523	126	6	the	the	DET
aiti-13523	126	7	process	process	NOUN
aiti-13523	126	8	of	of	ADP
aiti-13523	126	9	dividing	divide	VERB
aiti-13523	126	10	text	text	NOUN
aiti-13523	126	11	into	into	ADP
aiti-13523	126	12	tokens	token	NOUN
aiti-13523	126	13	or	or	CCONJ
aiti-13523	126	14	linguistic	linguistic	ADJ
aiti-13523	126	15	units	unit	NOUN
aiti-13523	126	16	such	such	ADJ
aiti-13523	126	17	as	as	ADP
aiti-13523	126	18	words	word	NOUN
aiti-13523	126	19	,	,	PUNCT
aiti-13523	126	20	punctuation	punctuation	NOUN
aiti-13523	126	21	marks	mark	NOUN
aiti-13523	126	22	,	,	PUNCT
aiti-13523	126	23	numbers	number	NOUN
aiti-13523	126	24	,	,	PUNCT
aiti-13523	126	25	and	and	CCONJ
aiti-13523	126	26	alphanumeric	alphanumeric	ADJ
aiti-13523	126	27	data	datum	NOUN
aiti-13523	126	28	.	.	PUNCT
aiti-13523	127	1	each	each	DET
aiti-13523	127	2	element	element	NOUN
aiti-13523	127	3	corresponds	correspond	VERB
aiti-13523	127	4	to	to	ADP
aiti-13523	127	5	a	a	DET
aiti-13523	127	6	token	token	NOUN
aiti-13523	127	7	which	which	PRON
aiti-13523	127	8	will	will	AUX
aiti-13523	127	9	be	be	AUX
aiti-13523	127	10	useful	useful	ADJ
aiti-13523	127	11	for	for	ADP
aiti-13523	127	12	the	the	DET
aiti-13523	127	13	analysis	analysis	NOUN
aiti-13523	127	14	.	.	PUNCT
aiti-13523	128	1	3.2	3.2	NUM
aiti-13523	128	2	.	.	PUNCT
aiti-13523	129	1	data	datum	NOUN
aiti-13523	129	2	re	re	VERB
aiti-13523	129	3	-	-	NOUN
aiti-13523	129	4	sampling	sample	VERB
aiti-13523	129	5	as	as	SCONJ
aiti-13523	129	6	shown	show	VERB
aiti-13523	129	7	in	in	ADP
aiti-13523	129	8	fig	fig	NOUN
aiti-13523	129	9	.	.	PUNCT
aiti-13523	130	1	2	2	NUM
aiti-13523	130	2	,	,	PUNCT
aiti-13523	130	3	emohd	emohd	PROPN
aiti-13523	130	4	data	datum	NOUN
aiti-13523	130	5	is	be	AUX
aiti-13523	130	6	unbalanced	unbalanced	ADJ
aiti-13523	130	7	,	,	PUNCT
aiti-13523	130	8	which	which	PRON
aiti-13523	130	9	may	may	AUX
aiti-13523	130	10	impair	impair	VERB
aiti-13523	130	11	classification	classification	NOUN
aiti-13523	130	12	performance	performance	NOUN
aiti-13523	130	13	,	,	PUNCT
aiti-13523	130	14	so	so	ADV
aiti-13523	130	15	resampling	resample	VERB
aiti-13523	130	16	is	be	AUX
aiti-13523	130	17	necessary	necessary	ADJ
aiti-13523	130	18	.	.	PUNCT
aiti-13523	131	1	there	there	PRON
aiti-13523	131	2	are	be	VERB
aiti-13523	131	3	several	several	ADJ
aiti-13523	131	4	ways	way	NOUN
aiti-13523	131	5	to	to	PART
aiti-13523	131	6	handle	handle	VERB
aiti-13523	131	7	imbalanced	imbalanced	ADJ
aiti-13523	131	8	data	datum	NOUN
aiti-13523	131	9	,	,	PUNCT
aiti-13523	131	10	such	such	ADJ
aiti-13523	131	11	as	as	ADP
aiti-13523	131	12	undersampling	undersampling	ADJ
aiti-13523	131	13	and	and	CCONJ
aiti-13523	131	14	oversampling	oversampling	ADJ
aiti-13523	131	15	.	.	PUNCT
aiti-13523	132	1	in	in	ADP
aiti-13523	132	2	this	this	DET
aiti-13523	132	3	study	study	NOUN
aiti-13523	132	4	different	different	ADJ
aiti-13523	132	5	resampling	resample	VERB
aiti-13523	132	6	methods	method	NOUN
aiti-13523	132	7	are	be	AUX
aiti-13523	132	8	tested	test	VERB
aiti-13523	132	9	to	to	PART
aiti-13523	132	10	see	see	VERB
aiti-13523	132	11	their	their	PRON
aiti-13523	132	12	impact	impact	NOUN
aiti-13523	132	13	on	on	ADP
aiti-13523	132	14	the	the	DET
aiti-13523	132	15	results	result	NOUN
aiti-13523	132	16	of	of	ADP
aiti-13523	132	17	the	the	DET
aiti-13523	132	18	classification	classification	NOUN
aiti-13523	132	19	,	,	PUNCT
aiti-13523	132	20	the	the	DET
aiti-13523	132	21	choice	choice	NOUN
aiti-13523	132	22	of	of	ADP
aiti-13523	132	23	methods	method	NOUN
aiti-13523	132	24	used	use	VERB
aiti-13523	132	25	covers	cover	VERB
aiti-13523	132	26	those	those	DET
aiti-13523	132	27	best	well	ADV
aiti-13523	132	28	known	know	VERB
aiti-13523	132	29	134	134	NUM
aiti-13523	132	30	advances	advance	NOUN
aiti-13523	132	31	in	in	ADP
aiti-13523	132	32	technology	technology	NOUN
aiti-13523	132	33	innovation	innovation	NOUN
aiti-13523	132	34	,	,	PUNCT
aiti-13523	132	35	vol	vol	NOUN
aiti-13523	132	36	.	.	PROPN
aiti-13523	133	1	9	9	NUM
aiti-13523	133	2	,	,	PUNCT
aiti-13523	133	3	no	no	INTJ
aiti-13523	133	4	.	.	NOUN
aiti-13523	133	5	2	2	NUM
aiti-13523	133	6	,	,	PUNCT
aiti-13523	133	7	2024	2024	NUM
aiti-13523	133	8	,	,	PUNCT
aiti-13523	133	9	pp	pp	ADJ
aiti-13523	133	10	.	.	PUNCT
aiti-13523	134	1	129	129	NUM
aiti-13523	134	2	-	-	SYM
aiti-13523	134	3	142	142	NUM
aiti-13523	134	4	in	in	ADP
aiti-13523	134	5	the	the	DET
aiti-13523	134	6	additional	additional	ADJ
aiti-13523	134	7	field	field	NOUN
aiti-13523	134	8	:	:	PUNCT
aiti-13523	134	9	naive	naive	ADJ
aiti-13523	134	10	undersampling	undersampling	NOUN
aiti-13523	134	11	,	,	PUNCT
aiti-13523	134	12	which	which	PRON
aiti-13523	134	13	consists	consist	VERB
aiti-13523	134	14	of	of	ADP
aiti-13523	134	15	removing	remove	VERB
aiti-13523	134	16	certain	certain	ADJ
aiti-13523	134	17	minority	minority	NOUN
aiti-13523	134	18	classes	class	NOUN
aiti-13523	134	19	(	(	PUNCT
aiti-13523	134	20	in	in	ADP
aiti-13523	134	21	the	the	DET
aiti-13523	134	22	case	case	NOUN
aiti-13523	134	23	of	of	ADP
aiti-13523	134	24	emohd	emohd	PROPN
aiti-13523	134	25	data	datum	NOUN
aiti-13523	134	26	this	this	PRON
aiti-13523	134	27	is	be	AUX
aiti-13523	134	28	the	the	DET
aiti-13523	134	29	minority	minority	NOUN
aiti-13523	134	30	class	class	NOUN
aiti-13523	134	31	sad	sad	ADJ
aiti-13523	134	32	)	)	PUNCT
aiti-13523	134	33	,	,	PUNCT
aiti-13523	134	34	and	and	CCONJ
aiti-13523	134	35	oversampling	oversampling	NOUN
aiti-13523	134	36	which	which	PRON
aiti-13523	134	37	involves	involve	VERB
aiti-13523	134	38	adding	add	VERB
aiti-13523	134	39	additional	additional	ADJ
aiti-13523	134	40	copies	copy	NOUN
aiti-13523	134	41	of	of	ADP
aiti-13523	134	42	observations	observation	NOUN
aiti-13523	134	43	from	from	ADP
aiti-13523	134	44	the	the	DET
aiti-13523	134	45	minority	minority	NOUN
aiti-13523	134	46	class	class	NOUN
aiti-13523	134	47	to	to	PART
aiti-13523	134	48	balance	balance	VERB
aiti-13523	134	49	the	the	DET
aiti-13523	134	50	class	class	NOUN
aiti-13523	134	51	distribution	distribution	NOUN
aiti-13523	134	52	,	,	PUNCT
aiti-13523	134	53	and	and	CCONJ
aiti-13523	134	54	in	in	ADP
aiti-13523	134	55	this	this	DET
aiti-13523	134	56	perspective	perspective	NOUN
aiti-13523	134	57	this	this	DET
aiti-13523	134	58	study	study	NOUN
aiti-13523	134	59	tests	test	VERB
aiti-13523	134	60	different	different	ADJ
aiti-13523	134	61	oversampling	oversampling	ADJ
aiti-13523	134	62	approaches	approach	NOUN
aiti-13523	134	63	:	:	PUNCT
aiti-13523	134	64	(	(	PUNCT
aiti-13523	134	65	1	1	X
aiti-13523	134	66	)	)	PUNCT
aiti-13523	134	67	naive	naive	ADJ
aiti-13523	134	68	oversampling	oversampling	NOUN
aiti-13523	134	69	:	:	PUNCT
aiti-13523	134	70	this	this	PRON
aiti-13523	134	71	involves	involves	AUX
aiti-13523	134	72	randomly	randomly	ADV
aiti-13523	134	73	duplicating	duplicate	VERB
aiti-13523	134	74	the	the	DET
aiti-13523	134	75	observations	observation	NOUN
aiti-13523	134	76	of	of	ADP
aiti-13523	134	77	the	the	DET
aiti-13523	134	78	minority	minority	NOUN
aiti-13523	134	79	class	class	NOUN
aiti-13523	134	80	to	to	PART
aiti-13523	134	81	strengthen	strengthen	VERB
aiti-13523	134	82	its	its	PRON
aiti-13523	134	83	signal	signal	NOUN
aiti-13523	134	84	by	by	ADP
aiti-13523	134	85	resampling	resample	VERB
aiti-13523	134	86	with	with	ADP
aiti-13523	134	87	replacement	replacement	NOUN
aiti-13523	134	88	.	.	PUNCT
aiti-13523	135	1	(	(	PUNCT
aiti-13523	135	2	2	2	X
aiti-13523	135	3	)	)	PUNCT
aiti-13523	135	4	nearmiss	nearmiss	ADJ
aiti-13523	135	5	:	:	PUNCT
aiti-13523	135	6	there	there	PRON
aiti-13523	135	7	are	be	VERB
aiti-13523	135	8	3	3	NUM
aiti-13523	135	9	versions	version	NOUN
aiti-13523	135	10	of	of	ADP
aiti-13523	135	11	nearmiss	nearmiss	NOUN
aiti-13523	135	12	.	.	PUNCT
aiti-13523	136	1	in	in	ADP
aiti-13523	136	2	this	this	DET
aiti-13523	136	3	study	study	NOUN
aiti-13523	136	4	,	,	PUNCT
aiti-13523	136	5	an	an	DET
aiti-13523	136	6	experiment	experiment	NOUN
aiti-13523	136	7	with	with	ADP
aiti-13523	136	8	nearmiss1	nearmiss1	NOUN
aiti-13523	136	9	selects	select	VERB
aiti-13523	136	10	examples	example	NOUN
aiti-13523	136	11	from	from	ADP
aiti-13523	136	12	the	the	DET
aiti-13523	136	13	majority	majority	NOUN
aiti-13523	136	14	class	class	NOUN
aiti-13523	136	15	that	that	PRON
aiti-13523	136	16	are	be	AUX
aiti-13523	136	17	close	close	ADJ
aiti-13523	136	18	to	to	ADP
aiti-13523	136	19	three	three	NUM
aiti-13523	136	20	of	of	ADP
aiti-13523	136	21	the	the	DET
aiti-13523	136	22	closest	close	ADJ
aiti-13523	136	23	examples	example	NOUN
aiti-13523	136	24	from	from	ADP
aiti-13523	136	25	the	the	DET
aiti-13523	136	26	minority	minority	NOUN
aiti-13523	136	27	class	class	NOUN
aiti-13523	136	28	and	and	CCONJ
aiti-13523	136	29	removes	remove	VERB
aiti-13523	136	30	them	they	PRON
aiti-13523	136	31	[	[	X
aiti-13523	136	32	21	21	NUM
aiti-13523	136	33	]	]	PUNCT
aiti-13523	136	34	.	.	PUNCT
aiti-13523	137	1	(	(	PUNCT
aiti-13523	137	2	3	3	X
aiti-13523	137	3	)	)	PUNCT
aiti-13523	137	4	smote	smote	NOUN
aiti-13523	137	5	:	:	PUNCT
aiti-13523	137	6	synthetic	synthetic	ADJ
aiti-13523	137	7	minority	minority	NOUN
aiti-13523	137	8	oversampling	oversample	VERB
aiti-13523	137	9	technique	technique	NOUN
aiti-13523	138	1	[	[	X
aiti-13523	138	2	22	22	NUM
aiti-13523	138	3	]	]	PUNCT
aiti-13523	138	4	,	,	PUNCT
aiti-13523	138	5	is	be	AUX
aiti-13523	138	6	a	a	DET
aiti-13523	138	7	method	method	NOUN
aiti-13523	138	8	for	for	ADP
aiti-13523	138	9	oversampling	oversample	VERB
aiti-13523	138	10	minority	minority	NOUN
aiti-13523	138	11	observations	observation	NOUN
aiti-13523	138	12	.	.	PUNCT
aiti-13523	139	1	the	the	DET
aiti-13523	139	2	smote	smote	ADJ
aiti-13523	139	3	algorithm	algorithm	NOUN
aiti-13523	139	4	generates	generate	VERB
aiti-13523	139	5	new	new	ADJ
aiti-13523	139	6	minority	minority	NOUN
aiti-13523	139	7	individuals	individual	NOUN
aiti-13523	139	8	similar	similar	ADJ
aiti-13523	139	9	to	to	ADP
aiti-13523	139	10	existing	exist	VERB
aiti-13523	139	11	ones	one	NOUN
aiti-13523	139	12	,	,	PUNCT
aiti-13523	139	13	without	without	ADP
aiti-13523	139	14	being	be	AUX
aiti-13523	139	15	strictly	strictly	ADV
aiti-13523	139	16	identical	identical	ADJ
aiti-13523	139	17	.	.	PUNCT
aiti-13523	140	1	this	this	PRON
aiti-13523	140	2	helps	help	VERB
aiti-13523	140	3	to	to	PART
aiti-13523	140	4	evenly	evenly	ADV
aiti-13523	140	5	distribute	distribute	VERB
aiti-13523	140	6	the	the	DET
aiti-13523	140	7	population	population	NOUN
aiti-13523	140	8	of	of	ADP
aiti-13523	140	9	minority	minority	NOUN
aiti-13523	140	10	individuals	individual	NOUN
aiti-13523	140	11	.	.	PUNCT
aiti-13523	141	1	(	(	PUNCT
aiti-13523	141	2	4	4	X
aiti-13523	141	3	)	)	PUNCT
aiti-13523	141	4	adasyn	adasyn	NOUN
aiti-13523	141	5	:	:	PUNCT
aiti-13523	141	6	the	the	DET
aiti-13523	141	7	goal	goal	NOUN
aiti-13523	141	8	of	of	ADP
aiti-13523	141	9	adasyn	adasyn	NOUN
aiti-13523	141	10	is	be	AUX
aiti-13523	141	11	to	to	PART
aiti-13523	141	12	generate	generate	VERB
aiti-13523	141	13	an	an	DET
aiti-13523	141	14	appropriate	appropriate	ADJ
aiti-13523	141	15	number	number	NOUN
aiti-13523	141	16	of	of	ADP
aiti-13523	141	17	synthetic	synthetic	ADJ
aiti-13523	141	18	alternatives	alternative	NOUN
aiti-13523	141	19	for	for	ADP
aiti-13523	141	20	each	each	DET
aiti-13523	141	21	minority	minority	NOUN
aiti-13523	141	22	class	class	NOUN
aiti-13523	141	23	observation	observation	NOUN
aiti-13523	141	24	[	[	X
aiti-13523	141	25	23	23	NUM
aiti-13523	141	26	]	]	PUNCT
aiti-13523	141	27	.	.	PUNCT
aiti-13523	142	1	the	the	DET
aiti-13523	142	2	concept	concept	NOUN
aiti-13523	142	3	of	of	ADP
aiti-13523	142	4	“	"	PUNCT
aiti-13523	142	5	appropriate	appropriate	ADJ
aiti-13523	142	6	number	number	NOUN
aiti-13523	142	7	”	"	PUNCT
aiti-13523	142	8	depends	depend	VERB
aiti-13523	142	9	on	on	ADP
aiti-13523	142	10	the	the	DET
aiti-13523	142	11	difficulty	difficulty	NOUN
aiti-13523	142	12	of	of	ADP
aiti-13523	142	13	learning	learn	VERB
aiti-13523	142	14	the	the	DET
aiti-13523	142	15	original	original	ADJ
aiti-13523	142	16	observation	observation	NOUN
aiti-13523	142	17	.	.	PUNCT
aiti-13523	143	1	3.3	3.3	NUM
aiti-13523	143	2	.	.	PUNCT
aiti-13523	144	1	feature	feature	NOUN
aiti-13523	144	2	selection	selection	NOUN
aiti-13523	144	3	as	as	SCONJ
aiti-13523	144	4	textual	textual	ADJ
aiti-13523	144	5	data	datum	NOUN
aiti-13523	144	6	can	can	AUX
aiti-13523	144	7	not	not	PART
aiti-13523	144	8	be	be	AUX
aiti-13523	144	9	used	use	VERB
aiti-13523	144	10	directly	directly	ADV
aiti-13523	144	11	in	in	ADP
aiti-13523	144	12	machine	machine	NOUN
aiti-13523	144	13	learning	learn	VERB
aiti-13523	144	14	algorithms	algorithm	NOUN
aiti-13523	144	15	including	include	VERB
aiti-13523	144	16	classical	classical	ADJ
aiti-13523	144	17	neural	neural	ADJ
aiti-13523	144	18	networks	network	NOUN
aiti-13523	144	19	,	,	PUNCT
aiti-13523	144	20	they	they	PRON
aiti-13523	144	21	must	must	AUX
aiti-13523	144	22	be	be	AUX
aiti-13523	144	23	converted	convert	VERB
aiti-13523	144	24	into	into	ADP
aiti-13523	144	25	digital	digital	ADJ
aiti-13523	144	26	representations	representation	NOUN
aiti-13523	144	27	.	.	PUNCT
aiti-13523	145	1	this	this	DET
aiti-13523	145	2	process	process	NOUN
aiti-13523	145	3	,	,	PUNCT
aiti-13523	145	4	called	call	VERB
aiti-13523	145	5	vectorization	vectorization	NOUN
aiti-13523	145	6	,	,	PUNCT
aiti-13523	145	7	transforms	transform	VERB
aiti-13523	145	8	raw	raw	ADJ
aiti-13523	145	9	text	text	NOUN
aiti-13523	145	10	data	datum	NOUN
aiti-13523	145	11	obtained	obtain	VERB
aiti-13523	145	12	after	after	ADP
aiti-13523	145	13	cleaning	clean	VERB
aiti-13523	145	14	into	into	ADP
aiti-13523	145	15	feature	feature	NOUN
aiti-13523	145	16	vectors	vector	NOUN
aiti-13523	145	17	.	.	PUNCT
aiti-13523	146	1	several	several	ADJ
aiti-13523	146	2	approaches	approach	NOUN
aiti-13523	146	3	can	can	AUX
aiti-13523	146	4	be	be	AUX
aiti-13523	146	5	used	use	VERB
aiti-13523	146	6	to	to	PART
aiti-13523	146	7	perform	perform	VERB
aiti-13523	146	8	this	this	DET
aiti-13523	146	9	task	task	NOUN
aiti-13523	146	10	,	,	PUNCT
aiti-13523	146	11	each	each	PRON
aiti-13523	146	12	extracting	extract	VERB
aiti-13523	146	13	different	different	ADJ
aiti-13523	146	14	types	type	NOUN
aiti-13523	146	15	of	of	ADP
aiti-13523	146	16	features	feature	NOUN
aiti-13523	146	17	from	from	ADP
aiti-13523	146	18	the	the	DET
aiti-13523	146	19	text	text	NOUN
aiti-13523	146	20	.	.	PUNCT
aiti-13523	147	1	this	this	DET
aiti-13523	147	2	study	study	NOUN
aiti-13523	147	3	,	,	PUNCT
aiti-13523	147	4	compares	compare	VERB
aiti-13523	147	5	different	different	ADJ
aiti-13523	147	6	vectorization	vectorization	NOUN
aiti-13523	147	7	methods	method	NOUN
aiti-13523	147	8	,	,	PUNCT
aiti-13523	147	9	including	include	VERB
aiti-13523	147	10	count	count	NOUN
aiti-13523	147	11	vectorization	vectorization	NOUN
aiti-13523	147	12	,	,	PUNCT
aiti-13523	147	13	tf	tf	PROPN
aiti-13523	147	14	-	-	PUNCT
aiti-13523	147	15	idf	idf	PROPN
aiti-13523	147	16	,	,	PUNCT
aiti-13523	147	17	and	and	CCONJ
aiti-13523	147	18	word2vec	word2vec	X
aiti-13523	147	19	,	,	PUNCT
aiti-13523	147	20	to	to	PART
aiti-13523	147	21	obtain	obtain	VERB
aiti-13523	147	22	relevant	relevant	ADJ
aiti-13523	147	23	features	feature	NOUN
aiti-13523	147	24	from	from	ADP
aiti-13523	147	25	text	text	NOUN
aiti-13523	147	26	data	datum	NOUN
aiti-13523	147	27	.	.	PUNCT
aiti-13523	148	1	first	first	ADV
aiti-13523	148	2	,	,	PUNCT
aiti-13523	148	3	an	an	DET
aiti-13523	148	4	implementation	implementation	NOUN
aiti-13523	148	5	of	of	ADP
aiti-13523	148	6	the	the	DET
aiti-13523	148	7	cbow	cbow	PROPN
aiti-13523	148	8	model	model	NOUN
aiti-13523	148	9	,	,	PUNCT
aiti-13523	148	10	which	which	PRON
aiti-13523	148	11	is	be	AUX
aiti-13523	148	12	a	a	DET
aiti-13523	148	13	textual	textual	ADJ
aiti-13523	148	14	representation	representation	NOUN
aiti-13523	148	15	that	that	PRON
aiti-13523	148	16	describes	describe	VERB
aiti-13523	148	17	the	the	DET
aiti-13523	148	18	occurrence	occurrence	NOUN
aiti-13523	148	19	of	of	ADP
aiti-13523	148	20	words	word	NOUN
aiti-13523	148	21	in	in	ADP
aiti-13523	148	22	a	a	DET
aiti-13523	148	23	document	document	NOUN
aiti-13523	148	24	,	,	PUNCT
aiti-13523	148	25	ignoring	ignore	VERB
aiti-13523	148	26	the	the	DET
aiti-13523	148	27	order	order	NOUN
aiti-13523	148	28	or	or	CCONJ
aiti-13523	148	29	structure	structure	NOUN
aiti-13523	148	30	of	of	ADP
aiti-13523	148	31	the	the	DET
aiti-13523	148	32	document	document	NOUN
aiti-13523	148	33	.	.	PUNCT
aiti-13523	149	1	the	the	DET
aiti-13523	149	2	model	model	NOUN
aiti-13523	149	3	only	only	ADV
aiti-13523	149	4	cares	care	VERB
aiti-13523	149	5	whether	whether	SCONJ
aiti-13523	149	6	known	know	VERB
aiti-13523	149	7	words	word	NOUN
aiti-13523	149	8	appear	appear	VERB
aiti-13523	149	9	in	in	ADP
aiti-13523	149	10	the	the	DET
aiti-13523	149	11	document	document	NOUN
aiti-13523	149	12	[	[	X
aiti-13523	149	13	24	24	NUM
aiti-13523	149	14	]	]	PUNCT
aiti-13523	149	15	.	.	PUNCT
aiti-13523	150	1	furthermore	furthermore	ADV
aiti-13523	150	2	,	,	PUNCT
aiti-13523	150	3	experiment	experiment	NOUN
aiti-13523	150	4	with	with	ADP
aiti-13523	150	5	tf	tf	PROPN
aiti-13523	150	6	-	-	PUNCT
aiti-13523	150	7	idf	idf	PROPN
aiti-13523	150	8	which	which	PRON
aiti-13523	150	9	is	be	AUX
aiti-13523	150	10	a	a	DET
aiti-13523	150	11	statistical	statistical	ADJ
aiti-13523	150	12	technique	technique	NOUN
aiti-13523	150	13	used	use	VERB
aiti-13523	150	14	in	in	ADP
aiti-13523	150	15	information	information	NOUN
aiti-13523	150	16	retrieval	retrieval	NOUN
aiti-13523	150	17	and	and	CCONJ
aiti-13523	150	18	data	datum	NOUN
aiti-13523	150	19	mining	mining	NOUN
aiti-13523	150	20	to	to	PART
aiti-13523	150	21	quantify	quantify	VERB
aiti-13523	150	22	words	word	NOUN
aiti-13523	150	23	in	in	ADP
aiti-13523	150	24	a	a	DET
aiti-13523	150	25	set	set	NOUN
aiti-13523	150	26	of	of	ADP
aiti-13523	150	27	documents	document	NOUN
aiti-13523	150	28	[	[	X
aiti-13523	150	29	25	25	NUM
aiti-13523	150	30	]	]	PUNCT
aiti-13523	150	31	.	.	PUNCT
aiti-13523	151	1	tf	tf	PROPN
aiti-13523	151	2	-	-	PUNCT
aiti-13523	151	3	idf	idf	PROPN
aiti-13523	151	4	is	be	AUX
aiti-13523	151	5	based	base	VERB
aiti-13523	151	6	on	on	ADP
aiti-13523	151	7	the	the	DET
aiti-13523	151	8	frequency	frequency	NOUN
aiti-13523	151	9	of	of	ADP
aiti-13523	151	10	words	word	NOUN
aiti-13523	151	11	in	in	ADP
aiti-13523	151	12	a	a	DET
aiti-13523	151	13	text	text	NOUN
aiti-13523	151	14	,	,	PUNCT
aiti-13523	151	15	as	as	SCONJ
aiti-13523	151	16	described	describe	VERB
aiti-13523	151	17	by	by	ADP
aiti-13523	151	18	the	the	DET
aiti-13523	151	19	zipf	zipf	PROPN
aiti-13523	151	20	law	law	NOUN
aiti-13523	152	1	[	[	X
aiti-13523	152	2	26	26	NUM
aiti-13523	152	3	]	]	PUNCT
aiti-13523	152	4	.	.	PUNCT
aiti-13523	153	1	tf	tf	PROPN
aiti-13523	153	2	measures	measure	VERB
aiti-13523	153	3	the	the	DET
aiti-13523	153	4	importance	importance	NOUN
aiti-13523	153	5	of	of	ADP
aiti-13523	153	6	a	a	DET
aiti-13523	153	7	term	term	NOUN
aiti-13523	153	8	in	in	ADP
aiti-13523	153	9	a	a	DET
aiti-13523	153	10	document	document	NOUN
aiti-13523	153	11	,	,	PUNCT
aiti-13523	153	12	while	while	SCONJ
aiti-13523	153	13	idf	idf	PROPN
aiti-13523	153	14	measures	measure	NOUN
aiti-13523	153	15	whether	whether	SCONJ
aiti-13523	153	16	the	the	DET
aiti-13523	153	17	term	term	NOUN
aiti-13523	153	18	is	be	AUX
aiti-13523	153	19	discriminative	discriminative	NOUN
aiti-13523	153	20	(	(	PUNCT
aiti-13523	153	21	i.e.	i.e.	X
aiti-13523	153	22	,	,	PUNCT
aiti-13523	153	23	not	not	PART
aiti-13523	153	24	widely	widely	ADV
aiti-13523	153	25	distributed	distribute	VERB
aiti-13523	153	26	)	)	PUNCT
aiti-13523	153	27	.	.	PUNCT
aiti-13523	154	1	therefore	therefore	ADV
aiti-13523	154	2	,	,	PUNCT
aiti-13523	154	3	a	a	DET
aiti-13523	154	4	term	term	NOUN
aiti-13523	154	5	with	with	ADP
aiti-13523	154	6	a	a	DET
aiti-13523	154	7	high	high	ADJ
aiti-13523	154	8	tf	tf	ADJ
aiti-13523	154	9	-	-	PUNCT
aiti-13523	154	10	idf	idf	NOUN
aiti-13523	154	11	value	value	NOUN
aiti-13523	154	12	should	should	AUX
aiti-13523	154	13	be	be	AUX
aiti-13523	154	14	prominent	prominent	ADJ
aiti-13523	154	15	in	in	ADP
aiti-13523	154	16	the	the	DET
aiti-13523	154	17	current	current	ADJ
aiti-13523	154	18	document	document	NOUN
aiti-13523	154	19	and	and	CCONJ
aiti-13523	154	20	also	also	ADV
aiti-13523	154	21	appear	appear	VERB
aiti-13523	154	22	rarely	rarely	ADV
aiti-13523	154	23	in	in	ADP
aiti-13523	154	24	other	other	ADJ
aiti-13523	154	25	documents	document	NOUN
aiti-13523	154	26	.	.	PUNCT
aiti-13523	155	1	the	the	DET
aiti-13523	155	2	last	last	ADJ
aiti-13523	155	3	model	model	NOUN
aiti-13523	155	4	tested	test	VERB
aiti-13523	155	5	is	be	AUX
aiti-13523	155	6	the	the	DET
aiti-13523	155	7	word2vec	word2vec	X
aiti-13523	155	8	[	[	X
aiti-13523	155	9	27	27	NUM
aiti-13523	155	10	]	]	X
aiti-13523	155	11	embedding	embed	VERB
aiti-13523	155	12	model	model	NOUN
aiti-13523	155	13	based	base	VERB
aiti-13523	155	14	on	on	ADP
aiti-13523	155	15	a	a	DET
aiti-13523	155	16	two	two	NUM
aiti-13523	155	17	-	-	PUNCT
aiti-13523	155	18	layer	layer	NOUN
aiti-13523	155	19	neural	neural	ADJ
aiti-13523	155	20	network	network	NOUN
aiti-13523	155	21	trained	train	VERB
aiti-13523	155	22	to	to	PART
aiti-13523	155	23	predict	predict	VERB
aiti-13523	155	24	the	the	DET
aiti-13523	155	25	vector	vector	NOUN
aiti-13523	155	26	representation	representation	NOUN
aiti-13523	155	27	of	of	ADP
aiti-13523	155	28	words	word	NOUN
aiti-13523	155	29	in	in	ADP
aiti-13523	155	30	context	context	NOUN
aiti-13523	155	31	.	.	PUNCT
aiti-13523	156	1	simply	simply	ADV
aiti-13523	156	2	put	put	VERB
aiti-13523	156	3	,	,	PUNCT
aiti-13523	156	4	word2vec	word2vec	PRON
aiti-13523	156	5	takes	take	VERB
aiti-13523	156	6	a	a	DET
aiti-13523	156	7	corpus	corpus	NOUN
aiti-13523	156	8	of	of	ADP
aiti-13523	156	9	text	text	NOUN
aiti-13523	156	10	as	as	ADP
aiti-13523	156	11	input	input	NOUN
aiti-13523	156	12	and	and	CCONJ
aiti-13523	156	13	generates	generate	VERB
aiti-13523	156	14	a	a	DET
aiti-13523	156	15	set	set	NOUN
aiti-13523	156	16	of	of	ADP
aiti-13523	156	17	vectors	vector	NOUN
aiti-13523	156	18	for	for	ADP
aiti-13523	156	19	the	the	DET
aiti-13523	156	20	words	word	NOUN
aiti-13523	156	21	in	in	ADP
aiti-13523	156	22	that	that	DET
aiti-13523	156	23	corpus	corpus	NOUN
aiti-13523	156	24	.	.	PUNCT
aiti-13523	157	1	its	its	PRON
aiti-13523	157	2	goal	goal	NOUN
aiti-13523	157	3	is	be	AUX
aiti-13523	157	4	to	to	ADP
aiti-13523	157	5	group	group	NOUN
aiti-13523	157	6	vectors	vector	NOUN
aiti-13523	157	7	of	of	ADP
aiti-13523	157	8	similar	similar	ADJ
aiti-13523	157	9	words	word	NOUN
aiti-13523	157	10	into	into	ADP
aiti-13523	157	11	a	a	DET
aiti-13523	157	12	vector	vector	NOUN
aiti-13523	157	13	space	space	NOUN
aiti-13523	157	14	.	.	PUNCT
aiti-13523	158	1	with	with	ADP
aiti-13523	158	2	enough	enough	ADJ
aiti-13523	158	3	data	datum	NOUN
aiti-13523	158	4	,	,	PUNCT
aiti-13523	158	5	usage	usage	NOUN
aiti-13523	158	6	,	,	PUNCT
aiti-13523	158	7	and	and	CCONJ
aiti-13523	158	8	context	context	NOUN
aiti-13523	158	9	,	,	PUNCT
aiti-13523	158	10	word2vec	word2vec	PRON
aiti-13523	158	11	can	can	AUX
aiti-13523	158	12	accurately	accurately	ADV
aiti-13523	158	13	guess	guess	VERB
aiti-13523	158	14	the	the	DET
aiti-13523	158	15	meaning	meaning	NOUN
aiti-13523	158	16	of	of	ADP
aiti-13523	158	17	a	a	DET
aiti-13523	158	18	word	word	NOUN
aiti-13523	158	19	based	base	VERB
aiti-13523	158	20	on	on	ADP
aiti-13523	158	21	its	its	PRON
aiti-13523	158	22	past	past	ADJ
aiti-13523	158	23	appearances	appearance	NOUN
aiti-13523	158	24	.	.	PUNCT
aiti-13523	159	1	they	they	PRON
aiti-13523	159	2	used	use	VERB
aiti-13523	159	3	the	the	DET
aiti-13523	159	4	google	google	PROPN
aiti-13523	159	5	learning	learning	NOUN
aiti-13523	159	6	model	model	NOUN
aiti-13523	159	7	available	available	ADJ
aiti-13523	159	8	online†	online†	ADJ
aiti-13523	159	9	,	,	PUNCT
aiti-13523	159	10	consisting	consist	VERB
aiti-13523	159	11	of	of	ADP
aiti-13523	159	12	300	300	NUM
aiti-13523	159	13	vector	vector	NOUN
aiti-13523	159	14	dimensions	dimension	NOUN
aiti-13523	159	15	for	for	ADP
aiti-13523	159	16	3	3	NUM
aiti-13523	159	17	million	million	NUM
aiti-13523	159	18	words	word	NOUN
aiti-13523	159	19	and	and	CCONJ
aiti-13523	159	20	sentences	sentence	NOUN
aiti-13523	159	21	,	,	PUNCT
aiti-13523	159	22	as	as	ADP
aiti-13523	159	23	a	a	DET
aiti-13523	159	24	training	training	NOUN
aiti-13523	159	25	basis	basis	NOUN
aiti-13523	159	26	.	.	PUNCT
aiti-13523	160	1	3.4	3.4	NUM
aiti-13523	160	2	.	.	PUNCT
aiti-13523	160	3	baseline	baseline	NOUN
aiti-13523	160	4	modeling	modeling	NOUN
aiti-13523	160	5	in	in	ADP
aiti-13523	160	6	this	this	DET
aiti-13523	160	7	step	step	NOUN
aiti-13523	160	8	,	,	PUNCT
aiti-13523	160	9	basic	basic	ADJ
aiti-13523	160	10	classification	classification	NOUN
aiti-13523	160	11	approaches	approach	NOUN
aiti-13523	160	12	—	—	PUNCT
aiti-13523	160	13	logistic	logistic	ADJ
aiti-13523	160	14	regression	regression	NOUN
aiti-13523	160	15	,	,	PUNCT
aiti-13523	160	16	nb	nb	INTJ
aiti-13523	160	17	,	,	PUNCT
aiti-13523	160	18	and	and	CCONJ
aiti-13523	160	19	lightgbm	lightgbm	ADJ
aiti-13523	160	20	,	,	PUNCT
aiti-13523	160	21	using	use	VERB
aiti-13523	160	22	different	different	ADJ
aiti-13523	160	23	feature	feature	NOUN
aiti-13523	160	24	selection	selection	NOUN
aiti-13523	160	25	models	model	NOUN
aiti-13523	160	26	(	(	PUNCT
aiti-13523	160	27	cbow	cbow	VERB
aiti-13523	160	28	,	,	PUNCT
aiti-13523	160	29	tf	tf	PROPN
aiti-13523	160	30	-	-	PUNCT
aiti-13523	160	31	idf	idf	PROPN
aiti-13523	160	32	,	,	PUNCT
aiti-13523	160	33	and	and	CCONJ
aiti-13523	160	34	word2vec	word2vec	NUM
aiti-13523	160	35	)	)	PUNCT
aiti-13523	160	36	.	.	PUNCT
aiti-13523	161	1	logistic	logistic	ADJ
aiti-13523	161	2	regression	regression	NOUN
aiti-13523	161	3	is	be	AUX
aiti-13523	161	4	a	a	DET
aiti-13523	161	5	statistical	statistical	ADJ
aiti-13523	161	6	approach	approach	NOUN
aiti-13523	161	7	used	use	VERB
aiti-13523	161	8	for	for	ADP
aiti-13523	161	9	classification	classification	NOUN
aiti-13523	161	10	problems	problem	NOUN
aiti-13523	161	11	when	when	SCONJ
aiti-13523	161	12	the	the	DET
aiti-13523	161	13	dependent	dependent	ADJ
aiti-13523	161	14	(	(	PUNCT
aiti-13523	161	15	target	target	NOUN
aiti-13523	161	16	)	)	PUNCT
aiti-13523	161	17	variable	variable	NOUN
aiti-13523	161	18	is	be	AUX
aiti-13523	161	19	categorical	categorical	ADJ
aiti-13523	161	20	.	.	PUNCT
aiti-13523	162	1	logistic	logistic	ADJ
aiti-13523	162	2	regression	regression	NOUN
aiti-13523	162	3	uses	use	VERB
aiti-13523	162	4	the	the	DET
aiti-13523	162	5	sigmoid	sigmoid	NOUN
aiti-13523	162	6	mathematical	mathematical	ADJ
aiti-13523	162	7	function	function	NOUN
aiti-13523	162	8	to	to	PART
aiti-13523	162	9	return	return	VERB
aiti-13523	162	10	the	the	DET
aiti-13523	162	11	probability	probability	NOUN
aiti-13523	162	12	of	of	ADP
aiti-13523	162	13	a	a	DET
aiti-13523	162	14	label	label	NOUN
aiti-13523	162	15	[	[	X
aiti-13523	162	16	28	28	NUM
aiti-13523	162	17	]	]	X
aiti-13523	162	18	:	:	PUNCT
aiti-13523	162	19	1	1	NUM
aiti-13523	162	20	(	(	PUNCT
aiti-13523	162	21	)	)	PUNCT
aiti-13523	162	22	1	1	NUM
aiti-13523	162	23	−	−	NOUN
aiti-13523	162	24	=	=	SYM
aiti-13523	163	1	+	+	NUM
aiti-13523	163	2	x	x	SYM
aiti-13523	163	3	sg	sg	PROPN
aiti-13523	163	4	x	x	SYM
aiti-13523	163	5	e	e	X
aiti-13523	163	6	(	(	PUNCT
aiti-13523	163	7	1	1	NUM
aiti-13523	163	8	)	)	PUNCT
aiti-13523	163	9	†	†	PROPN
aiti-13523	163	10	https://code.google.com/archive/p/	https://code.google.com/archive/p/	X
aiti-13523	163	11	word2vec	word2vec	X
aiti-13523	163	12	advances	advance	VERB
aiti-13523	163	13	in	in	ADP
aiti-13523	163	14	technology	technology	NOUN
aiti-13523	163	15	innovation	innovation	NOUN
aiti-13523	163	16	,	,	PUNCT
aiti-13523	163	17	vol	vol	NOUN
aiti-13523	163	18	.	.	PROPN
aiti-13523	164	1	9	9	NUM
aiti-13523	164	2	,	,	PUNCT
aiti-13523	164	3	no	no	INTJ
aiti-13523	164	4	.	.	NOUN
aiti-13523	164	5	2	2	NUM
aiti-13523	164	6	,	,	PUNCT
aiti-13523	164	7	2024	2024	NUM
aiti-13523	164	8	,	,	PUNCT
aiti-13523	164	9	pp	pp	ADJ
aiti-13523	164	10	.	.	PUNCT
aiti-13523	165	1	129	129	NUM
aiti-13523	165	2	-	-	SYM
aiti-13523	165	3	142	142	NUM
aiti-13523	165	4	135	135	NUM
aiti-13523	165	5	the	the	DET
aiti-13523	165	6	second	second	ADJ
aiti-13523	165	7	implemented	implement	VERB
aiti-13523	165	8	nb	nb	PROPN
aiti-13523	165	9	model	model	NOUN
aiti-13523	165	10	is	be	AUX
aiti-13523	165	11	a	a	DET
aiti-13523	165	12	probabilistic	probabilistic	ADJ
aiti-13523	165	13	machine	machine	NOUN
aiti-13523	165	14	learning	learning	NOUN
aiti-13523	165	15	model	model	NOUN
aiti-13523	165	16	used	use	VERB
aiti-13523	165	17	for	for	ADP
aiti-13523	165	18	classification	classification	NOUN
aiti-13523	165	19	tasks	task	NOUN
aiti-13523	165	20	.	.	PUNCT
aiti-13523	166	1	in	in	ADP
aiti-13523	166	2	this	this	DET
aiti-13523	166	3	case	case	NOUN
aiti-13523	166	4	.	.	PUNCT
aiti-13523	167	1	the	the	DET
aiti-13523	167	2	classifier	classifier	PROPN
aiti-13523	167	3	node	node	NOUN
aiti-13523	167	4	is	be	AUX
aiti-13523	167	5	based	base	VERB
aiti-13523	167	6	on	on	ADP
aiti-13523	167	7	bayes	bayes	PROPN
aiti-13523	167	8	theorem	theorem	VERB
aiti-13523	167	9	2	2	NUM
aiti-13523	167	10	:	:	PUNCT
aiti-13523	167	11	(	(	PUNCT
aiti-13523	167	12	/	/	SYM
aiti-13523	167	13	)	)	PUNCT
aiti-13523	167	14	(	(	PUNCT
aiti-13523	167	15	)	)	PUNCT
aiti-13523	167	16	(	(	PUNCT
aiti-13523	167	17	/	/	SYM
aiti-13523	167	18	)	)	PUNCT
aiti-13523	167	19	(	(	PUNCT
aiti-13523	167	20	)	)	PUNCT
aiti-13523	168	1	=	=	PUNCT
aiti-13523	168	2	p	p	NOUN
aiti-13523	168	3	b	b	PROPN
aiti-13523	168	4	a	a	DET
aiti-13523	168	5	p	p	X
aiti-13523	168	6	a	a	DET
aiti-13523	168	7	p	p	NOUN
aiti-13523	168	8	a	a	DET
aiti-13523	168	9	b	b	NOUN
aiti-13523	168	10	p	p	X
aiti-13523	168	11	b	b	PROPN
aiti-13523	168	12	(	(	PUNCT
aiti-13523	168	13	2	2	NUM
aiti-13523	168	14	)	)	PUNCT
aiti-13523	168	15	using	use	VERB
aiti-13523	168	16	this	this	DET
aiti-13523	168	17	theorem	theorem	NOUN
aiti-13523	168	18	,	,	PUNCT
aiti-13523	168	19	the	the	DET
aiti-13523	168	20	probability	probability	NOUN
aiti-13523	168	21	that	that	SCONJ
aiti-13523	168	22	a	a	PRON
aiti-13523	168	23	will	will	AUX
aiti-13523	168	24	occur	occur	VERB
aiti-13523	168	25	will	will	AUX
aiti-13523	168	26	be	be	AUX
aiti-13523	168	27	found	find	VERB
aiti-13523	168	28	,	,	PUNCT
aiti-13523	168	29	given	give	VERB
aiti-13523	168	30	that	that	SCONJ
aiti-13523	168	31	b	b	NOUN
aiti-13523	168	32	has	have	AUX
aiti-13523	168	33	occurred	occur	VERB
aiti-13523	168	34	(	(	PUNCT
aiti-13523	168	35	b	b	NOUN
aiti-13523	168	36	is	be	AUX
aiti-13523	168	37	the	the	DET
aiti-13523	168	38	evidence	evidence	NOUN
aiti-13523	168	39	and	and	CCONJ
aiti-13523	168	40	a	a	PRON
aiti-13523	168	41	is	be	AUX
aiti-13523	168	42	the	the	DET
aiti-13523	168	43	hypothesis	hypothesis	NOUN
aiti-13523	168	44	)	)	PUNCT
aiti-13523	169	1	[	[	X
aiti-13523	169	2	29	29	NUM
aiti-13523	169	3	]	]	PUNCT
aiti-13523	169	4	.	.	PUNCT
aiti-13523	170	1	the	the	DET
aiti-13523	170	2	last	last	ADJ
aiti-13523	170	3	implemented	implement	VERB
aiti-13523	170	4	model	model	NOUN
aiti-13523	170	5	is	be	AUX
aiti-13523	170	6	lightgbm	lightgbm	ADJ
aiti-13523	170	7	,	,	PUNCT
aiti-13523	170	8	it	it	PRON
aiti-13523	170	9	is	be	AUX
aiti-13523	170	10	a	a	DET
aiti-13523	170	11	decision	decision	NOUN
aiti-13523	170	12	tree	tree	NOUN
aiti-13523	170	13	-	-	PUNCT
aiti-13523	170	14	based	base	VERB
aiti-13523	170	15	optimization	optimization	NOUN
aiti-13523	170	16	ensemble	ensemble	ADJ
aiti-13523	170	17	method	method	NOUN
aiti-13523	170	18	used	use	VERB
aiti-13523	170	19	in	in	ADP
aiti-13523	170	20	classification	classification	NOUN
aiti-13523	170	21	and	and	CCONJ
aiti-13523	170	22	regression	regression	NOUN
aiti-13523	170	23	.	.	PUNCT
aiti-13523	171	1	this	this	DET
aiti-13523	171	2	model	model	NOUN
aiti-13523	171	3	creates	create	VERB
aiti-13523	171	4	leaf	leaf	NOUN
aiti-13523	171	5	-	-	PUNCT
aiti-13523	171	6	aware	aware	ADJ
aiti-13523	171	7	decision	decision	NOUN
aiti-13523	171	8	trees	tree	NOUN
aiti-13523	171	9	,	,	PUNCT
aiti-13523	171	10	such	such	ADJ
aiti-13523	171	11	that	that	SCONJ
aiti-13523	171	12	the	the	DET
aiti-13523	171	13	best	well	ADV
aiti-13523	171	14	-	-	PUNCT
aiti-13523	171	15	fit	fit	ADJ
aiti-13523	171	16	leaf	leaf	NOUN
aiti-13523	171	17	of	of	ADP
aiti-13523	171	18	the	the	DET
aiti-13523	171	19	tree	tree	NOUN
aiti-13523	171	20	will	will	AUX
aiti-13523	171	21	be	be	AUX
aiti-13523	171	22	split	split	VERB
aiti-13523	171	23	while	while	SCONJ
aiti-13523	171	24	further	far	ADV
aiti-13523	171	25	strengthening	strengthen	VERB
aiti-13523	171	26	calculations	calculation	NOUN
aiti-13523	171	27	split	split	VERB
aiti-13523	171	28	the	the	DET
aiti-13523	171	29	depth	depth	NOUN
aiti-13523	171	30	of	of	ADP
aiti-13523	171	31	the	the	DET
aiti-13523	171	32	tree	tree	NOUN
aiti-13523	171	33	into	into	ADP
aiti-13523	171	34	two	two	NUM
aiti-13523	171	35	parts	part	NOUN
aiti-13523	171	36	,	,	PUNCT
aiti-13523	171	37	one	one	NUM
aiti-13523	171	38	wise	wise	ADJ
aiti-13523	171	39	and	and	CCONJ
aiti-13523	171	40	the	the	DET
aiti-13523	171	41	other	other	ADJ
aiti-13523	171	42	insightful	insightful	ADJ
aiti-13523	171	43	,	,	PUNCT
aiti-13523	171	44	as	as	SCONJ
aiti-13523	171	45	opposed	oppose	VERB
aiti-13523	171	46	to	to	ADP
aiti-13523	171	47	leaves	leave	NOUN
aiti-13523	171	48	[	[	X
aiti-13523	171	49	30	30	NUM
aiti-13523	171	50	]	]	PUNCT
aiti-13523	171	51	.	.	PUNCT
aiti-13523	172	1	3.5	3.5	NUM
aiti-13523	172	2	.	.	PUNCT
aiti-13523	173	1	recurrent	recurrent	ADJ
aiti-13523	173	2	neural	neural	ADJ
aiti-13523	173	3	networks	network	NOUN
aiti-13523	173	4	given	give	VERB
aiti-13523	173	5	the	the	DET
aiti-13523	173	6	impressive	impressive	ADJ
aiti-13523	173	7	results	result	NOUN
aiti-13523	173	8	of	of	ADP
aiti-13523	173	9	deep	deep	ADJ
aiti-13523	173	10	learning	learning	NOUN
aiti-13523	173	11	algorithms	algorithm	NOUN
aiti-13523	173	12	,	,	PUNCT
aiti-13523	173	13	particularly	particularly	ADV
aiti-13523	173	14	in	in	ADP
aiti-13523	173	15	the	the	DET
aiti-13523	173	16	analysis	analysis	NOUN
aiti-13523	173	17	of	of	ADP
aiti-13523	173	18	textual	textual	ADJ
aiti-13523	173	19	data	datum	NOUN
aiti-13523	173	20	[	[	X
aiti-13523	173	21	11	11	NUM
aiti-13523	173	22	-	-	SYM
aiti-13523	173	23	13	13	NUM
aiti-13523	173	24	]	]	PUNCT
aiti-13523	173	25	,	,	PUNCT
aiti-13523	173	26	an	an	DET
aiti-13523	173	27	exploration	exploration	NOUN
aiti-13523	173	28	of	of	ADP
aiti-13523	173	29	their	their	PRON
aiti-13523	173	30	scope	scope	NOUN
aiti-13523	173	31	on	on	ADP
aiti-13523	173	32	the	the	DET
aiti-13523	173	33	emohd	emohd	NOUN
aiti-13523	173	34	dataset	dataset	NOUN
aiti-13523	173	35	,	,	PUNCT
aiti-13523	173	36	so	so	CCONJ
aiti-13523	173	37	two	two	NUM
aiti-13523	173	38	types	type	NOUN
aiti-13523	173	39	of	of	ADP
aiti-13523	173	40	recurrent	recurrent	ADJ
aiti-13523	173	41	neural	neural	ADJ
aiti-13523	173	42	networks	network	NOUN
aiti-13523	173	43	(	(	PUNCT
aiti-13523	173	44	rnn	rnn	PROPN
aiti-13523	173	45	)	)	PUNCT
aiti-13523	173	46	are	be	AUX
aiti-13523	173	47	implemented	implement	VERB
aiti-13523	173	48	:	:	PUNCT
aiti-13523	173	49	lstm	lstm	NOUN
aiti-13523	173	50	and	and	CCONJ
aiti-13523	173	51	the	the	DET
aiti-13523	173	52	bert	bert	NOUN
aiti-13523	173	53	,	,	PUNCT
aiti-13523	173	54	and	and	CCONJ
aiti-13523	173	55	compared	compare	VERB
aiti-13523	173	56	them	they	PRON
aiti-13523	173	57	to	to	ADP
aiti-13523	173	58	the	the	DET
aiti-13523	173	59	learning	learning	NOUN
aiti-13523	173	60	algorithms	algorithm	NOUN
aiti-13523	173	61	implemented	implement	VERB
aiti-13523	173	62	previously	previously	ADV
aiti-13523	173	63	based	base	VERB
aiti-13523	173	64	on	on	ADP
aiti-13523	173	65	their	their	PRON
aiti-13523	173	66	classification	classification	NOUN
aiti-13523	173	67	performance	performance	NOUN
aiti-13523	173	68	.	.	PUNCT
aiti-13523	174	1	3.5.1	3.5.1	NUM
aiti-13523	174	2	.	.	PUNCT
aiti-13523	174	3	long	long	ADJ
aiti-13523	174	4	short	short	ADJ
aiti-13523	174	5	-	-	PUNCT
aiti-13523	174	6	term	term	NOUN
aiti-13523	174	7	memory	memory	NOUN
aiti-13523	174	8	(	(	PUNCT
aiti-13523	174	9	lstm	lstm	NOUN
aiti-13523	174	10	)	)	PUNCT
aiti-13523	174	11	lstm	lstm	NOUN
aiti-13523	174	12	is	be	AUX
aiti-13523	174	13	a	a	DET
aiti-13523	174	14	variant	variant	NOUN
aiti-13523	174	15	of	of	ADP
aiti-13523	174	16	rnn	rnn	NOUN
aiti-13523	174	17	,	,	PUNCT
aiti-13523	174	18	designed	design	VERB
aiti-13523	174	19	to	to	PART
aiti-13523	174	20	handle	handle	VERB
aiti-13523	174	21	time	time	NOUN
aiti-13523	174	22	series	series	PROPN
aiti-13523	174	23	data	datum	NOUN
aiti-13523	174	24	or	or	CCONJ
aiti-13523	174	25	sequences	sequence	NOUN
aiti-13523	174	26	.	.	PUNCT
aiti-13523	175	1	what	what	PRON
aiti-13523	175	2	sets	set	VERB
aiti-13523	175	3	lstms	lstms	ADJ
aiti-13523	175	4	apart	apart	ADV
aiti-13523	175	5	is	be	AUX
aiti-13523	175	6	their	their	PRON
aiti-13523	175	7	ability	ability	NOUN
aiti-13523	175	8	to	to	PART
aiti-13523	175	9	handle	handle	VERB
aiti-13523	175	10	inputs	input	NOUN
aiti-13523	175	11	of	of	ADP
aiti-13523	175	12	different	different	ADJ
aiti-13523	175	13	lengths	length	NOUN
aiti-13523	175	14	,	,	PUNCT
aiti-13523	175	15	thanks	thank	NOUN
aiti-13523	175	16	to	to	ADP
aiti-13523	175	17	their	their	PRON
aiti-13523	175	18	short	short	ADJ
aiti-13523	175	19	-	-	PUNCT
aiti-13523	175	20	term	term	NOUN
aiti-13523	175	21	memory	memory	NOUN
aiti-13523	175	22	capabilities	capability	NOUN
aiti-13523	175	23	.	.	PUNCT
aiti-13523	176	1	additionally	additionally	ADV
aiti-13523	176	2	,	,	PUNCT
aiti-13523	176	3	lstms	lstms	NOUN
aiti-13523	176	4	are	be	AUX
aiti-13523	176	5	excellent	excellent	ADJ
aiti-13523	176	6	at	at	ADP
aiti-13523	176	7	understanding	understand	VERB
aiti-13523	176	8	context	context	NOUN
aiti-13523	176	9	because	because	SCONJ
aiti-13523	176	10	they	they	PRON
aiti-13523	176	11	can	can	AUX
aiti-13523	176	12	process	process	VERB
aiti-13523	176	13	data	datum	NOUN
aiti-13523	176	14	packets	packet	NOUN
aiti-13523	176	15	almost	almost	ADV
aiti-13523	176	16	simultaneously	simultaneously	ADV
aiti-13523	176	17	.	.	PUNCT
aiti-13523	177	1	in	in	ADP
aiti-13523	177	2	this	this	DET
aiti-13523	177	3	approach	approach	NOUN
aiti-13523	177	4	,	,	PUNCT
aiti-13523	177	5	it	it	PRON
aiti-13523	177	6	implemented	implement	VERB
aiti-13523	177	7	a	a	DET
aiti-13523	177	8	sequential	sequential	ADJ
aiti-13523	177	9	lstm	lstm	ADJ
aiti-13523	177	10	model	model	NOUN
aiti-13523	177	11	to	to	PART
aiti-13523	177	12	solve	solve	VERB
aiti-13523	177	13	a	a	DET
aiti-13523	177	14	predictive	predictive	ADJ
aiti-13523	177	15	modeling	modeling	NOUN
aiti-13523	177	16	problem	problem	NOUN
aiti-13523	177	17	where	where	SCONJ
aiti-13523	177	18	it	it	PRON
aiti-13523	177	19	needed	need	VERB
aiti-13523	177	20	to	to	PART
aiti-13523	177	21	predict	predict	VERB
aiti-13523	177	22	a	a	DET
aiti-13523	177	23	category	category	NOUN
aiti-13523	177	24	for	for	ADP
aiti-13523	177	25	an	an	DET
aiti-13523	177	26	input	input	NOUN
aiti-13523	177	27	sequence	sequence	NOUN
aiti-13523	177	28	.	.	PUNCT
aiti-13523	178	1	the	the	DET
aiti-13523	178	2	implemented	implement	VERB
aiti-13523	178	3	lstm	lstm	NOUN
aiti-13523	178	4	model	model	NOUN
aiti-13523	178	5	consists	consist	VERB
aiti-13523	178	6	of	of	ADP
aiti-13523	178	7	four	four	NUM
aiti-13523	178	8	layers	layer	NOUN
aiti-13523	178	9	presented	present	VERB
aiti-13523	178	10	in	in	ADP
aiti-13523	178	11	fig	fig	NOUN
aiti-13523	178	12	.	.	PUNCT
aiti-13523	179	1	3	3	X
aiti-13523	179	2	.	.	X
aiti-13523	179	3	fig	fig	NOUN
aiti-13523	179	4	.	.	PUNCT
aiti-13523	180	1	3	3	NUM
aiti-13523	180	2	lstm	lstm	NOUN
aiti-13523	180	3	and	and	CCONJ
aiti-13523	180	4	bert	bert	PROPN
aiti-13523	180	5	model	model	NOUN
aiti-13523	180	6	architecture	architecture	NOUN
aiti-13523	180	7	the	the	DET
aiti-13523	180	8	input	input	NOUN
aiti-13523	180	9	layer	layer	NOUN
aiti-13523	180	10	(	(	PUNCT
aiti-13523	180	11	integration	integration	NOUN
aiti-13523	180	12	layer	layer	NOUN
aiti-13523	180	13	)	)	PUNCT
aiti-13523	180	14	consists	consist	VERB
aiti-13523	180	15	of	of	ADP
aiti-13523	180	16	128	128	NUM
aiti-13523	180	17	lstm	lstm	ADJ
aiti-13523	180	18	units	unit	NOUN
aiti-13523	180	19	which	which	PRON
aiti-13523	180	20	map	map	VERB
aiti-13523	180	21	the	the	DET
aiti-13523	180	22	words	word	NOUN
aiti-13523	180	23	of	of	ADP
aiti-13523	180	24	the	the	DET
aiti-13523	180	25	text	text	NOUN
aiti-13523	180	26	into	into	ADP
aiti-13523	180	27	real	real	ADV
aiti-13523	180	28	-	-	PUNCT
aiti-13523	180	29	valued	value	VERB
aiti-13523	180	30	vectors	vector	NOUN
aiti-13523	180	31	.	.	PUNCT
aiti-13523	181	1	this	this	DET
aiti-13523	181	2	layer	layer	NOUN
aiti-13523	181	3	takes	take	VERB
aiti-13523	181	4	as	as	ADP
aiti-13523	181	5	input	input	NOUN
aiti-13523	181	6	three	three	NUM
aiti-13523	181	7	entities	entity	NOUN
aiti-13523	181	8	,	,	PUNCT
aiti-13523	181	9	including	include	VERB
aiti-13523	181	10	:	:	PUNCT
aiti-13523	181	11	the	the	DET
aiti-13523	181	12	vocabulary	vocabulary	ADJ
aiti-13523	181	13	size	size	NOUN
aiti-13523	181	14	dimension	dimension	NOUN
aiti-13523	181	15	of	of	ADP
aiti-13523	181	16	each	each	DET
aiti-13523	181	17	embedded	embed	VERB
aiti-13523	181	18	word	word	NOUN
aiti-13523	181	19	(	(	PUNCT
aiti-13523	181	20	input	input	NOUN
aiti-13523	181	21	dimension	dimension	NOUN
aiti-13523	181	22	)	)	PUNCT
aiti-13523	181	23	,	,	PUNCT
aiti-13523	181	24	the	the	DET
aiti-13523	181	25	maximum	maximum	ADJ
aiti-13523	181	26	number	number	NOUN
aiti-13523	181	27	of	of	ADP
aiti-13523	181	28	words	word	NOUN
aiti-13523	181	29	in	in	ADP
aiti-13523	181	30	the	the	DET
aiti-13523	181	31	vocabulary	vocabulary	NOUN
aiti-13523	181	32	(	(	PUNCT
aiti-13523	181	33	maximum	maximum	ADJ
aiti-13523	181	34	feature	feature	NOUN
aiti-13523	181	35	)	)	PUNCT
aiti-13523	181	36	,	,	PUNCT
aiti-13523	181	37	and	and	CCONJ
aiti-13523	181	38	the	the	DET
aiti-13523	181	39	maximum	maximum	ADJ
aiti-13523	181	40	length	length	NOUN
aiti-13523	181	41	of	of	ADP
aiti-13523	181	42	a	a	DET
aiti-13523	181	43	sequence	sequence	NOUN
aiti-13523	181	44	(	(	PUNCT
aiti-13523	181	45	input	input	NOUN
aiti-13523	181	46	length	length	NOUN
aiti-13523	181	47	)	)	PUNCT
aiti-13523	181	48	.	.	PUNCT
aiti-13523	182	1	the	the	DET
aiti-13523	182	2	second	second	ADJ
aiti-13523	182	3	layer	layer	NOUN
aiti-13523	182	4	is	be	AUX
aiti-13523	182	5	the	the	DET
aiti-13523	182	6	dropout	dropout	NOUN
aiti-13523	182	7	layer	layer	NOUN
aiti-13523	182	8	:	:	PUNCT
aiti-13523	182	9	initialized	initialize	VERB
aiti-13523	182	10	this	this	DET
aiti-13523	182	11	layer	layer	NOUN
aiti-13523	182	12	with	with	ADP
aiti-13523	182	13	a	a	DET
aiti-13523	182	14	rate	rate	NOUN
aiti-13523	182	15	of	of	ADP
aiti-13523	182	16	40	40	NUM
aiti-13523	182	17	%	%	NOUN
aiti-13523	182	18	to	to	PART
aiti-13523	182	19	reduce	reduce	VERB
aiti-13523	182	20	overfitting	overfitting	NOUN
aiti-13523	182	21	when	when	SCONJ
aiti-13523	182	22	training	train	VERB
aiti-13523	182	23	the	the	DET
aiti-13523	182	24	model	model	NOUN
aiti-13523	182	25	.	.	PUNCT
aiti-13523	183	1	this	this	PRON
aiti-13523	183	2	will	will	AUX
aiti-13523	183	3	apply	apply	VERB
aiti-13523	183	4	random	random	ADJ
aiti-13523	183	5	deactivation	deactivation	NOUN
aiti-13523	183	6	in	in	ADP
aiti-13523	183	7	each	each	DET
aiti-13523	183	8	epoch	epoch	NOUN
aiti-13523	183	9	,	,	PUNCT
aiti-13523	183	10	meaning	mean	VERB
aiti-13523	183	11	that	that	SCONJ
aiti-13523	183	12	on	on	ADP
aiti-13523	183	13	each	each	DET
aiti-13523	183	14	pass	pass	NOUN
aiti-13523	183	15	(	(	PUNCT
aiti-13523	183	16	forward	forward	ADJ
aiti-13523	183	17	propagation	propagation	NOUN
aiti-13523	183	18	)	)	PUNCT
aiti-13523	183	19	,	,	PUNCT
aiti-13523	183	20	the	the	DET
aiti-13523	183	21	model	model	NOUN
aiti-13523	183	22	learns	learn	VERB
aiti-13523	183	23	with	with	ADP
aiti-13523	183	24	a	a	DET
aiti-13523	183	25	configuration	configuration	NOUN
aiti-13523	183	26	of	of	ADP
aiti-13523	183	27	different	different	ADJ
aiti-13523	183	28	neurons	neuron	NOUN
aiti-13523	183	29	activating	activate	VERB
aiti-13523	183	30	and	and	CCONJ
aiti-13523	183	31	deactivating	deactivate	VERB
aiti-13523	183	32	randomly	randomly	ADV
aiti-13523	183	33	(	(	PUNCT
aiti-13523	183	34	40	40	NUM
aiti-13523	183	35	%	%	NOUN
aiti-13523	183	36	)	)	PUNCT
aiti-13523	183	37	.	.	PUNCT
aiti-13523	184	1	the	the	DET
aiti-13523	184	2	third	third	ADJ
aiti-13523	184	3	layer	layer	NOUN
aiti-13523	184	4	(	(	PUNCT
aiti-13523	184	5	lstm	lstm	ADJ
aiti-13523	184	6	layer	layer	NOUN
aiti-13523	184	7	)	)	PUNCT
aiti-13523	184	8	contains	contain	VERB
aiti-13523	184	9	192	192	NUM
aiti-13523	184	10	memory	memory	NOUN
aiti-13523	184	11	units	unit	NOUN
aiti-13523	184	12	(	(	PUNCT
aiti-13523	184	13	intelligent	intelligent	ADJ
aiti-13523	184	14	neurons	neuron	NOUN
aiti-13523	184	15	)	)	PUNCT
aiti-13523	184	16	to	to	PART
aiti-13523	184	17	optimize	optimize	VERB
aiti-13523	184	18	the	the	DET
aiti-13523	184	19	performance	performance	NOUN
aiti-13523	184	20	of	of	ADP
aiti-13523	184	21	the	the	DET
aiti-13523	184	22	model	model	NOUN
aiti-13523	184	23	,	,	PUNCT
aiti-13523	184	24	this	this	DET
aiti-13523	184	25	layer	layer	NOUN
aiti-13523	184	26	is	be	AUX
aiti-13523	184	27	configured	configure	VERB
aiti-13523	184	28	with	with	ADP
aiti-13523	184	29	dropout	dropout	NOUN
aiti-13523	184	30	which	which	PRON
aiti-13523	184	31	has	have	AUX
aiti-13523	184	32	been	be	AUX
aiti-13523	184	33	set	set	VERB
aiti-13523	184	34	at	at	ADP
aiti-13523	184	35	40	40	NUM
aiti-13523	184	36	%	%	NOUN
aiti-13523	184	37	,	,	PUNCT
aiti-13523	184	38	and	and	CCONJ
aiti-13523	184	39	recurrent	recurrent	ADJ
aiti-13523	184	40	dropout	dropout	NOUN
aiti-13523	184	41	which	which	PRON
aiti-13523	184	42	concerns	concern	VERB
aiti-13523	184	43	the	the	DET
aiti-13523	184	44	suppression	suppression	NOUN
aiti-13523	184	45	applied	apply	VERB
aiti-13523	184	46	to	to	ADP
aiti-13523	184	47	the	the	DET
aiti-13523	184	48	recurring	recur	VERB
aiti-13523	184	49	input	input	NOUN
aiti-13523	184	50	signal	signal	NOUN
aiti-13523	184	51	on	on	ADP
aiti-13523	184	52	lstm	lstm	ADJ
aiti-13523	184	53	units	unit	NOUN
aiti-13523	184	54	is	be	AUX
aiti-13523	184	55	set	set	VERB
aiti-13523	184	56	at	at	ADP
aiti-13523	184	57	20	20	NUM
aiti-13523	184	58	%	%	NOUN
aiti-13523	184	59	.	.	PUNCT
aiti-13523	185	1	the	the	DET
aiti-13523	185	2	output	output	NOUN
aiti-13523	185	3	layer	layer	NOUN
aiti-13523	185	4	(	(	PUNCT
aiti-13523	185	5	dense	dense	ADJ
aiti-13523	185	6	layer	layer	NOUN
aiti-13523	185	7	)	)	PUNCT
aiti-13523	185	8	implements	implement	VERB
aiti-13523	185	9	the	the	DET
aiti-13523	185	10	activation	activation	NOUN
aiti-13523	185	11	function	function	NOUN
aiti-13523	185	12	.	.	PUNCT
aiti-13523	186	1	in	in	ADP
aiti-13523	186	2	this	this	DET
aiti-13523	186	3	case	case	NOUN
aiti-13523	186	4	,	,	PUNCT
aiti-13523	186	5	a	a	DET
aiti-13523	186	6	softmax	softmax	NOUN
aiti-13523	186	7	function	function	NOUN
aiti-13523	186	8	is	be	AUX
aiti-13523	186	9	used	use	VERB
aiti-13523	186	10	since	since	SCONJ
aiti-13523	186	11	the	the	DET
aiti-13523	186	12	model	model	NOUN
aiti-13523	186	13	has	have	VERB
aiti-13523	186	14	6	6	NUM
aiti-13523	186	15	output	output	NOUN
aiti-13523	186	16	classes	class	NOUN
aiti-13523	186	17	this	this	DET
aiti-13523	186	18	number	number	NOUN
aiti-13523	186	19	is	be	AUX
aiti-13523	186	20	reduced	reduce	VERB
aiti-13523	186	21	to	to	ADP
aiti-13523	186	22	4	4	NUM
aiti-13523	186	23	after	after	ADP
aiti-13523	186	24	removing	remove	VERB
aiti-13523	186	25	the	the	DET
aiti-13523	186	26	minority	minority	NOUN
aiti-13523	186	27	classes	class	NOUN
aiti-13523	186	28	.	.	PUNCT
aiti-13523	187	1	136	136	NUM
aiti-13523	187	2	advances	advance	NOUN
aiti-13523	187	3	in	in	ADP
aiti-13523	187	4	technology	technology	NOUN
aiti-13523	187	5	innovation	innovation	NOUN
aiti-13523	187	6	,	,	PUNCT
aiti-13523	187	7	vol	vol	NOUN
aiti-13523	187	8	.	.	PROPN
aiti-13523	187	9	9	9	NUM
aiti-13523	187	10	,	,	PUNCT
aiti-13523	187	11	no	no	INTJ
aiti-13523	187	12	.	.	NOUN
aiti-13523	187	13	2	2	NUM
aiti-13523	187	14	,	,	PUNCT
aiti-13523	187	15	2024	2024	NUM
aiti-13523	187	16	,	,	PUNCT
aiti-13523	187	17	pp	pp	ADJ
aiti-13523	187	18	.	.	PUNCT
aiti-13523	188	1	129	129	NUM
aiti-13523	188	2	-	-	SYM
aiti-13523	188	3	142	142	NUM
aiti-13523	188	4	during	during	ADP
aiti-13523	188	5	the	the	DET
aiti-13523	188	6	model	model	NOUN
aiti-13523	188	7	compilation	compilation	NOUN
aiti-13523	188	8	phase	phase	NOUN
aiti-13523	188	9	:	:	PUNCT
aiti-13523	188	10	the	the	DET
aiti-13523	188	11	lstm	lstm	PROPN
aiti-13523	188	12	model	model	NOUN
aiti-13523	188	13	is	be	AUX
aiti-13523	188	14	configured	configure	VERB
aiti-13523	188	15	with	with	ADP
aiti-13523	188	16	a	a	DET
aiti-13523	188	17	categorical_crossentropy	categorical_crossentropy	NOUN
aiti-13523	188	18	loss	loss	NOUN
aiti-13523	188	19	function	function	NOUN
aiti-13523	188	20	(	(	PUNCT
aiti-13523	188	21	which	which	PRON
aiti-13523	188	22	measures	measure	VERB
aiti-13523	188	23	the	the	DET
aiti-13523	188	24	dissimilarity	dissimilarity	NOUN
aiti-13523	188	25	between	between	ADP
aiti-13523	188	26	the	the	DET
aiti-13523	188	27	predicted	predict	VERB
aiti-13523	188	28	probabilities	probability	NOUN
aiti-13523	188	29	and	and	CCONJ
aiti-13523	188	30	the	the	DET
aiti-13523	188	31	true	true	ADJ
aiti-13523	188	32	categorical	categorical	ADJ
aiti-13523	188	33	labels	label	NOUN
aiti-13523	188	34	guiding	guide	VERB
aiti-13523	188	35	the	the	DET
aiti-13523	188	36	model	model	NOUN
aiti-13523	188	37	to	to	PART
aiti-13523	188	38	minimize	minimize	VERB
aiti-13523	188	39	the	the	DET
aiti-13523	188	40	difference	difference	NOUN
aiti-13523	188	41	between	between	ADP
aiti-13523	188	42	them	they	PRON
aiti-13523	188	43	)	)	PUNCT
aiti-13523	188	44	and	and	CCONJ
aiti-13523	188	45	the	the	DET
aiti-13523	188	46	adam	adam	PROPN
aiti-13523	188	47	optimizer	optimizer	NOUN
aiti-13523	188	48	which	which	PRON
aiti-13523	188	49	improves	improve	VERB
aiti-13523	188	50	the	the	DET
aiti-13523	188	51	training	training	NOUN
aiti-13523	188	52	process	process	NOUN
aiti-13523	188	53	by	by	ADP
aiti-13523	188	54	adapting	adapt	VERB
aiti-13523	188	55	the	the	DET
aiti-13523	188	56	pace	pace	NOUN
aiti-13523	188	57	of	of	ADP
aiti-13523	188	58	learning	learn	VERB
aiti-13523	188	59	.	.	PUNCT
aiti-13523	189	1	the	the	DET
aiti-13523	189	2	training	training	NOUN
aiti-13523	189	3	set	set	NOUN
aiti-13523	189	4	was	be	AUX
aiti-13523	189	5	trained	train	VERB
aiti-13523	189	6	for	for	ADP
aiti-13523	189	7	200	200	NUM
aiti-13523	189	8	epochs	epoch	NOUN
aiti-13523	189	9	which	which	PRON
aiti-13523	189	10	represents	represent	VERB
aiti-13523	189	11	the	the	DET
aiti-13523	189	12	number	number	NOUN
aiti-13523	189	13	of	of	ADP
aiti-13523	189	14	times	time	NOUN
aiti-13523	189	15	the	the	DET
aiti-13523	189	16	model	model	NOUN
aiti-13523	189	17	goes	go	VERB
aiti-13523	189	18	through	through	ADP
aiti-13523	189	19	the	the	DET
aiti-13523	189	20	data	datum	NOUN
aiti-13523	189	21	set	set	VERB
aiti-13523	189	22	provided	provide	VERB
aiti-13523	189	23	for	for	ADP
aiti-13523	189	24	training	training	NOUN
aiti-13523	189	25	.	.	PUNCT
aiti-13523	190	1	this	this	DET
aiti-13523	190	2	number	number	NOUN
aiti-13523	190	3	of	of	ADP
aiti-13523	190	4	iterations	iteration	NOUN
aiti-13523	190	5	seemed	seem	VERB
aiti-13523	190	6	correct	correct	ADJ
aiti-13523	190	7	to	to	ADP
aiti-13523	190	8	us	we	PRON
aiti-13523	190	9	after	after	SCONJ
aiti-13523	190	10	several	several	ADJ
aiti-13523	190	11	tests	test	NOUN
aiti-13523	190	12	to	to	PART
aiti-13523	190	13	give	give	VERB
aiti-13523	190	14	the	the	DET
aiti-13523	190	15	model	model	NOUN
aiti-13523	190	16	the	the	DET
aiti-13523	190	17	possibility	possibility	NOUN
aiti-13523	190	18	of	of	ADP
aiti-13523	190	19	analyzing	analyze	VERB
aiti-13523	190	20	the	the	DET
aiti-13523	190	21	data	datum	NOUN
aiti-13523	190	22	several	several	ADJ
aiti-13523	190	23	times	time	NOUN
aiti-13523	190	24	and	and	CCONJ
aiti-13523	190	25	extracting	extract	VERB
aiti-13523	190	26	the	the	DET
aiti-13523	190	27	relationships	relationship	NOUN
aiti-13523	190	28	and	and	CCONJ
aiti-13523	190	29	complex	complex	ADJ
aiti-13523	190	30	variations	variation	NOUN
aiti-13523	190	31	present	present	ADJ
aiti-13523	190	32	in	in	ADP
aiti-13523	190	33	the	the	DET
aiti-13523	190	34	data	datum	NOUN
aiti-13523	190	35	set	set	VERB
aiti-13523	190	36	to	to	PART
aiti-13523	190	37	draw	draw	VERB
aiti-13523	190	38	lessons	lesson	NOUN
aiti-13523	190	39	from	from	ADP
aiti-13523	190	40	it	it	PRON
aiti-13523	190	41	.	.	PUNCT
aiti-13523	191	1	the	the	DET
aiti-13523	191	2	batch	batch	NOUN
aiti-13523	191	3	size	size	NOUN
aiti-13523	191	4	which	which	PRON
aiti-13523	191	5	determines	determine	VERB
aiti-13523	191	6	the	the	DET
aiti-13523	191	7	number	number	NOUN
aiti-13523	191	8	of	of	ADP
aiti-13523	191	9	samples	sample	NOUN
aiti-13523	191	10	that	that	PRON
aiti-13523	191	11	will	will	AUX
aiti-13523	191	12	be	be	AUX
aiti-13523	191	13	fed	feed	VERB
aiti-13523	191	14	into	into	ADP
aiti-13523	191	15	the	the	DET
aiti-13523	191	16	model	model	NOUN
aiti-13523	191	17	in	in	ADP
aiti-13523	191	18	each	each	DET
aiti-13523	191	19	iteration	iteration	NOUN
aiti-13523	191	20	,	,	PUNCT
aiti-13523	191	21	and	and	CCONJ
aiti-13523	191	22	which	which	PRON
aiti-13523	191	23	will	will	AUX
aiti-13523	191	24	allow	allow	VERB
aiti-13523	191	25	it	it	PRON
aiti-13523	191	26	to	to	PART
aiti-13523	191	27	calculate	calculate	VERB
aiti-13523	191	28	the	the	DET
aiti-13523	191	29	loss	loss	NOUN
aiti-13523	191	30	and	and	CCONJ
aiti-13523	191	31	update	update	VERB
aiti-13523	191	32	its	its	PRON
aiti-13523	191	33	weights	weight	NOUN
aiti-13523	191	34	accordingly	accordingly	ADV
aiti-13523	191	35	has	have	AUX
aiti-13523	191	36	been	be	AUX
aiti-13523	191	37	divided	divide	VERB
aiti-13523	191	38	into	into	ADP
aiti-13523	191	39	64	64	NUM
aiti-13523	191	40	batches	batch	NOUN
aiti-13523	191	41	.	.	PUNCT
aiti-13523	192	1	3.5.2	3.5.2	X
aiti-13523	192	2	.	.	PUNCT
aiti-13523	192	3	bidirectional	bidirectional	ADJ
aiti-13523	192	4	encoder	encoder	NOUN
aiti-13523	192	5	representations	representation	VERB
aiti-13523	192	6	from	from	ADP
aiti-13523	192	7	transformers	transformer	NOUN
aiti-13523	192	8	(	(	PUNCT
aiti-13523	192	9	bert	bert	PROPN
aiti-13523	192	10	)	)	PUNCT
aiti-13523	192	11	bert	bert	PROPN
aiti-13523	192	12	is	be	AUX
aiti-13523	192	13	a	a	DET
aiti-13523	192	14	text	text	NOUN
aiti-13523	192	15	representation	representation	NOUN
aiti-13523	192	16	model	model	NOUN
aiti-13523	192	17	developed	develop	VERB
aiti-13523	192	18	by	by	ADP
aiti-13523	192	19	google	google	PROPN
aiti-13523	192	20	that	that	PRON
aiti-13523	192	21	is	be	AUX
aiti-13523	192	22	context	context	NOUN
aiti-13523	192	23	-	-	PUNCT
aiti-13523	192	24	aware	aware	ADJ
aiti-13523	192	25	,	,	PUNCT
aiti-13523	192	26	meaning	mean	VERB
aiti-13523	192	27	that	that	SCONJ
aiti-13523	192	28	a	a	DET
aiti-13523	192	29	word	word	NOUN
aiti-13523	192	30	is	be	AUX
aiti-13523	192	31	represented	represent	VERB
aiti-13523	192	32	based	base	VERB
aiti-13523	192	33	on	on	ADP
aiti-13523	192	34	its	its	PRON
aiti-13523	192	35	context	context	NOUN
aiti-13523	192	36	in	in	ADP
aiti-13523	192	37	the	the	DET
aiti-13523	192	38	text	text	NOUN
aiti-13523	192	39	.	.	PUNCT
aiti-13523	193	1	additionally	additionally	ADV
aiti-13523	193	2	,	,	PUNCT
aiti-13523	193	3	bert	bert	PROPN
aiti-13523	193	4	’s	’s	PART
aiti-13523	193	5	context	context	NOUN
aiti-13523	193	6	is	be	AUX
aiti-13523	193	7	bidirectional	bidirectional	ADJ
aiti-13523	193	8	,	,	PUNCT
aiti-13523	193	9	meaning	mean	VERB
aiti-13523	193	10	that	that	SCONJ
aiti-13523	193	11	the	the	DET
aiti-13523	193	12	representation	representation	NOUN
aiti-13523	193	13	of	of	ADP
aiti-13523	193	14	a	a	DET
aiti-13523	193	15	word	word	NOUN
aiti-13523	193	16	takes	take	VERB
aiti-13523	193	17	into	into	ADP
aiti-13523	193	18	account	account	NOUN
aiti-13523	193	19	not	not	PART
aiti-13523	193	20	only	only	ADV
aiti-13523	193	21	the	the	DET
aiti-13523	193	22	words	word	NOUN
aiti-13523	193	23	preceding	precede	VERB
aiti-13523	193	24	it	it	PRON
aiti-13523	193	25	in	in	ADP
aiti-13523	193	26	a	a	DET
aiti-13523	193	27	sentence	sentence	NOUN
aiti-13523	193	28	but	but	CCONJ
aiti-13523	193	29	also	also	ADV
aiti-13523	193	30	the	the	DET
aiti-13523	193	31	words	word	NOUN
aiti-13523	193	32	following	follow	VERB
aiti-13523	193	33	it	it	PRON
aiti-13523	193	34	.	.	PUNCT
aiti-13523	194	1	bert	bert	PROPN
aiti-13523	194	2	uses	use	VERB
aiti-13523	194	3	the	the	DET
aiti-13523	194	4	transformer	transformer	ADJ
aiti-13523	194	5	attention	attention	NOUN
aiti-13523	194	6	mechanism	mechanism	NOUN
aiti-13523	194	7	,	,	PUNCT
aiti-13523	194	8	which	which	PRON
aiti-13523	194	9	learns	learn	VERB
aiti-13523	194	10	the	the	DET
aiti-13523	194	11	contextual	contextual	ADJ
aiti-13523	194	12	relationships	relationship	NOUN
aiti-13523	194	13	between	between	ADP
aiti-13523	194	14	words	word	NOUN
aiti-13523	194	15	(	(	PUNCT
aiti-13523	194	16	or	or	CCONJ
aiti-13523	194	17	sub	sub	NOUN
aiti-13523	194	18	-	-	NOUN
aiti-13523	194	19	words	word	NOUN
aiti-13523	194	20	)	)	PUNCT
aiti-13523	194	21	in	in	ADP
aiti-13523	194	22	a	a	DET
aiti-13523	194	23	text	text	NOUN
aiti-13523	194	24	.	.	PUNCT
aiti-13523	195	1	in	in	ADP
aiti-13523	195	2	its	its	PRON
aiti-13523	195	3	traditional	traditional	ADJ
aiti-13523	195	4	form	form	NOUN
aiti-13523	195	5	,	,	PUNCT
aiti-13523	195	6	the	the	DET
aiti-13523	195	7	transformer	transformer	NOUN
aiti-13523	195	8	includes	include	VERB
aiti-13523	195	9	two	two	NUM
aiti-13523	195	10	mechanisms	mechanism	NOUN
aiti-13523	195	11	:	:	PUNCT
aiti-13523	195	12	an	an	DET
aiti-13523	195	13	encoder	encoder	NOUN
aiti-13523	195	14	that	that	PRON
aiti-13523	195	15	reads	read	VERB
aiti-13523	195	16	input	input	NOUN
aiti-13523	195	17	text	text	NOUN
aiti-13523	195	18	and	and	CCONJ
aiti-13523	195	19	a	a	DET
aiti-13523	195	20	decoder	decoder	NOUN
aiti-13523	195	21	that	that	PRON
aiti-13523	195	22	produces	produce	VERB
aiti-13523	195	23	a	a	DET
aiti-13523	195	24	prediction	prediction	NOUN
aiti-13523	195	25	for	for	ADP
aiti-13523	195	26	a	a	DET
aiti-13523	195	27	task	task	NOUN
aiti-13523	195	28	.	.	PUNCT
aiti-13523	196	1	as	as	SCONJ
aiti-13523	196	2	bert	bert	PROPN
aiti-13523	196	3	is	be	AUX
aiti-13523	196	4	used	use	VERB
aiti-13523	196	5	to	to	PART
aiti-13523	196	6	generate	generate	VERB
aiti-13523	196	7	a	a	DET
aiti-13523	196	8	language	language	NOUN
aiti-13523	196	9	model	model	NOUN
aiti-13523	196	10	,	,	PUNCT
aiti-13523	196	11	only	only	ADV
aiti-13523	196	12	the	the	DET
aiti-13523	196	13	coding	code	VERB
aiti-13523	196	14	mechanism	mechanism	NOUN
aiti-13523	196	15	is	be	AUX
aiti-13523	196	16	needed	need	VERB
aiti-13523	196	17	.	.	PUNCT
aiti-13523	197	1	in	in	ADP
aiti-13523	197	2	this	this	DET
aiti-13523	197	3	model	model	NOUN
aiti-13523	197	4	,	,	PUNCT
aiti-13523	197	5	the	the	DET
aiti-13523	197	6	use	use	NOUN
aiti-13523	197	7	of	of	ADP
aiti-13523	197	8	the	the	DET
aiti-13523	197	9	bert	bert	NOUN
aiti-13523	197	10	-	-	PUNCT
aiti-13523	197	11	base	base	NOUN
aiti-13523	197	12	-	-	PUNCT
aiti-13523	197	13	cased	case	VERB
aiti-13523	197	14	model	model	NOUN
aiti-13523	197	15	from	from	ADP
aiti-13523	197	16	the	the	DET
aiti-13523	197	17	transformer	transformer	NOUN
aiti-13523	197	18	’s	’s	PART
aiti-13523	197	19	library	library	NOUN
aiti-13523	197	20	allows	allow	VERB
aiti-13523	197	21	easy	easy	ADJ
aiti-13523	197	22	access	access	NOUN
aiti-13523	197	23	to	to	ADP
aiti-13523	197	24	transformation	transformation	NOUN
aiti-13523	197	25	models	model	NOUN
aiti-13523	197	26	and	and	CCONJ
aiti-13523	197	27	simplifies	simplifie	NOUN
aiti-13523	197	28	many	many	ADJ
aiti-13523	197	29	technical	technical	ADJ
aiti-13523	197	30	implementation	implementation	NOUN
aiti-13523	197	31	details	detail	NOUN
aiti-13523	197	32	.	.	PUNCT
aiti-13523	198	1	this	this	DET
aiti-13523	198	2	model	model	NOUN
aiti-13523	198	3	is	be	AUX
aiti-13523	198	4	advantageous	advantageous	ADJ
aiti-13523	198	5	for	for	ADP
aiti-13523	198	6	the	the	DET
aiti-13523	198	7	classification	classification	NOUN
aiti-13523	198	8	of	of	ADP
aiti-13523	198	9	multi	multi	ADJ
aiti-13523	198	10	-	-	ADJ
aiti-13523	198	11	label	label	ADJ
aiti-13523	198	12	texts	text	NOUN
aiti-13523	198	13	,	,	PUNCT
aiti-13523	198	14	it	it	PRON
aiti-13523	198	15	remains	remain	VERB
aiti-13523	198	16	case	case	NOUN
aiti-13523	198	17	sensitive	sensitive	ADJ
aiti-13523	198	18	,	,	PUNCT
aiti-13523	198	19	otherwise	otherwise	ADV
aiti-13523	198	20	,	,	PUNCT
aiti-13523	198	21	an	an	DET
aiti-13523	198	22	already	already	ADV
aiti-13523	198	23	solved	solve	VERB
aiti-13523	198	24	of	of	ADP
aiti-13523	198	25	this	this	DET
aiti-13523	198	26	problem	problem	NOUN
aiti-13523	198	27	during	during	ADP
aiti-13523	198	28	the	the	DET
aiti-13523	198	29	preprocessing	preprocessing	NOUN
aiti-13523	198	30	phase	phase	NOUN
aiti-13523	198	31	of	of	ADP
aiti-13523	198	32	data	datum	NOUN
aiti-13523	198	33	.	.	PUNCT
aiti-13523	199	1	as	as	SCONJ
aiti-13523	199	2	you	you	PRON
aiti-13523	199	3	can	can	AUX
aiti-13523	199	4	see	see	VERB
aiti-13523	199	5	in	in	ADP
aiti-13523	199	6	fig	fig	NOUN
aiti-13523	199	7	.	.	PUNCT
aiti-13523	200	1	3	3	NUM
aiti-13523	200	2	,	,	PUNCT
aiti-13523	200	3	the	the	DET
aiti-13523	200	4	model	model	NOUN
aiti-13523	200	5	takes	take	VERB
aiti-13523	200	6	labeled	label	VERB
aiti-13523	200	7	training	training	NOUN
aiti-13523	200	8	and	and	CCONJ
aiti-13523	200	9	test	test	NOUN
aiti-13523	200	10	data	datum	NOUN
aiti-13523	200	11	as	as	ADP
aiti-13523	200	12	input	input	NOUN
aiti-13523	200	13	and	and	CCONJ
aiti-13523	200	14	then	then	ADV
aiti-13523	200	15	loads	load	VERB
aiti-13523	200	16	bert	bert	PROPN
aiti-13523	200	17	’s	’s	PART
aiti-13523	200	18	tokenizer	tokenizer	NOUN
aiti-13523	200	19	,	,	PUNCT
aiti-13523	200	20	which	which	PRON
aiti-13523	200	21	divides	divide	VERB
aiti-13523	200	22	the	the	DET
aiti-13523	200	23	text	text	NOUN
aiti-13523	200	24	into	into	ADP
aiti-13523	200	25	subword	subword	PROPN
aiti-13523	200	26	units	unit	NOUN
aiti-13523	200	27	called	call	VERB
aiti-13523	200	28	tokens	token	NOUN
aiti-13523	200	29	.	.	PUNCT
aiti-13523	201	1	these	these	DET
aiti-13523	201	2	tokens	token	NOUN
aiti-13523	201	3	are	be	AUX
aiti-13523	201	4	then	then	ADV
aiti-13523	201	5	encoded	encode	VERB
aiti-13523	201	6	and	and	CCONJ
aiti-13523	201	7	converted	convert	VERB
aiti-13523	201	8	to	to	ADP
aiti-13523	201	9	digital	digital	ADJ
aiti-13523	201	10	format	format	NOUN
aiti-13523	201	11	,	,	PUNCT
aiti-13523	201	12	thus	thus	ADV
aiti-13523	201	13	forming	form	VERB
aiti-13523	201	14	input	input	NOUN
aiti-13523	201	15	identifiers	identifier	NOUN
aiti-13523	201	16	(	(	PUNCT
aiti-13523	201	17	input	input	NOUN
aiti-13523	201	18	ids	id	NOUN
aiti-13523	201	19	)	)	PUNCT
aiti-13523	201	20	and	and	CCONJ
aiti-13523	201	21	attention	attention	NOUN
aiti-13523	201	22	masks	mask	NOUN
aiti-13523	201	23	.	.	PUNCT
aiti-13523	202	1	input	input	NOUN
aiti-13523	202	2	ids	id	NOUN
aiti-13523	202	3	are	be	AUX
aiti-13523	202	4	integer	integer	NOUN
aiti-13523	202	5	identifiers	identifier	NOUN
aiti-13523	202	6	of	of	ADP
aiti-13523	202	7	each	each	PRON
aiti-13523	202	8	token	token	VERB
aiti-13523	202	9	in	in	ADP
aiti-13523	202	10	a	a	DET
aiti-13523	202	11	sequence	sequence	NOUN
aiti-13523	202	12	(	(	PUNCT
aiti-13523	202	13	a	a	DET
aiti-13523	202	14	set	set	NOUN
aiti-13523	202	15	of	of	ADP
aiti-13523	202	16	them	they	PRON
aiti-13523	202	17	to	to	ADP
aiti-13523	202	18	a	a	DET
aiti-13523	202	19	length	length	NOUN
aiti-13523	202	20	of	of	ADP
aiti-13523	202	21	256	256	NUM
aiti-13523	202	22	,	,	PUNCT
aiti-13523	202	23	is	be	AUX
aiti-13523	202	24	chosen	choose	VERB
aiti-13523	202	25	based	base	VERB
aiti-13523	202	26	on	on	ADP
aiti-13523	202	27	the	the	DET
aiti-13523	202	28	token	token	ADJ
aiti-13523	202	29	length	length	NOUN
aiti-13523	202	30	distribution	distribution	NOUN
aiti-13523	202	31	)	)	PUNCT
aiti-13523	202	32	.	.	PUNCT
aiti-13523	203	1	in	in	ADP
aiti-13523	203	2	this	this	DET
aiti-13523	203	3	case	case	NOUN
aiti-13523	203	4	,	,	PUNCT
aiti-13523	203	5	each	each	DET
aiti-13523	203	6	unique	unique	ADJ
aiti-13523	203	7	token	token	NOUN
aiti-13523	203	8	of	of	ADP
aiti-13523	203	9	the	the	DET
aiti-13523	203	10	vocabulary	vocabulary	NOUN
aiti-13523	203	11	is	be	AUX
aiti-13523	203	12	assigned	assign	VERB
aiti-13523	203	13	an	an	DET
aiti-13523	203	14	integer	integer	NOUN
aiti-13523	203	15	identifier	identifier	NOUN
aiti-13523	203	16	which	which	PRON
aiti-13523	203	17	represents	represent	VERB
aiti-13523	203	18	a	a	DET
aiti-13523	203	19	shortcut	shortcut	NOUN
aiti-13523	203	20	of	of	ADP
aiti-13523	203	21	a	a	DET
aiti-13523	203	22	one	one	NUM
aiti-13523	203	23	-	-	PUNCT
aiti-13523	203	24	hot	hot	ADJ
aiti-13523	203	25	encoded	encode	VERB
aiti-13523	203	26	vector	vector	NOUN
aiti-13523	203	27	:	:	PUNCT
aiti-13523	203	28	one	one	NUM
aiti-13523	203	29	-	-	PUNCT
aiti-13523	203	30	hot	hot	ADJ
aiti-13523	203	31	encoded	encode	VERB
aiti-13523	203	32	vectors	vector	NOUN
aiti-13523	203	33	are	be	AUX
aiti-13523	203	34	only	only	ADV
aiti-13523	203	35	vectors	vector	NOUN
aiti-13523	203	36	in	in	ADP
aiti-13523	203	37	which	which	PRON
aiti-13523	203	38	the	the	DET
aiti-13523	203	39	element	element	NOUN
aiti-13523	203	40	at	at	ADP
aiti-13523	203	41	the	the	DET
aiti-13523	203	42	index	index	NOUN
aiti-13523	203	43	corresponding	correspond	VERB
aiti-13523	203	44	to	to	ADP
aiti-13523	203	45	the	the	DET
aiti-13523	203	46	represented	represent	VERB
aiti-13523	203	47	token	token	NOUN
aiti-13523	203	48	has	have	VERB
aiti-13523	203	49	a	a	DET
aiti-13523	203	50	value	value	NOUN
aiti-13523	203	51	of	of	ADP
aiti-13523	203	52	one	one	NUM
aiti-13523	203	53	,	,	PUNCT
aiti-13523	203	54	and	and	CCONJ
aiti-13523	203	55	all	all	DET
aiti-13523	203	56	other	other	ADJ
aiti-13523	203	57	elements	element	NOUN
aiti-13523	203	58	have	have	VERB
aiti-13523	203	59	a	a	DET
aiti-13523	203	60	value	value	NOUN
aiti-13523	203	61	of	of	ADP
aiti-13523	203	62	zero	zero	NUM
aiti-13523	203	63	.	.	PUNCT
aiti-13523	204	1	attention	attention	NOUN
aiti-13523	204	2	masks	mask	NOUN
aiti-13523	204	3	are	be	AUX
aiti-13523	204	4	applied	apply	VERB
aiti-13523	204	5	to	to	PART
aiti-13523	204	6	extend	extend	VERB
aiti-13523	204	7	sequences	sequence	NOUN
aiti-13523	204	8	shorter	short	ADJ
aiti-13523	204	9	than	than	ADP
aiti-13523	204	10	the	the	DET
aiti-13523	204	11	maximum	maximum	ADJ
aiti-13523	204	12	sequence	sequence	NOUN
aiti-13523	204	13	length	length	NOUN
aiti-13523	204	14	with	with	ADP
aiti-13523	204	15	padding	padding	NOUN
aiti-13523	204	16	tokens	token	NOUN
aiti-13523	204	17	.	.	PUNCT
aiti-13523	205	1	fill	fill	NOUN
aiti-13523	205	2	tokens	token	NOUN
aiti-13523	205	3	are	be	AUX
aiti-13523	205	4	just	just	ADV
aiti-13523	205	5	placeholders	placeholder	NOUN
aiti-13523	205	6	and	and	CCONJ
aiti-13523	205	7	do	do	AUX
aiti-13523	205	8	not	not	PART
aiti-13523	205	9	influence	influence	VERB
aiti-13523	205	10	the	the	DET
aiti-13523	205	11	model	model	NOUN
aiti-13523	205	12	output	output	NOUN
aiti-13523	205	13	in	in	ADP
aiti-13523	205	14	any	any	DET
aiti-13523	205	15	way	way	NOUN
aiti-13523	205	16	.	.	PUNCT
aiti-13523	206	1	subsequently	subsequently	ADV
aiti-13523	206	2	,	,	PUNCT
aiti-13523	206	3	a	a	DET
aiti-13523	206	4	simple	simple	ADJ
aiti-13523	206	5	addition	addition	NOUN
aiti-13523	206	6	of	of	ADP
aiti-13523	206	7	a	a	DET
aiti-13523	206	8	classification	classification	NOUN
aiti-13523	206	9	layer	layer	NOUN
aiti-13523	206	10	takes	take	VERB
aiti-13523	206	11	as	as	SCONJ
aiti-13523	206	12	input	input	NOUN
aiti-13523	206	13	the	the	DET
aiti-13523	206	14	sequence	sequence	NOUN
aiti-13523	206	15	level	level	NOUN
aiti-13523	206	16	embedding	embed	VERB
aiti-13523	206	17	and	and	CCONJ
aiti-13523	206	18	generates	generate	VERB
aiti-13523	206	19	the	the	DET
aiti-13523	206	20	class	class	NOUN
aiti-13523	206	21	label	label	NOUN
aiti-13523	206	22	,	,	PUNCT
aiti-13523	206	23	for	for	ADP
aiti-13523	206	24	this	this	DET
aiti-13523	206	25	,	,	PUNCT
aiti-13523	206	26	bertforsequence	bertforsequence	NOUN
aiti-13523	206	27	-	-	PUNCT
aiti-13523	206	28	classification	classification	NOUN
aiti-13523	206	29	acts	act	NOUN
aiti-13523	206	30	as	as	ADP
aiti-13523	206	31	a	a	DET
aiti-13523	206	32	linear	linear	ADJ
aiti-13523	206	33	layer	layer	NOUN
aiti-13523	206	34	on	on	ADP
aiti-13523	206	35	top	top	NOUN
aiti-13523	206	36	of	of	ADP
aiti-13523	206	37	the	the	DET
aiti-13523	206	38	final	final	ADJ
aiti-13523	206	39	layer	layer	NOUN
aiti-13523	206	40	of	of	ADP
aiti-13523	206	41	the	the	DET
aiti-13523	206	42	transformer	transformer	NOUN
aiti-13523	206	43	and	and	CCONJ
aiti-13523	206	44	classifies	classify	VERB
aiti-13523	206	45	the	the	DET
aiti-13523	206	46	input	input	NOUN
aiti-13523	206	47	data	datum	NOUN
aiti-13523	206	48	.	.	PUNCT
aiti-13523	207	1	to	to	PART
aiti-13523	207	2	refine	refine	VERB
aiti-13523	207	3	this	this	DET
aiti-13523	207	4	bert	bert	NOUN
aiti-13523	207	5	classifier	classifier	NOUN
aiti-13523	207	6	,	,	PUNCT
aiti-13523	207	7	an	an	DET
aiti-13523	207	8	optimizer	optimizer	NOUN
aiti-13523	207	9	is	be	AUX
aiti-13523	207	10	used	use	VERB
aiti-13523	207	11	with	with	ADP
aiti-13523	207	12	fixed	fix	VERB
aiti-13523	207	13	weight	weight	NOUN
aiti-13523	207	14	loss	loss	NOUN
aiti-13523	207	15	adamw	adamw	NOUN
aiti-13523	207	16	,	,	PUNCT
aiti-13523	207	17	which	which	PRON
aiti-13523	207	18	is	be	AUX
aiti-13523	207	19	parameterized	parameterized	ADJ
aiti-13523	207	20	with	with	ADP
aiti-13523	207	21	a	a	DET
aiti-13523	207	22	learning	learn	VERB
aiti-13523	207	23	rate	rate	NOUN
aiti-13523	207	24	lr	lr	NOUN
aiti-13523	207	25	=	=	SYM
aiti-13523	207	26	1e-5	1e-5	PROPN
aiti-13523	207	27	,	,	PUNCT
aiti-13523	207	28	and	and	CCONJ
aiti-13523	207	29	fixed	fix	VERB
aiti-13523	207	30	adam	adam	PROPN
aiti-13523	207	31	’s	’s	PART
aiti-13523	207	32	epsilon	epsilon	PROPN
aiti-13523	207	33	for	for	ADP
aiti-13523	207	34	numerical	numerical	ADJ
aiti-13523	207	35	stability	stability	NOUN
aiti-13523	207	36	(	(	PUNCT
aiti-13523	207	37	eps	eps	PROPN
aiti-13523	207	38	=	=	SYM
aiti-13523	207	39	1e-8	1e-8	NUM
aiti-13523	207	40	)	)	PUNCT
aiti-13523	207	41	.	.	PUNCT
aiti-13523	208	1	adam	adam	PROPN
aiti-13523	208	2	trained	train	VERB
aiti-13523	208	3	this	this	DET
aiti-13523	208	4	model	model	NOUN
aiti-13523	208	5	on	on	ADP
aiti-13523	208	6	3	3	NUM
aiti-13523	208	7	epochs	epoch	NOUN
aiti-13523	208	8	in	in	ADP
aiti-13523	208	9	batches	batch	NOUN
aiti-13523	208	10	of	of	ADP
aiti-13523	208	11	3	3	NUM
aiti-13523	208	12	.	.	NOUN
aiti-13523	208	13	3.6	3.6	NUM
aiti-13523	208	14	.	.	PUNCT
aiti-13523	209	1	explainable	explainable	ADJ
aiti-13523	209	2	predictions	prediction	NOUN
aiti-13523	209	3	diagnostic	diagnostic	ADJ
aiti-13523	209	4	xai	xai	PROPN
aiti-13523	209	5	encompasses	encompass	VERB
aiti-13523	209	6	a	a	DET
aiti-13523	209	7	set	set	NOUN
aiti-13523	209	8	of	of	ADP
aiti-13523	209	9	processes	process	NOUN
aiti-13523	209	10	and	and	CCONJ
aiti-13523	209	11	methodologies	methodology	NOUN
aiti-13523	209	12	designed	design	VERB
aiti-13523	209	13	to	to	PART
aiti-13523	209	14	improve	improve	VERB
aiti-13523	209	15	this	this	DET
aiti-13523	209	16	understanding	understanding	NOUN
aiti-13523	209	17	of	of	ADP
aiti-13523	209	18	the	the	DET
aiti-13523	209	19	results	result	NOUN
aiti-13523	209	20	generated	generate	VERB
aiti-13523	209	21	by	by	ADP
aiti-13523	209	22	machine	machine	NOUN
aiti-13523	209	23	learning	learning	NOUN
aiti-13523	209	24	algorithms	algorithm	NOUN
aiti-13523	209	25	.	.	PUNCT
aiti-13523	210	1	these	these	DET
aiti-13523	210	2	methodologies	methodology	NOUN
aiti-13523	210	3	aim	aim	VERB
aiti-13523	210	4	to	to	PART
aiti-13523	210	5	shed	shed	VERB
aiti-13523	210	6	light	light	NOUN
aiti-13523	210	7	on	on	ADP
aiti-13523	210	8	how	how	SCONJ
aiti-13523	210	9	classification	classification	NOUN
aiti-13523	210	10	models	model	NOUN
aiti-13523	210	11	arrive	arrive	VERB
aiti-13523	210	12	at	at	ADP
aiti-13523	210	13	their	their	PRON
aiti-13523	210	14	predictions	prediction	NOUN
aiti-13523	210	15	.	.	PUNCT
aiti-13523	211	1	typically	typically	ADV
aiti-13523	211	2	,	,	PUNCT
aiti-13523	211	3	this	this	PRON
aiti-13523	211	4	involves	involve	VERB
aiti-13523	211	5	providing	provide	VERB
aiti-13523	211	6	textual	textual	ADJ
aiti-13523	211	7	or	or	CCONJ
aiti-13523	211	8	visual	visual	ADJ
aiti-13523	211	9	explanations	explanation	NOUN
aiti-13523	211	10	that	that	PRON
aiti-13523	211	11	explain	explain	VERB
aiti-13523	211	12	the	the	DET
aiti-13523	211	13	connection	connection	NOUN
aiti-13523	211	14	between	between	ADP
aiti-13523	211	15	the	the	DET
aiti-13523	211	16	input	input	NOUN
aiti-13523	211	17	features	feature	NOUN
aiti-13523	211	18	of	of	ADP
aiti-13523	211	19	a	a	DET
aiti-13523	211	20	prediction	prediction	NOUN
aiti-13523	211	21	(	(	PUNCT
aiti-13523	211	22	e.g.	e.g.	ADV
aiti-13523	211	23	,	,	PUNCT
aiti-13523	211	24	words	word	NOUN
aiti-13523	211	25	in	in	ADP
aiti-13523	211	26	a	a	DET
aiti-13523	211	27	text	text	NOUN
aiti-13523	211	28	)	)	PUNCT
aiti-13523	211	29	and	and	CCONJ
aiti-13523	211	30	the	the	DET
aiti-13523	211	31	model	model	NOUN
aiti-13523	211	32	’s	’s	PART
aiti-13523	211	33	output	output	NOUN
aiti-13523	211	34	[	[	X
aiti-13523	211	35	20	20	NUM
aiti-13523	211	36	]	]	PUNCT
aiti-13523	211	37	.	.	PUNCT
aiti-13523	212	1	in	in	ADP
aiti-13523	212	2	this	this	DET
aiti-13523	212	3	research	research	NOUN
aiti-13523	212	4	approach	approach	NOUN
aiti-13523	212	5	,	,	PUNCT
aiti-13523	212	6	an	an	DET
aiti-13523	212	7	implemented	implement	VERB
aiti-13523	212	8	lime	lime	NOUN
aiti-13523	212	9	is	be	AUX
aiti-13523	212	10	applied	apply	VERB
aiti-13523	212	11	to	to	PART
aiti-13523	212	12	analyze	analyze	VERB
aiti-13523	212	13	classifiers	classifier	NOUN
aiti-13523	212	14	that	that	PRON
aiti-13523	212	15	exhibit	exhibit	VERB
aiti-13523	212	16	lower	low	ADJ
aiti-13523	212	17	performance	performance	NOUN
aiti-13523	212	18	than	than	ADP
aiti-13523	212	19	other	other	ADJ
aiti-13523	212	20	baseline	baseline	NOUN
aiti-13523	212	21	models	model	NOUN
aiti-13523	212	22	.	.	PUNCT
aiti-13523	213	1	the	the	DET
aiti-13523	213	2	goal	goal	NOUN
aiti-13523	213	3	is	be	AUX
aiti-13523	213	4	to	to	PART
aiti-13523	213	5	better	well	ADV
aiti-13523	213	6	understand	understand	VERB
aiti-13523	213	7	the	the	DET
aiti-13523	213	8	contributions	contribution	NOUN
aiti-13523	213	9	of	of	ADP
aiti-13523	213	10	specific	specific	ADJ
aiti-13523	213	11	words	word	NOUN
aiti-13523	213	12	to	to	ADP
aiti-13523	213	13	the	the	DET
aiti-13523	213	14	output	output	NOUN
aiti-13523	213	15	class	class	NOUN
aiti-13523	213	16	predictions	prediction	NOUN
aiti-13523	213	17	,	,	PUNCT
aiti-13523	213	18	particularly	particularly	ADV
aiti-13523	213	19	regarding	regard	VERB
aiti-13523	213	20	the	the	DET
aiti-13523	213	21	classifier	classifier	NOUN
aiti-13523	213	22	that	that	PRON
aiti-13523	213	23	gave	give	VERB
aiti-13523	213	24	the	the	DET
aiti-13523	213	25	lowest	low	ADJ
aiti-13523	213	26	scores	score	NOUN
aiti-13523	213	27	among	among	ADP
aiti-13523	213	28	the	the	DET
aiti-13523	213	29	implemented	implement	VERB
aiti-13523	213	30	baseline	baseline	NOUN
aiti-13523	213	31	models	model	NOUN
aiti-13523	213	32	.	.	PUNCT
aiti-13523	214	1	advances	advance	NOUN
aiti-13523	214	2	in	in	ADP
aiti-13523	214	3	technology	technology	NOUN
aiti-13523	214	4	innovation	innovation	NOUN
aiti-13523	214	5	,	,	PUNCT
aiti-13523	214	6	vol	vol	NOUN
aiti-13523	214	7	.	.	PROPN
aiti-13523	215	1	9	9	NUM
aiti-13523	215	2	,	,	PUNCT
aiti-13523	215	3	no	no	INTJ
aiti-13523	215	4	.	.	NOUN
aiti-13523	215	5	2	2	NUM
aiti-13523	215	6	,	,	PUNCT
aiti-13523	215	7	2024	2024	NUM
aiti-13523	215	8	,	,	PUNCT
aiti-13523	215	9	pp	pp	ADJ
aiti-13523	215	10	.	.	PUNCT
aiti-13523	216	1	129	129	NUM
aiti-13523	216	2	-	-	SYM
aiti-13523	216	3	142	142	NUM
aiti-13523	216	4	137	137	NUM
aiti-13523	216	5	as	as	SCONJ
aiti-13523	216	6	shown	show	VERB
aiti-13523	216	7	in	in	ADP
aiti-13523	216	8	fig	fig	NOUN
aiti-13523	216	9	.	.	PUNCT
aiti-13523	217	1	4	4	NUM
aiti-13523	217	2	,	,	PUNCT
aiti-13523	217	3	the	the	DET
aiti-13523	217	4	lime	lime	NOUN
aiti-13523	217	5	model	model	NOUN
aiti-13523	217	6	works	work	VERB
aiti-13523	217	7	independently	independently	ADV
aiti-13523	217	8	from	from	ADP
aiti-13523	217	9	the	the	DET
aiti-13523	217	10	classification	classification	NOUN
aiti-13523	217	11	model	model	NOUN
aiti-13523	217	12	used	use	VERB
aiti-13523	217	13	.	.	PUNCT
aiti-13523	218	1	it	it	PRON
aiti-13523	218	2	can	can	AUX
aiti-13523	218	3	provide	provide	VERB
aiti-13523	218	4	clear	clear	ADJ
aiti-13523	218	5	and	and	CCONJ
aiti-13523	218	6	precise	precise	ADJ
aiti-13523	218	7	explanations	explanation	NOUN
aiti-13523	218	8	for	for	ADP
aiti-13523	218	9	individual	individual	ADJ
aiti-13523	218	10	predictions	prediction	NOUN
aiti-13523	218	11	made	make	VERB
aiti-13523	218	12	by	by	ADP
aiti-13523	218	13	any	any	DET
aiti-13523	218	14	classifier	classifier	NOUN
aiti-13523	218	15	or	or	CCONJ
aiti-13523	218	16	regressor	regressor	NOUN
aiti-13523	218	17	.	.	PUNCT
aiti-13523	219	1	lime	lime	NOUN
aiti-13523	219	2	achieves	achieve	VERB
aiti-13523	219	3	this	this	DET
aiti-13523	219	4	goal	goal	NOUN
aiti-13523	219	5	by	by	ADP
aiti-13523	219	6	locally	locally	ADV
aiti-13523	219	7	approximating	approximate	VERB
aiti-13523	219	8	the	the	DET
aiti-13523	219	9	model	model	NOUN
aiti-13523	219	10	with	with	ADP
aiti-13523	219	11	an	an	DET
aiti-13523	219	12	interpretable	interpretable	ADJ
aiti-13523	219	13	model	model	NOUN
aiti-13523	219	14	,	,	PUNCT
aiti-13523	219	15	thereby	thereby	ADV
aiti-13523	219	16	facilitating	facilitate	VERB
aiti-13523	219	17	the	the	DET
aiti-13523	219	18	interpretability	interpretability	NOUN
aiti-13523	219	19	of	of	ADP
aiti-13523	219	20	complex	complex	ADJ
aiti-13523	219	21	model	model	NOUN
aiti-13523	219	22	decisionmaking	decisionmake	VERB
aiti-13523	219	23	processes	process	NOUN
aiti-13523	219	24	.	.	PUNCT
aiti-13523	220	1	the	the	DET
aiti-13523	220	2	explainability	explainability	NOUN
aiti-13523	220	3	process	process	NOUN
aiti-13523	220	4	in	in	ADP
aiti-13523	220	5	lime	lime	NOUN
aiti-13523	220	6	involves	involve	VERB
aiti-13523	220	7	two	two	NUM
aiti-13523	220	8	fundamental	fundamental	ADJ
aiti-13523	220	9	steps	step	NOUN
aiti-13523	220	10	:	:	PUNCT
aiti-13523	220	11	during	during	ADP
aiti-13523	220	12	the	the	DET
aiti-13523	220	13	first	first	ADJ
aiti-13523	220	14	step	step	NOUN
aiti-13523	220	15	,	,	PUNCT
aiti-13523	220	16	employ	employ	VERB
aiti-13523	220	17	a	a	DET
aiti-13523	220	18	lime	lime	NOUN
aiti-13523	220	19	explainer	explainer	NOUN
aiti-13523	220	20	to	to	PART
aiti-13523	220	21	calculate	calculate	VERB
aiti-13523	220	22	the	the	DET
aiti-13523	220	23	contribution	contribution	NOUN
aiti-13523	220	24	of	of	ADP
aiti-13523	220	25	each	each	DET
aiti-13523	220	26	word	word	NOUN
aiti-13523	220	27	to	to	ADP
aiti-13523	220	28	a	a	DET
aiti-13523	220	29	class	class	NOUN
aiti-13523	220	30	.	.	PUNCT
aiti-13523	221	1	the	the	DET
aiti-13523	221	2	lime	lime	NOUN
aiti-13523	221	3	explainer	explainer	NOUN
aiti-13523	221	4	takes	take	VERB
aiti-13523	221	5	as	as	ADP
aiti-13523	221	6	inputs	input	NOUN
aiti-13523	221	7	the	the	DET
aiti-13523	221	8	perturbed	perturb	VERB
aiti-13523	221	9	data	datum	NOUN
aiti-13523	221	10	(	(	PUNCT
aiti-13523	221	11	obtained	obtain	VERB
aiti-13523	221	12	by	by	ADP
aiti-13523	221	13	permuting	permute	VERB
aiti-13523	221	14	an	an	DET
aiti-13523	221	15	observation	observation	NOUN
aiti-13523	221	16	)	)	PUNCT
aiti-13523	221	17	,	,	PUNCT
aiti-13523	221	18	the	the	DET
aiti-13523	221	19	labels	label	NOUN
aiti-13523	221	20	(	(	PUNCT
aiti-13523	221	21	the	the	DET
aiti-13523	221	22	classes	class	NOUN
aiti-13523	221	23	for	for	ADP
aiti-13523	221	24	which	which	PRON
aiti-13523	221	25	an	an	DET
aiti-13523	221	26	explanation	explanation	NOUN
aiti-13523	221	27	is	be	AUX
aiti-13523	221	28	done	do	VERB
aiti-13523	221	29	)	)	PUNCT
aiti-13523	221	30	,	,	PUNCT
aiti-13523	221	31	and	and	CCONJ
aiti-13523	221	32	the	the	DET
aiti-13523	221	33	distances	distance	NOUN
aiti-13523	221	34	(	(	PUNCT
aiti-13523	221	35	similarity	similarity	NOUN
aiti-13523	221	36	distance	distance	NOUN
aiti-13523	221	37	between	between	ADP
aiti-13523	221	38	the	the	DET
aiti-13523	221	39	original	original	ADJ
aiti-13523	221	40	observation	observation	NOUN
aiti-13523	221	41	and	and	CCONJ
aiti-13523	221	42	the	the	DET
aiti-13523	221	43	perturbed	perturb	VERB
aiti-13523	221	44	observations	observation	NOUN
aiti-13523	221	45	)	)	PUNCT
aiti-13523	221	46	.	.	PUNCT
aiti-13523	222	1	the	the	DET
aiti-13523	222	2	selected	select	VERB
aiti-13523	222	3	machine	machine	NOUN
aiti-13523	222	4	learning	learning	NOUN
aiti-13523	222	5	model	model	NOUN
aiti-13523	222	6	is	be	AUX
aiti-13523	222	7	applied	apply	VERB
aiti-13523	222	8	to	to	PART
aiti-13523	222	9	predict	predict	VERB
aiti-13523	222	10	the	the	DET
aiti-13523	222	11	results	result	NOUN
aiti-13523	222	12	of	of	ADP
aiti-13523	222	13	the	the	DET
aiti-13523	222	14	perturbed	perturb	VERB
aiti-13523	222	15	data	datum	NOUN
aiti-13523	222	16	.	.	PUNCT
aiti-13523	223	1	at	at	ADP
aiti-13523	223	2	the	the	DET
aiti-13523	223	3	output	output	NOUN
aiti-13523	223	4	of	of	ADP
aiti-13523	223	5	this	this	DET
aiti-13523	223	6	step	step	NOUN
aiti-13523	223	7	,	,	PUNCT
aiti-13523	223	8	the	the	DET
aiti-13523	223	9	weights	weight	NOUN
aiti-13523	223	10	of	of	ADP
aiti-13523	223	11	the	the	DET
aiti-13523	223	12	resulting	result	VERB
aiti-13523	223	13	features	feature	NOUN
aiti-13523	223	14	are	be	AUX
aiti-13523	223	15	obtained	obtain	VERB
aiti-13523	223	16	to	to	PART
aiti-13523	223	17	explain	explain	VERB
aiti-13523	223	18	the	the	DET
aiti-13523	223	19	behavior	behavior	NOUN
aiti-13523	223	20	of	of	ADP
aiti-13523	223	21	the	the	DET
aiti-13523	223	22	classifier	classifier	NOUN
aiti-13523	223	23	(	(	PUNCT
aiti-13523	223	24	explanation	explanation	NOUN
aiti-13523	223	25	of	of	ADP
aiti-13523	223	26	list	list	NOUN
aiti-13523	224	1	[	[	X
aiti-13523	224	2	word	word	NOUN
aiti-13523	224	3	,	,	PUNCT
aiti-13523	224	4	contributing	contribute	VERB
aiti-13523	224	5	weight	weight	NOUN
aiti-13523	224	6	,	,	PUNCT
aiti-13523	224	7	label	label	NOUN
aiti-13523	224	8	]	]	PUNCT
aiti-13523	224	9	)	)	PUNCT
aiti-13523	224	10	.	.	PUNCT
aiti-13523	225	1	secondly	secondly	ADV
aiti-13523	225	2	,	,	PUNCT
aiti-13523	225	3	a	a	DET
aiti-13523	225	4	calculation	calculation	NOUN
aiti-13523	225	5	of	of	ADP
aiti-13523	225	6	the	the	DET
aiti-13523	225	7	average	average	ADJ
aiti-13523	225	8	contribution	contribution	NOUN
aiti-13523	225	9	of	of	ADP
aiti-13523	225	10	each	each	DET
aiti-13523	225	11	word	word	NOUN
aiti-13523	225	12	to	to	ADP
aiti-13523	225	13	a	a	DET
aiti-13523	225	14	class	class	NOUN
aiti-13523	225	15	allows	allow	VERB
aiti-13523	225	16	us	we	PRON
aiti-13523	225	17	to	to	PART
aiti-13523	225	18	sort	sort	VERB
aiti-13523	225	19	and	and	CCONJ
aiti-13523	225	20	classify	classify	VERB
aiti-13523	225	21	words	word	NOUN
aiti-13523	225	22	according	accord	VERB
aiti-13523	225	23	to	to	ADP
aiti-13523	225	24	their	their	PRON
aiti-13523	225	25	impact	impact	NOUN
aiti-13523	225	26	as	as	ADP
aiti-13523	225	27	detractors	detractor	NOUN
aiti-13523	225	28	or	or	CCONJ
aiti-13523	225	29	supporters	supporter	NOUN
aiti-13523	225	30	in	in	ADP
aiti-13523	225	31	the	the	DET
aiti-13523	225	32	classification	classification	NOUN
aiti-13523	225	33	model	model	NOUN
aiti-13523	225	34	.	.	PUNCT
aiti-13523	226	1	fig	fig	NOUN
aiti-13523	226	2	.	.	PUNCT
aiti-13523	227	1	4	4	NUM
aiti-13523	227	2	lime	lime	NOUN
aiti-13523	227	3	model	model	NOUN
aiti-13523	227	4	process	process	NOUN
aiti-13523	227	5	4	4	NUM
aiti-13523	227	6	.	.	PUNCT
aiti-13523	227	7	experiments	experiment	NOUN
aiti-13523	227	8	and	and	CCONJ
aiti-13523	227	9	results	result	NOUN
aiti-13523	227	10	this	this	DET
aiti-13523	227	11	section	section	NOUN
aiti-13523	227	12	contains	contain	VERB
aiti-13523	227	13	the	the	DET
aiti-13523	227	14	results	result	NOUN
aiti-13523	227	15	of	of	ADP
aiti-13523	227	16	the	the	DET
aiti-13523	227	17	experiment	experiment	NOUN
aiti-13523	227	18	conducted	conduct	VERB
aiti-13523	227	19	in	in	ADP
aiti-13523	227	20	this	this	DET
aiti-13523	227	21	study	study	NOUN
aiti-13523	227	22	.	.	PUNCT
aiti-13523	228	1	it	it	PRON
aiti-13523	228	2	presents	present	VERB
aiti-13523	228	3	the	the	DET
aiti-13523	228	4	experiment	experiment	NOUN
aiti-13523	228	5	setup	setup	NOUN
aiti-13523	228	6	and	and	CCONJ
aiti-13523	228	7	the	the	DET
aiti-13523	228	8	metric	metric	NOUN
aiti-13523	228	9	used	use	VERB
aiti-13523	228	10	for	for	ADP
aiti-13523	228	11	evaluation	evaluation	NOUN
aiti-13523	228	12	,	,	PUNCT
aiti-13523	228	13	followed	follow	VERB
aiti-13523	228	14	by	by	ADP
aiti-13523	228	15	the	the	DET
aiti-13523	228	16	classification	classification	NOUN
aiti-13523	228	17	results	result	NOUN
aiti-13523	228	18	with	with	ADP
aiti-13523	228	19	baselines	baseline	NOUN
aiti-13523	228	20	and	and	CCONJ
aiti-13523	228	21	deep	deep	ADJ
aiti-13523	228	22	learning	learning	NOUN
aiti-13523	228	23	models	model	NOUN
aiti-13523	228	24	.	.	PUNCT
aiti-13523	229	1	additionally	additionally	ADV
aiti-13523	229	2	,	,	PUNCT
aiti-13523	229	3	it	it	PRON
aiti-13523	229	4	analyzes	analyze	VERB
aiti-13523	229	5	the	the	DET
aiti-13523	229	6	results	result	NOUN
aiti-13523	229	7	of	of	ADP
aiti-13523	229	8	the	the	DET
aiti-13523	229	9	explainability	explainability	NOUN
aiti-13523	229	10	provided	provide	VERB
aiti-13523	229	11	by	by	ADP
aiti-13523	229	12	the	the	DET
aiti-13523	229	13	lime	lime	NOUN
aiti-13523	229	14	model	model	NOUN
aiti-13523	229	15	.	.	PUNCT
aiti-13523	230	1	4.1	4.1	NUM
aiti-13523	230	2	.	.	PUNCT
aiti-13523	231	1	experimental	experimental	ADJ
aiti-13523	231	2	setup	setup	NOUN
aiti-13523	231	3	the	the	DET
aiti-13523	231	4	present	present	ADJ
aiti-13523	231	5	experiment	experiment	NOUN
aiti-13523	231	6	was	be	AUX
aiti-13523	231	7	conducted	conduct	VERB
aiti-13523	231	8	using	use	VERB
aiti-13523	231	9	the	the	DET
aiti-13523	231	10	google	google	PROPN
aiti-13523	231	11	colab	colab	PROPN
aiti-13523	231	12	platform	platform	NOUN
aiti-13523	231	13	with	with	ADP
aiti-13523	231	14	the	the	DET
aiti-13523	231	15	aim	aim	NOUN
aiti-13523	231	16	of	of	ADP
aiti-13523	231	17	training	training	NOUN
aiti-13523	231	18	learning	learning	NOUN
aiti-13523	231	19	models	model	NOUN
aiti-13523	231	20	.	.	PUNCT
aiti-13523	232	1	this	this	DET
aiti-13523	232	2	platform	platform	NOUN
aiti-13523	232	3	provides	provide	VERB
aiti-13523	232	4	unlimited	unlimited	ADJ
aiti-13523	232	5	access	access	NOUN
aiti-13523	232	6	to	to	ADP
aiti-13523	232	7	high	high	ADJ
aiti-13523	232	8	-	-	PUNCT
aiti-13523	232	9	performance	performance	NOUN
aiti-13523	232	10	graphics	graphic	NOUN
aiti-13523	232	11	processing	processing	NOUN
aiti-13523	232	12	units	unit	NOUN
aiti-13523	232	13	(	(	PUNCT
aiti-13523	232	14	gpus	gpu	NOUN
aiti-13523	232	15	)	)	PUNCT
aiti-13523	232	16	with	with	ADP
aiti-13523	232	17	minimal	minimal	ADJ
aiti-13523	232	18	configuration	configuration	NOUN
aiti-13523	232	19	requirements	requirement	NOUN
aiti-13523	232	20	.	.	PUNCT
aiti-13523	233	1	4.2	4.2	NUM
aiti-13523	233	2	.	.	PUNCT
aiti-13523	233	3	evaluation	evaluation	NOUN
aiti-13523	233	4	metric	metric	NOUN
aiti-13523	233	5	this	this	DET
aiti-13523	233	6	study	study	NOUN
aiti-13523	233	7	is	be	AUX
aiti-13523	233	8	a	a	DET
aiti-13523	233	9	comparison	comparison	NOUN
aiti-13523	233	10	of	of	ADP
aiti-13523	233	11	the	the	DET
aiti-13523	233	12	performance	performance	NOUN
aiti-13523	233	13	of	of	ADP
aiti-13523	233	14	various	various	ADJ
aiti-13523	233	15	baseline	baseline	NOUN
aiti-13523	233	16	models	model	NOUN
aiti-13523	233	17	on	on	ADP
aiti-13523	233	18	the	the	DET
aiti-13523	233	19	emohd	emohd	NOUN
aiti-13523	233	20	dataset	dataset	NOUN
aiti-13523	233	21	and	and	CCONJ
aiti-13523	233	22	the	the	DET
aiti-13523	233	23	performance	performance	NOUN
aiti-13523	233	24	of	of	ADP
aiti-13523	233	25	lstm	lstm	NOUN
aiti-13523	233	26	and	and	CCONJ
aiti-13523	233	27	bert	bert	PROPN
aiti-13523	233	28	for	for	ADP
aiti-13523	233	29	sentiment	sentiment	NOUN
aiti-13523	233	30	classification	classification	NOUN
aiti-13523	233	31	.	.	PUNCT
aiti-13523	234	1	during	during	ADP
aiti-13523	234	2	the	the	DET
aiti-13523	234	3	experimentation	experimentation	NOUN
aiti-13523	234	4	,	,	PUNCT
aiti-13523	234	5	the	the	DET
aiti-13523	234	6	preprocessed	preprocesse	VERB
aiti-13523	234	7	data	datum	NOUN
aiti-13523	234	8	was	be	AUX
aiti-13523	234	9	split	split	VERB
aiti-13523	234	10	using	use	VERB
aiti-13523	234	11	the	the	DET
aiti-13523	234	12	train_test_split	train_test_split	ADJ
aiti-13523	234	13	function	function	NOUN
aiti-13523	234	14	,	,	PUNCT
aiti-13523	234	15	so	so	SCONJ
aiti-13523	234	16	that	that	SCONJ
aiti-13523	234	17	20	20	NUM
aiti-13523	234	18	%	%	NOUN
aiti-13523	234	19	was	be	AUX
aiti-13523	234	20	allocated	allocate	VERB
aiti-13523	234	21	for	for	ADP
aiti-13523	234	22	testing	testing	NOUN
aiti-13523	234	23	and	and	CCONJ
aiti-13523	234	24	the	the	DET
aiti-13523	234	25	remaining	remain	VERB
aiti-13523	234	26	80	80	NUM
aiti-13523	234	27	%	%	NOUN
aiti-13523	234	28	was	be	AUX
aiti-13523	234	29	used	use	VERB
aiti-13523	234	30	for	for	ADP
aiti-13523	234	31	training	training	NOUN
aiti-13523	234	32	.	.	PUNCT
aiti-13523	235	1	to	to	PART
aiti-13523	235	2	evaluate	evaluate	VERB
aiti-13523	235	3	the	the	DET
aiti-13523	235	4	performance	performance	NOUN
aiti-13523	235	5	of	of	ADP
aiti-13523	235	6	each	each	DET
aiti-13523	235	7	classifier	classifier	NOUN
aiti-13523	235	8	,	,	PUNCT
aiti-13523	235	9	utilize	utilize	VERB
aiti-13523	235	10	the	the	DET
aiti-13523	235	11	f1	f1	NOUN
aiti-13523	235	12	-	-	PUNCT
aiti-13523	235	13	score	score	NOUN
aiti-13523	235	14	,	,	PUNCT
aiti-13523	235	15	a	a	DET
aiti-13523	235	16	standard	standard	ADJ
aiti-13523	235	17	evaluation	evaluation	NOUN
aiti-13523	235	18	metric	metric	NOUN
aiti-13523	235	19	that	that	PRON
aiti-13523	235	20	is	be	AUX
aiti-13523	235	21	more	more	ADV
aiti-13523	235	22	suitable	suitable	ADJ
aiti-13523	235	23	for	for	ADP
aiti-13523	235	24	imbalanced	imbalanced	ADJ
aiti-13523	235	25	datasets	dataset	NOUN
aiti-13523	235	26	than	than	ADP
aiti-13523	235	27	accuracy	accuracy	NOUN
aiti-13523	235	28	.	.	PUNCT
aiti-13523	236	1	the	the	DET
aiti-13523	236	2	f1	f1	NOUN
aiti-13523	236	3	-	-	PUNCT
aiti-13523	236	4	score	score	NOUN
aiti-13523	236	5	is	be	AUX
aiti-13523	236	6	a	a	DET
aiti-13523	236	7	weighted	weighted	ADJ
aiti-13523	236	8	average	average	NOUN
aiti-13523	236	9	of	of	ADP
aiti-13523	236	10	precision	precision	NOUN
aiti-13523	236	11	and	and	CCONJ
aiti-13523	236	12	recall	recall	VERB
aiti-13523	236	13	and	and	CCONJ
aiti-13523	236	14	takes	take	VERB
aiti-13523	236	15	into	into	ADP
aiti-13523	236	16	account	account	NOUN
aiti-13523	236	17	both	both	DET
aiti-13523	236	18	false	false	ADJ
aiti-13523	236	19	positives	positive	NOUN
aiti-13523	236	20	and	and	CCONJ
aiti-13523	236	21	false	false	ADJ
aiti-13523	236	22	negatives	negative	NOUN
aiti-13523	236	23	.	.	PUNCT
aiti-13523	237	1	the	the	DET
aiti-13523	237	2	mathematical	mathematical	ADJ
aiti-13523	237	3	expression	expression	NOUN
aiti-13523	237	4	for	for	ADP
aiti-13523	237	5	the	the	DET
aiti-13523	237	6	f1	f1	NOUN
aiti-13523	237	7	-	-	PUNCT
aiti-13523	237	8	score	score	NOUN
aiti-13523	237	9	is	be	AUX
aiti-13523	237	10	shown	show	VERB
aiti-13523	237	11	in	in	ADP
aiti-13523	237	12	:	:	PUNCT
aiti-13523	237	13	recall	recall	NOUN
aiti-13523	237	14	precision	precision	NOUN
aiti-13523	237	15	f1	f1	NOUN
aiti-13523	237	16	-	-	PUNCT
aiti-13523	237	17	score	score	NOUN
aiti-13523	237	18	2	2	NUM
aiti-13523	237	19	recall	recall	NOUN
aiti-13523	237	20	precision	precision	NOUN
aiti-13523	237	21	×	×	NOUN
aiti-13523	237	22	=	=	SYM
aiti-13523	237	23	×	×	NOUN
aiti-13523	238	1	+	+	CCONJ
aiti-13523	238	2	(	(	PUNCT
aiti-13523	238	3	3	3	NUM
aiti-13523	238	4	)	)	SYM
aiti-13523	238	5	138	138	NUM
aiti-13523	238	6	advances	advance	NOUN
aiti-13523	238	7	in	in	ADP
aiti-13523	238	8	technology	technology	NOUN
aiti-13523	238	9	innovation	innovation	NOUN
aiti-13523	238	10	,	,	PUNCT
aiti-13523	238	11	vol	vol	NOUN
aiti-13523	238	12	.	.	PROPN
aiti-13523	238	13	9	9	NUM
aiti-13523	238	14	,	,	PUNCT
aiti-13523	238	15	no	no	INTJ
aiti-13523	238	16	.	.	NOUN
aiti-13523	238	17	2	2	NUM
aiti-13523	238	18	,	,	PUNCT
aiti-13523	238	19	2024	2024	NUM
aiti-13523	238	20	,	,	PUNCT
aiti-13523	238	21	pp	pp	ADJ
aiti-13523	238	22	.	.	PUNCT
aiti-13523	239	1	129	129	NUM
aiti-13523	239	2	-	-	SYM
aiti-13523	239	3	142	142	NUM
aiti-13523	239	4	4.3	4.3	NUM
aiti-13523	239	5	.	.	PUNCT
aiti-13523	239	6	results	result	NOUN
aiti-13523	239	7	of	of	ADP
aiti-13523	239	8	classification	classification	NOUN
aiti-13523	239	9	with	with	ADP
aiti-13523	239	10	baseline	baseline	ADJ
aiti-13523	239	11	methods	method	NOUN
aiti-13523	239	12	a	a	DET
aiti-13523	239	13	trained	train	VERB
aiti-13523	239	14	of	of	ADP
aiti-13523	239	15	all	all	DET
aiti-13523	239	16	the	the	DET
aiti-13523	239	17	machine	machine	NOUN
aiti-13523	239	18	learning	learn	VERB
aiti-13523	239	19	algorithms	algorithm	NOUN
aiti-13523	239	20	as	as	SCONJ
aiti-13523	239	21	described	describe	VERB
aiti-13523	239	22	in	in	ADP
aiti-13523	239	23	the	the	DET
aiti-13523	239	24	“	"	PUNCT
aiti-13523	239	25	basic	basic	ADJ
aiti-13523	239	26	modeling	modeling	NOUN
aiti-13523	239	27	”	"	PUNCT
aiti-13523	239	28	section	section	NOUN
aiti-13523	239	29	with	with	ADP
aiti-13523	239	30	the	the	DET
aiti-13523	239	31	models	model	NOUN
aiti-13523	239	32	:	:	PUNCT
aiti-13523	239	33	logistic	logistic	ADJ
aiti-13523	239	34	regression	regression	NOUN
aiti-13523	239	35	,	,	PUNCT
aiti-13523	239	36	nb	nb	INTJ
aiti-13523	239	37	,	,	PUNCT
aiti-13523	239	38	and	and	CCONJ
aiti-13523	239	39	lightgbm	lightgbm	ADJ
aiti-13523	239	40	,	,	PUNCT
aiti-13523	239	41	each	each	DET
aiti-13523	239	42	time	time	NOUN
aiti-13523	239	43	using	use	VERB
aiti-13523	239	44	a	a	DET
aiti-13523	239	45	different	different	ADJ
aiti-13523	239	46	feature	feature	NOUN
aiti-13523	239	47	selection	selection	NOUN
aiti-13523	239	48	method	method	NOUN
aiti-13523	239	49	(	(	PUNCT
aiti-13523	239	50	cbow	cbow	VERB
aiti-13523	239	51	,	,	PUNCT
aiti-13523	239	52	tf	tf	PROPN
aiti-13523	239	53	-	-	PUNCT
aiti-13523	239	54	idf	idf	PROPN
aiti-13523	239	55	,	,	PUNCT
aiti-13523	239	56	word2vec	word2vec	PROPN
aiti-13523	239	57	)	)	PUNCT
aiti-13523	239	58	and	and	CCONJ
aiti-13523	239	59	an	an	DET
aiti-13523	239	60	evaluation	evaluation	NOUN
aiti-13523	239	61	of	of	ADP
aiti-13523	239	62	their	their	PRON
aiti-13523	239	63	performance	performance	NOUN
aiti-13523	239	64	on	on	ADP
aiti-13523	239	65	the	the	DET
aiti-13523	239	66	emohd	emohd	PROPN
aiti-13523	239	67	dataset	dataset	NOUN
aiti-13523	239	68	,	,	PUNCT
aiti-13523	239	69	including	include	VERB
aiti-13523	239	70	and	and	CCONJ
aiti-13523	239	71	excluding	exclude	VERB
aiti-13523	239	72	minority	minority	NOUN
aiti-13523	239	73	data	datum	NOUN
aiti-13523	239	74	classes	class	NOUN
aiti-13523	239	75	,	,	PUNCT
aiti-13523	239	76	using	use	VERB
aiti-13523	239	77	five	five	NUM
aiti-13523	239	78	different	different	ADJ
aiti-13523	239	79	resampling	resample	VERB
aiti-13523	239	80	methods	method	NOUN
aiti-13523	239	81	:	:	PUNCT
aiti-13523	239	82	naive	naive	ADJ
aiti-13523	239	83	undersampling	undersampling	ADJ
aiti-13523	239	84	,	,	PUNCT
aiti-13523	239	85	naive	naive	ADJ
aiti-13523	239	86	oversampling	oversampling	NOUN
aiti-13523	239	87	,	,	PUNCT
aiti-13523	239	88	oversampling	oversample	VERB
aiti-13523	239	89	with	with	ADP
aiti-13523	239	90	nearmiss	nearmiss	ADJ
aiti-13523	239	91	,	,	PUNCT
aiti-13523	239	92	smote	smote	ADJ
aiti-13523	239	93	,	,	PUNCT
aiti-13523	239	94	and	and	CCONJ
aiti-13523	239	95	adasyn	adasyn	PROPN
aiti-13523	239	96	.	.	PUNCT
aiti-13523	240	1	the	the	DET
aiti-13523	240	2	results	result	NOUN
aiti-13523	240	3	of	of	ADP
aiti-13523	240	4	these	these	DET
aiti-13523	240	5	evaluations	evaluation	NOUN
aiti-13523	240	6	are	be	AUX
aiti-13523	240	7	presented	present	VERB
aiti-13523	240	8	in	in	ADP
aiti-13523	240	9	tables	table	NOUN
aiti-13523	240	10	1	1	NUM
aiti-13523	240	11	and	and	CCONJ
aiti-13523	240	12	2	2	NUM
aiti-13523	240	13	.	.	NOUN
aiti-13523	240	14	table	table	NOUN
aiti-13523	240	15	1	1	NUM
aiti-13523	240	16	f1	f1	NOUN
aiti-13523	240	17	-	-	PUNCT
aiti-13523	240	18	score	score	NOUN
aiti-13523	240	19	implemented	implement	VERB
aiti-13523	240	20	baseline	baseline	NOUN
aiti-13523	240	21	including	include	VERB
aiti-13523	240	22	minority	minority	NOUN
aiti-13523	240	23	classes	class	NOUN
aiti-13523	240	24	model	model	VERB
aiti-13523	240	25	feature	feature	NOUN
aiti-13523	240	26	extraction	extraction	NOUN
aiti-13523	240	27	dc	dc	PROPN
aiti-13523	240	28	naive	naive	ADJ
aiti-13523	240	29	us	we	PRON
aiti-13523	240	30	naive	naive	ADJ
aiti-13523	240	31	os	os	INTJ
aiti-13523	240	32	nearmiss	nearmiss	ADJ
aiti-13523	240	33	smote	smote	PROPN
aiti-13523	240	34	adasyn	adasyn	PROPN
aiti-13523	240	35	nb	nb	PROPN
aiti-13523	240	36	cbow	cbow	VERB
aiti-13523	240	37	0.476	0.476	NUM
aiti-13523	240	38	0.574	0.574	NUM
aiti-13523	240	39	0.700	0.700	NUM
aiti-13523	240	40	0.574	0.574	NUM
aiti-13523	240	41	0.579	0.579	NUM
aiti-13523	240	42	0.593	0.593	NUM
aiti-13523	240	43	lr	lr	PROPN
aiti-13523	240	44	0.488	0.488	NUM
aiti-13523	240	45	0.608	0.608	NUM
aiti-13523	240	46	0.823	0.823	NUM
aiti-13523	240	47	0.609	0.609	NUM
aiti-13523	240	48	0.617	0.617	NUM
aiti-13523	240	49	0.622	0.622	NUM
aiti-13523	240	50	lgbm	lgbm	ADJ
aiti-13523	240	51	0.485	0.485	NUM
aiti-13523	240	52	0.633	0.633	NUM
aiti-13523	240	53	0.603	0.603	NUM
aiti-13523	240	54	0.633	0.633	NUM
aiti-13523	240	55	0.577	0.577	NUM
aiti-13523	240	56	0.613	0.613	NUM
aiti-13523	240	57	nb	nb	INTJ
aiti-13523	241	1	tf	tf	PROPN
aiti-13523	241	2	-	-	PUNCT
aiti-13523	241	3	idf	idf	PROPN
aiti-13523	241	4	0.489	0.489	NUM
aiti-13523	241	5	0.638	0.638	NUM
aiti-13523	241	6	0.680	0.680	NUM
aiti-13523	241	7	0.638	0.638	NUM
aiti-13523	241	8	0.599	0.599	NUM
aiti-13523	241	9	0.599	0.599	NUM
aiti-13523	241	10	lr	lr	NOUN
aiti-13523	241	11	0.504	0.504	NUM
aiti-13523	241	12	0.617	0.617	NUM
aiti-13523	241	13	0.839	0.839	NUM
aiti-13523	241	14	0.618	0.618	NUM
aiti-13523	241	15	0.629	0.629	NUM
aiti-13523	241	16	0.628	0.628	NUM
aiti-13523	241	17	lgbm	lgbm	ADJ
aiti-13523	241	18	0.495	0.495	NUM
aiti-13523	241	19	0.639	0.639	NUM
aiti-13523	241	20	0.613	0.613	NUM
aiti-13523	241	21	0.642	0.642	NUM
aiti-13523	241	22	0.585	0.585	NUM
aiti-13523	241	23	0.592	0.592	NUM
aiti-13523	241	24	lr	lr	X
aiti-13523	241	25	word2vec	word2vec	X
aiti-13523	241	26	0.489	0.489	NUM
aiti-13523	241	27	0.612	0.612	NUM
aiti-13523	241	28	0.631	0.631	NUM
aiti-13523	241	29	0.616	0.616	NUM
aiti-13523	241	30	0.612	0.612	NUM
aiti-13523	241	31	0.613	0.613	NUM
aiti-13523	241	32	table	table	NOUN
aiti-13523	241	33	2	2	NUM
aiti-13523	241	34	f1	f1	NOUN
aiti-13523	241	35	-	-	PUNCT
aiti-13523	241	36	score	score	NOUN
aiti-13523	241	37	implemented	implement	VERB
aiti-13523	241	38	baseline	baseline	NOUN
aiti-13523	241	39	excluding	exclude	VERB
aiti-13523	241	40	minority	minority	NOUN
aiti-13523	241	41	classes	class	NOUN
aiti-13523	241	42	model	model	VERB
aiti-13523	241	43	feature	feature	NOUN
aiti-13523	241	44	extraction	extraction	NOUN
aiti-13523	241	45	dc	dc	PROPN
aiti-13523	241	46	naive	naive	ADJ
aiti-13523	241	47	us	we	PRON
aiti-13523	241	48	naive	naive	ADJ
aiti-13523	241	49	os	os	INTJ
aiti-13523	241	50	nearmiss	nearmiss	ADJ
aiti-13523	241	51	smote	smote	PROPN
aiti-13523	241	52	adasyn	adasyn	PROPN
aiti-13523	241	53	nb	nb	PROPN
aiti-13523	241	54	cbow	cbow	VERB
aiti-13523	241	55	0.472	0.472	NUM
aiti-13523	241	56	0.544	0.544	NUM
aiti-13523	241	57	0.737	0.737	NUM
aiti-13523	241	58	0.556	0.556	NUM
aiti-13523	241	59	0.577	0.577	NUM
aiti-13523	241	60	0.551	0.551	NUM
aiti-13523	241	61	lr	lr	VERB
aiti-13523	241	62	0.486	0.486	NUM
aiti-13523	241	63	0.581	0.581	NUM
aiti-13523	241	64	0.803	0.803	NUM
aiti-13523	241	65	0.608	0.608	NUM
aiti-13523	241	66	0.616	0.616	NUM
aiti-13523	241	67	0.633	0.633	NUM
aiti-13523	241	68	lgbm	lgbm	NOUN
aiti-13523	241	69	0.465	0.465	NUM
aiti-13523	241	70	0.611	0.611	NUM
aiti-13523	241	71	0.578	0.578	NUM
aiti-13523	241	72	0.604	0.604	NUM
aiti-13523	241	73	0.539	0.539	NUM
aiti-13523	241	74	0.551	0.551	NUM
aiti-13523	241	75	nb	nb	NOUN
aiti-13523	241	76	tf	tf	PROPN
aiti-13523	241	77	-	-	PUNCT
aiti-13523	241	78	idf	idf	PROPN
aiti-13523	241	79	0.475	0.475	NUM
aiti-13523	241	80	0.588	0.588	NUM
aiti-13523	241	81	0.667	0.667	NUM
aiti-13523	241	82	0.587	0.587	NUM
aiti-13523	241	83	0.595	0.595	NUM
aiti-13523	241	84	0.608	0.608	NUM
aiti-13523	241	85	lr	lr	NOUN
aiti-13523	241	86	0.490	0.490	NUM
aiti-13523	241	87	0.610	0.610	NUM
aiti-13523	241	88	0.831	0.831	NUM
aiti-13523	241	89	0.631	0.631	NUM
aiti-13523	241	90	0.671	0.671	NUM
aiti-13523	241	91	0.676	0.676	NUM
aiti-13523	241	92	lgbm	lgbm	NOUN
aiti-13523	241	93	0.487	0.487	NUM
aiti-13523	241	94	0.609	0.609	NUM
aiti-13523	241	95	0.618	0.618	NUM
aiti-13523	241	96	0.601	0.601	NUM
aiti-13523	241	97	0.531	0.531	NUM
aiti-13523	241	98	0.540	0.540	NUM
aiti-13523	241	99	lr	lr	X
aiti-13523	241	100	word2vec	word2vec	X
aiti-13523	241	101	0.483	0.483	NUM
aiti-13523	241	102	0.592	0.592	NUM
aiti-13523	241	103	0.600	0.600	NUM
aiti-13523	241	104	0.569	0.569	NUM
aiti-13523	241	105	0.527	0.527	NUM
aiti-13523	241	106	0.539	0.539	NUM
aiti-13523	241	107	4.4	4.4	NUM
aiti-13523	241	108	.	.	PUNCT
aiti-13523	242	1	results	result	NOUN
aiti-13523	242	2	of	of	ADP
aiti-13523	242	3	classification	classification	NOUN
aiti-13523	242	4	with	with	ADP
aiti-13523	242	5	recurrent	recurrent	ADJ
aiti-13523	242	6	neuronal	neuronal	ADJ
aiti-13523	242	7	networks	network	NOUN
aiti-13523	242	8	(	(	PUNCT
aiti-13523	242	9	lstm	lstm	NOUN
aiti-13523	242	10	and	and	CCONJ
aiti-13523	242	11	bert	bert	NOUN
aiti-13523	242	12	)	)	PUNCT
aiti-13523	242	13	in	in	ADP
aiti-13523	242	14	this	this	DET
aiti-13523	242	15	experiment	experiment	NOUN
aiti-13523	242	16	,	,	PUNCT
aiti-13523	242	17	an	an	DET
aiti-13523	242	18	lstm	lstm	NOUN
aiti-13523	242	19	and	and	CCONJ
aiti-13523	242	20	a	a	DET
aiti-13523	242	21	bert	bert	NOUN
aiti-13523	242	22	model	model	NOUN
aiti-13523	242	23	(	(	PUNCT
aiti-13523	242	24	all	all	DET
aiti-13523	242	25	parameters	parameter	NOUN
aiti-13523	242	26	are	be	AUX
aiti-13523	242	27	explained	explain	VERB
aiti-13523	242	28	in	in	ADP
aiti-13523	242	29	previous	previous	ADJ
aiti-13523	242	30	sections	section	NOUN
aiti-13523	242	31	)	)	PUNCT
aiti-13523	242	32	are	be	AUX
aiti-13523	242	33	trained	train	VERB
aiti-13523	242	34	with	with	ADP
aiti-13523	242	35	three	three	NUM
aiti-13523	242	36	different	different	ADJ
aiti-13523	242	37	approaches	approach	NOUN
aiti-13523	242	38	:	:	PUNCT
aiti-13523	242	39	without	without	ADP
aiti-13523	242	40	re	re	VERB
aiti-13523	242	41	-	-	VERB
aiti-13523	242	42	sampling	sample	VERB
aiti-13523	242	43	,	,	PUNCT
aiti-13523	242	44	with	with	ADP
aiti-13523	242	45	oversampling	oversample	VERB
aiti-13523	242	46	including	include	VERB
aiti-13523	242	47	minor	minor	ADJ
aiti-13523	242	48	classes	class	NOUN
aiti-13523	242	49	,	,	PUNCT
aiti-13523	242	50	and	and	CCONJ
aiti-13523	242	51	with	with	ADP
aiti-13523	242	52	oversampling	oversample	VERB
aiti-13523	242	53	excluding	exclude	VERB
aiti-13523	242	54	minor	minor	ADJ
aiti-13523	242	55	classes	class	NOUN
aiti-13523	242	56	.	.	PUNCT
aiti-13523	243	1	the	the	DET
aiti-13523	243	2	obtained	obtain	VERB
aiti-13523	243	3	f1	f1	NOUN
aiti-13523	243	4	-	-	PUNCT
aiti-13523	243	5	scores	score	NOUN
aiti-13523	243	6	are	be	AUX
aiti-13523	243	7	in	in	ADP
aiti-13523	243	8	table	table	NOUN
aiti-13523	243	9	3	3	NUM
aiti-13523	243	10	:	:	PUNCT
aiti-13523	243	11	table	table	NOUN
aiti-13523	243	12	3	3	NUM
aiti-13523	243	13	f1	f1	NOUN
aiti-13523	243	14	-	-	PUNCT
aiti-13523	243	15	score	score	NOUN
aiti-13523	243	16	of	of	ADP
aiti-13523	243	17	lstm	lstm	NOUN
aiti-13523	243	18	and	and	CCONJ
aiti-13523	243	19	bert	bert	PROPN
aiti-13523	243	20	models	model	NOUN
aiti-13523	243	21	re	re	ADJ
aiti-13523	243	22	-	-	ADJ
aiti-13523	243	23	sampling	sample	VERB
aiti-13523	243	24	approach	approach	NOUN
aiti-13523	243	25	lstm	lstm	PROPN
aiti-13523	243	26	bert	bert	PROPN
aiti-13523	243	27	without	without	ADP
aiti-13523	243	28	re	re	VERB
aiti-13523	243	29	-	-	VERB
aiti-13523	243	30	sampling	sample	VERB
aiti-13523	243	31	49	49	NUM
aiti-13523	243	32	%	%	NOUN
aiti-13523	243	33	57	57	NUM
aiti-13523	243	34	%	%	NOUN
aiti-13523	243	35	with	with	ADP
aiti-13523	243	36	oversampling	oversample	VERB
aiti-13523	243	37	including	include	VERB
aiti-13523	243	38	minor	minor	ADJ
aiti-13523	243	39	classes	class	NOUN
aiti-13523	243	40	82	82	NUM
aiti-13523	243	41	%	%	NOUN
aiti-13523	243	42	82	82	NUM
aiti-13523	243	43	%	%	NOUN
aiti-13523	243	44	with	with	ADP
aiti-13523	243	45	oversampling	oversample	VERB
aiti-13523	243	46	excluding	exclude	VERB
aiti-13523	243	47	minor	minor	ADJ
aiti-13523	243	48	89	89	NUM
aiti-13523	243	49	%	%	NOUN
aiti-13523	243	50	89	89	NUM
aiti-13523	243	51	%	%	NOUN
aiti-13523	243	52	4.5	4.5	NUM
aiti-13523	243	53	.	.	PUNCT
aiti-13523	244	1	analysis	analysis	NOUN
aiti-13523	244	2	of	of	ADP
aiti-13523	244	3	results	result	NOUN
aiti-13523	244	4	of	of	ADP
aiti-13523	244	5	classification	classification	NOUN
aiti-13523	244	6	by	by	ADP
aiti-13523	244	7	closely	closely	ADV
aiti-13523	244	8	analyzing	analyzing	NOUN
aiti-13523	244	9	tables	table	NOUN
aiti-13523	244	10	1	1	NUM
aiti-13523	244	11	,	,	PUNCT
aiti-13523	244	12	2	2	NUM
aiti-13523	244	13	,	,	PUNCT
aiti-13523	244	14	and	and	CCONJ
aiti-13523	244	15	3	3	NUM
aiti-13523	244	16	:	:	PUNCT
aiti-13523	244	17	unbalanced	unbalanced	ADJ
aiti-13523	244	18	data	datum	NOUN
aiti-13523	244	19	significantly	significantly	ADV
aiti-13523	244	20	affects	affect	VERB
aiti-13523	244	21	the	the	DET
aiti-13523	244	22	classification	classification	NOUN
aiti-13523	244	23	and	and	CCONJ
aiti-13523	244	24	it	it	PRON
aiti-13523	244	25	is	be	AUX
aiti-13523	244	26	necessary	necessary	ADJ
aiti-13523	244	27	to	to	PART
aiti-13523	244	28	resample	resample	VERB
aiti-13523	244	29	the	the	DET
aiti-13523	244	30	data	datum	NOUN
aiti-13523	244	31	to	to	PART
aiti-13523	244	32	obtain	obtain	VERB
aiti-13523	244	33	better	well	ADJ
aiti-13523	244	34	results	result	NOUN
aiti-13523	244	35	.	.	PUNCT
aiti-13523	245	1	the	the	DET
aiti-13523	245	2	inclusion	inclusion	NOUN
aiti-13523	245	3	or	or	CCONJ
aiti-13523	245	4	exclusion	exclusion	NOUN
aiti-13523	245	5	of	of	ADP
aiti-13523	245	6	minority	minority	NOUN
aiti-13523	245	7	classes	class	NOUN
aiti-13523	245	8	has	have	VERB
aiti-13523	245	9	no	no	DET
aiti-13523	245	10	significant	significant	ADJ
aiti-13523	245	11	impact	impact	NOUN
aiti-13523	245	12	on	on	ADP
aiti-13523	245	13	the	the	DET
aiti-13523	245	14	classification	classification	NOUN
aiti-13523	245	15	results	result	NOUN
aiti-13523	245	16	according	accord	VERB
aiti-13523	245	17	to	to	ADP
aiti-13523	245	18	the	the	DET
aiti-13523	245	19	different	different	ADJ
aiti-13523	245	20	basic	basic	ADJ
aiti-13523	245	21	models	model	NOUN
aiti-13523	245	22	.	.	PUNCT
aiti-13523	246	1	the	the	DET
aiti-13523	246	2	scores	score	NOUN
aiti-13523	246	3	obtained	obtain	VERB
aiti-13523	246	4	in	in	ADP
aiti-13523	246	5	tables	table	NOUN
aiti-13523	246	6	1	1	NUM
aiti-13523	246	7	and	and	CCONJ
aiti-13523	246	8	2	2	NUM
aiti-13523	246	9	are	be	AUX
aiti-13523	246	10	almost	almost	ADV
aiti-13523	246	11	identical	identical	ADJ
aiti-13523	246	12	which	which	PRON
aiti-13523	246	13	is	be	AUX
aiti-13523	246	14	not	not	PART
aiti-13523	246	15	the	the	DET
aiti-13523	246	16	case	case	NOUN
aiti-13523	246	17	in	in	ADP
aiti-13523	246	18	table	table	NOUN
aiti-13523	246	19	3	3	NUM
aiti-13523	246	20	which	which	PRON
aiti-13523	246	21	clearly	clearly	ADV
aiti-13523	246	22	shows	show	VERB
aiti-13523	246	23	the	the	DET
aiti-13523	246	24	improvement	improvement	NOUN
aiti-13523	246	25	in	in	ADP
aiti-13523	246	26	the	the	DET
aiti-13523	246	27	classification	classification	NOUN
aiti-13523	246	28	rate	rate	NOUN
aiti-13523	246	29	after	after	ADP
aiti-13523	246	30	removing	remove	VERB
aiti-13523	246	31	the	the	DET
aiti-13523	246	32	minority	minority	NOUN
aiti-13523	246	33	classes	class	NOUN
aiti-13523	246	34	.	.	PUNCT
aiti-13523	247	1	this	this	PRON
aiti-13523	247	2	leads	lead	VERB
aiti-13523	247	3	to	to	ADP
aiti-13523	247	4	the	the	DET
aiti-13523	247	5	deduction	deduction	NOUN
aiti-13523	247	6	that	that	PRON
aiti-13523	247	7	oversampling	oversampling	NOUN
aiti-13523	247	8	has	have	VERB
aiti-13523	247	9	more	more	ADJ
aiti-13523	247	10	impact	impact	NOUN
aiti-13523	247	11	on	on	ADP
aiti-13523	247	12	the	the	DET
aiti-13523	247	13	classification	classification	NOUN
aiti-13523	247	14	using	use	VERB
aiti-13523	247	15	machine	machine	NOUN
aiti-13523	247	16	learning	learning	NOUN
aiti-13523	247	17	models	model	NOUN
aiti-13523	247	18	which	which	PRON
aiti-13523	247	19	is	be	AUX
aiti-13523	247	20	not	not	PART
aiti-13523	247	21	the	the	DET
aiti-13523	247	22	case	case	NOUN
aiti-13523	247	23	for	for	ADP
aiti-13523	247	24	deep	deep	ADJ
aiti-13523	247	25	learning	learning	NOUN
aiti-13523	247	26	algorithms	algorithm	NOUN
aiti-13523	247	27	,	,	PUNCT
aiti-13523	247	28	which	which	PRON
aiti-13523	247	29	are	be	AUX
aiti-13523	247	30	already	already	ADV
aiti-13523	247	31	more	more	ADV
aiti-13523	247	32	efficient	efficient	ADJ
aiti-13523	247	33	.	.	PUNCT
aiti-13523	248	1	in	in	ADP
aiti-13523	248	2	this	this	DET
aiti-13523	248	3	specific	specific	ADJ
aiti-13523	248	4	case	case	NOUN
aiti-13523	248	5	,	,	PUNCT
aiti-13523	248	6	it	it	PRON
aiti-13523	248	7	is	be	AUX
aiti-13523	248	8	clear	clear	ADJ
aiti-13523	248	9	that	that	SCONJ
aiti-13523	248	10	the	the	DET
aiti-13523	248	11	vectorization	vectorization	NOUN
aiti-13523	248	12	step	step	NOUN
aiti-13523	248	13	and	and	CCONJ
aiti-13523	248	14	the	the	DET
aiti-13523	248	15	choice	choice	NOUN
aiti-13523	248	16	of	of	ADP
aiti-13523	248	17	model	model	NOUN
aiti-13523	248	18	have	have	VERB
aiti-13523	248	19	a	a	DET
aiti-13523	248	20	significant	significant	ADJ
aiti-13523	248	21	impact	impact	NOUN
aiti-13523	248	22	on	on	ADP
aiti-13523	248	23	the	the	DET
aiti-13523	248	24	final	final	ADJ
aiti-13523	248	25	results	result	NOUN
aiti-13523	248	26	.	.	PUNCT
aiti-13523	249	1	by	by	ADP
aiti-13523	249	2	analyzing	analyze	VERB
aiti-13523	249	3	tables	table	NOUN
aiti-13523	249	4	1	1	NUM
aiti-13523	249	5	and	and	CCONJ
aiti-13523	249	6	2	2	NUM
aiti-13523	249	7	:	:	PUNCT
aiti-13523	249	8	(	(	PUNCT
aiti-13523	249	9	1	1	X
aiti-13523	249	10	)	)	PUNCT
aiti-13523	249	11	choosing	choose	VERB
aiti-13523	249	12	a	a	DET
aiti-13523	249	13	good	good	ADJ
aiti-13523	249	14	resampling	resampling	NOUN
aiti-13523	249	15	method	method	NOUN
aiti-13523	249	16	is	be	AUX
aiti-13523	249	17	important	important	ADJ
aiti-13523	249	18	to	to	PART
aiti-13523	249	19	improve	improve	VERB
aiti-13523	249	20	classification	classification	NOUN
aiti-13523	249	21	.	.	PUNCT
aiti-13523	250	1	in	in	ADP
aiti-13523	250	2	this	this	DET
aiti-13523	250	3	study	study	NOUN
aiti-13523	250	4	,	,	PUNCT
aiti-13523	250	5	naive	naive	ADJ
aiti-13523	250	6	oversampling	oversampling	NOUN
aiti-13523	250	7	gave	give	VERB
aiti-13523	250	8	the	the	DET
aiti-13523	250	9	best	good	ADJ
aiti-13523	250	10	results	result	NOUN
aiti-13523	250	11	on	on	ADP
aiti-13523	250	12	average	average	NOUN
aiti-13523	250	13	for	for	ADP
aiti-13523	250	14	the	the	DET
aiti-13523	250	15	baseline	baseline	ADJ
aiti-13523	250	16	algorithms	algorithm	NOUN
aiti-13523	250	17	and	and	CCONJ
aiti-13523	250	18	even	even	ADV
aiti-13523	250	19	the	the	DET
aiti-13523	250	20	highest	high	ADJ
aiti-13523	250	21	f1	f1	NOUN
aiti-13523	250	22	-	-	PUNCT
aiti-13523	250	23	score	score	NOUN
aiti-13523	250	24	was	be	AUX
aiti-13523	250	25	obtained	obtain	VERB
aiti-13523	250	26	using	use	VERB
aiti-13523	250	27	logistic	logistic	ADJ
aiti-13523	250	28	regression	regression	NOUN
aiti-13523	250	29	with	with	ADP
aiti-13523	250	30	tf	tf	PROPN
aiti-13523	250	31	-	-	PUNCT
aiti-13523	250	32	idf	idf	PROPN
aiti-13523	250	33	and	and	CCONJ
aiti-13523	250	34	naive	naive	ADJ
aiti-13523	250	35	oversampling	oversampling	NOUN
aiti-13523	250	36	.	.	PUNCT
aiti-13523	251	1	advances	advance	NOUN
aiti-13523	251	2	in	in	ADP
aiti-13523	251	3	technology	technology	NOUN
aiti-13523	251	4	innovation	innovation	NOUN
aiti-13523	251	5	,	,	PUNCT
aiti-13523	251	6	vol	vol	NOUN
aiti-13523	251	7	.	.	PROPN
aiti-13523	252	1	9	9	NUM
aiti-13523	252	2	,	,	PUNCT
aiti-13523	252	3	no	no	INTJ
aiti-13523	252	4	.	.	NOUN
aiti-13523	252	5	2	2	NUM
aiti-13523	252	6	,	,	PUNCT
aiti-13523	252	7	2024	2024	NUM
aiti-13523	252	8	,	,	PUNCT
aiti-13523	252	9	pp	pp	ADJ
aiti-13523	252	10	.	.	PUNCT
aiti-13523	253	1	129	129	NUM
aiti-13523	253	2	-	-	SYM
aiti-13523	253	3	142	142	NUM
aiti-13523	253	4	139	139	NUM
aiti-13523	253	5	(	(	PUNCT
aiti-13523	253	6	2	2	NUM
aiti-13523	253	7	)	)	PUNCT
aiti-13523	253	8	table	table	NOUN
aiti-13523	253	9	1	1	NUM
aiti-13523	253	10	clearly	clearly	ADV
aiti-13523	253	11	shows	show	VERB
aiti-13523	253	12	that	that	SCONJ
aiti-13523	253	13	the	the	DET
aiti-13523	253	14	logistic	logistic	ADJ
aiti-13523	253	15	regression	regression	NOUN
aiti-13523	253	16	learning	learn	VERB
aiti-13523	253	17	model	model	NOUN
aiti-13523	253	18	using	use	VERB
aiti-13523	253	19	feature	feature	NOUN
aiti-13523	253	20	selection	selection	NOUN
aiti-13523	253	21	with	with	ADP
aiti-13523	253	22	tf	tf	PROPN
aiti-13523	253	23	-	-	PUNCT
aiti-13523	253	24	idf	idf	PROPN
aiti-13523	253	25	outperformed	outperform	VERB
aiti-13523	253	26	others	other	NOUN
aiti-13523	253	27	with	with	ADP
aiti-13523	253	28	a	a	DET
aiti-13523	253	29	satisfactory	satisfactory	ADJ
aiti-13523	253	30	f1	f1	NOUN
aiti-13523	253	31	-	-	PUNCT
aiti-13523	253	32	score	score	NOUN
aiti-13523	253	33	of	of	ADP
aiti-13523	253	34	83.9	83.9	NUM
aiti-13523	253	35	%	%	NOUN
aiti-13523	253	36	when	when	SCONJ
aiti-13523	253	37	including	include	VERB
aiti-13523	253	38	the	the	DET
aiti-13523	253	39	minority	minority	NOUN
aiti-13523	253	40	class	class	NOUN
aiti-13523	253	41	in	in	ADP
aiti-13523	253	42	the	the	DET
aiti-13523	253	43	naive	naive	ADJ
aiti-13523	253	44	oversampling	oversampling	ADJ
aiti-13523	253	45	case	case	NOUN
aiti-13523	253	46	and	and	CCONJ
aiti-13523	253	47	83.1	83.1	NUM
aiti-13523	253	48	%	%	NOUN
aiti-13523	253	49	in	in	ADP
aiti-13523	253	50	the	the	DET
aiti-13523	253	51	case	case	NOUN
aiti-13523	253	52	of	of	ADP
aiti-13523	253	53	the	the	DET
aiti-13523	253	54	exclusion	exclusion	NOUN
aiti-13523	253	55	of	of	ADP
aiti-13523	253	56	minority	minority	NOUN
aiti-13523	253	57	classes	class	NOUN
aiti-13523	253	58	.	.	PUNCT
aiti-13523	254	1	these	these	DET
aiti-13523	254	2	results	result	NOUN
aiti-13523	254	3	demonstrate	demonstrate	VERB
aiti-13523	254	4	the	the	DET
aiti-13523	254	5	choice	choice	NOUN
aiti-13523	254	6	of	of	ADP
aiti-13523	254	7	using	use	VERB
aiti-13523	254	8	tf	tf	PROPN
aiti-13523	254	9	-	-	PUNCT
aiti-13523	254	10	idf	idf	PROPN
aiti-13523	254	11	is	be	AUX
aiti-13523	254	12	decisive	decisive	ADJ
aiti-13523	254	13	for	for	ADP
aiti-13523	254	14	the	the	DET
aiti-13523	254	15	improvement	improvement	NOUN
aiti-13523	254	16	of	of	ADP
aiti-13523	254	17	the	the	DET
aiti-13523	254	18	classification	classification	NOUN
aiti-13523	254	19	because	because	SCONJ
aiti-13523	254	20	even	even	ADV
aiti-13523	254	21	by	by	ADP
aiti-13523	254	22	including	include	VERB
aiti-13523	254	23	the	the	DET
aiti-13523	254	24	minority	minority	NOUN
aiti-13523	254	25	classes	class	VERB
aiti-13523	254	26	the	the	DET
aiti-13523	254	27	variation	variation	NOUN
aiti-13523	254	28	between	between	ADP
aiti-13523	254	29	the	the	DET
aiti-13523	254	30	two	two	NUM
aiti-13523	254	31	f1	f1	NOUN
aiti-13523	254	32	-	-	PUNCT
aiti-13523	254	33	scores	score	NOUN
aiti-13523	254	34	obtained	obtain	VERB
aiti-13523	254	35	is	be	AUX
aiti-13523	254	36	significant	significant	ADJ
aiti-13523	254	37	and	and	CCONJ
aiti-13523	254	38	the	the	DET
aiti-13523	254	39	result	result	NOUN
aiti-13523	254	40	remains	remain	VERB
aiti-13523	254	41	satisfactory	satisfactory	ADJ
aiti-13523	254	42	.	.	PUNCT
aiti-13523	255	1	(	(	PUNCT
aiti-13523	255	2	3	3	X
aiti-13523	255	3	)	)	PUNCT
aiti-13523	255	4	furthermore	furthermore	ADV
aiti-13523	255	5	,	,	PUNCT
aiti-13523	255	6	the	the	DET
aiti-13523	255	7	use	use	NOUN
aiti-13523	255	8	of	of	ADP
aiti-13523	255	9	the	the	DET
aiti-13523	255	10	word2vec	word2vec	PROPN
aiti-13523	255	11	model	model	NOUN
aiti-13523	255	12	does	do	AUX
aiti-13523	255	13	not	not	PART
aiti-13523	255	14	give	give	VERB
aiti-13523	255	15	satisfaction	satisfaction	NOUN
aiti-13523	255	16	,	,	PUNCT
aiti-13523	255	17	especially	especially	ADV
aiti-13523	255	18	in	in	ADP
aiti-13523	255	19	the	the	DET
aiti-13523	255	20	case	case	NOUN
aiti-13523	255	21	of	of	ADP
aiti-13523	255	22	the	the	DET
aiti-13523	255	23	exclusion	exclusion	NOUN
aiti-13523	255	24	of	of	ADP
aiti-13523	255	25	minority	minority	NOUN
aiti-13523	255	26	classes	class	NOUN
aiti-13523	255	27	.	.	PUNCT
aiti-13523	256	1	it	it	PRON
aiti-13523	256	2	seems	seem	VERB
aiti-13523	256	3	obvious	obvious	ADJ
aiti-13523	256	4	that	that	SCONJ
aiti-13523	256	5	the	the	DET
aiti-13523	256	6	model	model	NOUN
aiti-13523	256	7	does	do	AUX
aiti-13523	256	8	not	not	PART
aiti-13523	256	9	manage	manage	VERB
aiti-13523	256	10	to	to	PART
aiti-13523	256	11	select	select	VERB
aiti-13523	256	12	the	the	DET
aiti-13523	256	13	right	right	ADJ
aiti-13523	256	14	characteristics	characteristic	NOUN
aiti-13523	256	15	of	of	ADP
aiti-13523	256	16	words	word	NOUN
aiti-13523	256	17	which	which	PRON
aiti-13523	256	18	leads	lead	VERB
aiti-13523	256	19	to	to	ADP
aiti-13523	256	20	wrong	wrong	ADJ
aiti-13523	256	21	classification	classification	NOUN
aiti-13523	256	22	.	.	PUNCT
aiti-13523	257	1	(	(	PUNCT
aiti-13523	257	2	4	4	X
aiti-13523	257	3	)	)	PUNCT
aiti-13523	257	4	the	the	DET
aiti-13523	257	5	logistic	logistic	ADJ
aiti-13523	257	6	regression	regression	NOUN
aiti-13523	257	7	model	model	NOUN
aiti-13523	257	8	based	base	VERB
aiti-13523	257	9	on	on	ADP
aiti-13523	257	10	word2vec	word2vec	PRON
aiti-13523	257	11	has	have	AUX
aiti-13523	257	12	obtained	obtain	VERB
aiti-13523	257	13	the	the	DET
aiti-13523	257	14	worst	bad	ADJ
aiti-13523	257	15	result	result	NOUN
aiti-13523	257	16	in	in	ADP
aiti-13523	257	17	terms	term	NOUN
aiti-13523	257	18	of	of	ADP
aiti-13523	257	19	f1	f1	NOUN
aiti-13523	257	20	-	-	PUNCT
aiti-13523	257	21	score	score	NOUN
aiti-13523	257	22	,	,	PUNCT
aiti-13523	257	23	an	an	DET
aiti-13523	257	24	explanation	explanation	NOUN
aiti-13523	257	25	of	of	ADP
aiti-13523	257	26	these	these	DET
aiti-13523	257	27	predictions	prediction	NOUN
aiti-13523	257	28	is	be	AUX
aiti-13523	257	29	in	in	ADP
aiti-13523	257	30	the	the	DET
aiti-13523	257	31	following	follow	VERB
aiti-13523	257	32	section	section	NOUN
aiti-13523	257	33	.	.	PUNCT
aiti-13523	258	1	looking	look	VERB
aiti-13523	258	2	to	to	PART
aiti-13523	258	3	further	far	ADV
aiti-13523	258	4	,	,	PUNCT
aiti-13523	258	5	improve	improve	VERB
aiti-13523	258	6	the	the	DET
aiti-13523	258	7	classification	classification	NOUN
aiti-13523	258	8	score	score	NOUN
aiti-13523	258	9	has	have	AUX
aiti-13523	258	10	been	be	AUX
aiti-13523	258	11	obtained	obtain	VERB
aiti-13523	258	12	using	use	VERB
aiti-13523	258	13	lstm	lstm	NOUN
aiti-13523	258	14	and	and	CCONJ
aiti-13523	258	15	bert	bert	PROPN
aiti-13523	258	16	.	.	PUNCT
aiti-13523	259	1	as	as	SCONJ
aiti-13523	259	2	observed	observe	VERB
aiti-13523	259	3	in	in	ADP
aiti-13523	259	4	table	table	NOUN
aiti-13523	259	5	3	3	NUM
aiti-13523	259	6	,	,	PUNCT
aiti-13523	259	7	the	the	DET
aiti-13523	259	8	f1	f1	NOUN
aiti-13523	259	9	-	-	PUNCT
aiti-13523	259	10	scores	score	NOUN
aiti-13523	259	11	obtained	obtain	VERB
aiti-13523	259	12	by	by	ADP
aiti-13523	259	13	the	the	DET
aiti-13523	259	14	lstm	lstm	PROPN
aiti-13523	259	15	and	and	CCONJ
aiti-13523	259	16	bert	bert	PROPN
aiti-13523	259	17	models	model	NOUN
aiti-13523	259	18	after	after	ADP
aiti-13523	259	19	oversampling	oversample	VERB
aiti-13523	259	20	the	the	DET
aiti-13523	259	21	data	datum	NOUN
aiti-13523	259	22	,	,	PUNCT
aiti-13523	259	23	with	with	ADP
aiti-13523	259	24	or	or	CCONJ
aiti-13523	259	25	without	without	ADP
aiti-13523	259	26	minor	minor	ADJ
aiti-13523	259	27	classes	class	NOUN
aiti-13523	259	28	were	be	AUX
aiti-13523	259	29	similar	similar	ADJ
aiti-13523	259	30	.	.	PUNCT
aiti-13523	260	1	the	the	DET
aiti-13523	260	2	best	good	ADJ
aiti-13523	260	3	f1	f1	NOUN
aiti-13523	260	4	-	-	PUNCT
aiti-13523	260	5	score	score	NOUN
aiti-13523	260	6	of	of	ADP
aiti-13523	260	7	89	89	NUM
aiti-13523	260	8	%	%	NOUN
aiti-13523	260	9	was	be	AUX
aiti-13523	260	10	obtained	obtain	VERB
aiti-13523	260	11	with	with	ADP
aiti-13523	260	12	bert	bert	PROPN
aiti-13523	260	13	and	and	CCONJ
aiti-13523	260	14	lstm	lstm	NOUN
aiti-13523	260	15	models	model	NOUN
aiti-13523	260	16	with	with	ADP
aiti-13523	260	17	oversampling	oversample	VERB
aiti-13523	260	18	and	and	CCONJ
aiti-13523	260	19	exclusion	exclusion	NOUN
aiti-13523	260	20	of	of	ADP
aiti-13523	260	21	minority	minority	NOUN
aiti-13523	260	22	classes	class	NOUN
aiti-13523	260	23	.	.	PUNCT
aiti-13523	261	1	overall	overall	ADV
aiti-13523	261	2	,	,	PUNCT
aiti-13523	261	3	both	both	CCONJ
aiti-13523	261	4	the	the	DET
aiti-13523	261	5	lstm	lstm	PROPN
aiti-13523	261	6	and	and	CCONJ
aiti-13523	261	7	bert	bert	PROPN
aiti-13523	261	8	models	model	NOUN
aiti-13523	261	9	gave	give	VERB
aiti-13523	261	10	better	well	ADJ
aiti-13523	261	11	performance	performance	NOUN
aiti-13523	261	12	than	than	ADP
aiti-13523	261	13	the	the	DET
aiti-13523	261	14	baseline	baseline	NOUN
aiti-13523	261	15	models	model	NOUN
aiti-13523	261	16	.	.	PUNCT
aiti-13523	262	1	however	however	ADV
aiti-13523	262	2	,	,	PUNCT
aiti-13523	262	3	the	the	DET
aiti-13523	262	4	bert	bert	PROPN
aiti-13523	262	5	model	model	NOUN
aiti-13523	262	6	outperformed	outperform	VERB
aiti-13523	262	7	other	other	ADJ
aiti-13523	262	8	models	model	NOUN
aiti-13523	262	9	even	even	ADV
aiti-13523	262	10	when	when	SCONJ
aiti-13523	262	11	classifying	classify	VERB
aiti-13523	262	12	imbalanced	imbalanced	ADJ
aiti-13523	262	13	data	datum	NOUN
aiti-13523	262	14	without	without	ADP
aiti-13523	262	15	resampling	resample	VERB
aiti-13523	262	16	,	,	PUNCT
aiti-13523	262	17	achieving	achieve	VERB
aiti-13523	262	18	an	an	DET
aiti-13523	262	19	f1	f1	NOUN
aiti-13523	262	20	-	-	PUNCT
aiti-13523	262	21	score	score	NOUN
aiti-13523	262	22	of	of	ADP
aiti-13523	262	23	57	57	NUM
aiti-13523	262	24	%	%	NOUN
aiti-13523	262	25	.	.	PUNCT
aiti-13523	263	1	the	the	DET
aiti-13523	263	2	negative	negative	ADJ
aiti-13523	263	3	point	point	NOUN
aiti-13523	263	4	observed	observe	VERB
aiti-13523	263	5	about	about	ADP
aiti-13523	263	6	the	the	DET
aiti-13523	263	7	execution	execution	NOUN
aiti-13523	263	8	of	of	ADP
aiti-13523	263	9	deep	deep	ADJ
aiti-13523	263	10	learning	learning	NOUN
aiti-13523	263	11	models	model	NOUN
aiti-13523	263	12	is	be	AUX
aiti-13523	263	13	that	that	SCONJ
aiti-13523	263	14	they	they	PRON
aiti-13523	263	15	are	be	AUX
aiti-13523	263	16	very	very	ADV
aiti-13523	263	17	time	time	NOUN
aiti-13523	263	18	-	-	PUNCT
aiti-13523	263	19	consuming	consume	VERB
aiti-13523	263	20	.	.	PUNCT
aiti-13523	264	1	in	in	ADP
aiti-13523	264	2	particular	particular	ADJ
aiti-13523	264	3	,	,	PUNCT
aiti-13523	264	4	the	the	DET
aiti-13523	264	5	bert	bert	PROPN
aiti-13523	264	6	model	model	NOUN
aiti-13523	264	7	took	take	VERB
aiti-13523	264	8	an	an	DET
aiti-13523	264	9	average	average	NOUN
aiti-13523	264	10	of	of	ADP
aiti-13523	264	11	6	6	NUM
aiti-13523	264	12	hours	hour	NOUN
aiti-13523	264	13	to	to	PART
aiti-13523	264	14	execute	execute	VERB
aiti-13523	264	15	compared	compare	VERB
aiti-13523	264	16	to	to	ADP
aiti-13523	264	17	the	the	DET
aiti-13523	264	18	lstm	lstm	PROPN
aiti-13523	264	19	model	model	NOUN
aiti-13523	264	20	,	,	PUNCT
aiti-13523	264	21	which	which	PRON
aiti-13523	264	22	took	take	VERB
aiti-13523	264	23	1	1	NUM
aiti-13523	264	24	hour	hour	NOUN
aiti-13523	264	25	on	on	ADP
aiti-13523	264	26	average	average	ADJ
aiti-13523	264	27	.	.	PUNCT
aiti-13523	265	1	in	in	ADP
aiti-13523	265	2	contrast	contrast	NOUN
aiti-13523	265	3	,	,	PUNCT
aiti-13523	265	4	the	the	DET
aiti-13523	265	5	base	base	NOUN
aiti-13523	265	6	models	model	NOUN
aiti-13523	265	7	were	be	AUX
aiti-13523	265	8	the	the	DET
aiti-13523	265	9	fastest	fast	ADJ
aiti-13523	265	10	;	;	PUNCT
aiti-13523	265	11	with	with	ADP
aiti-13523	265	12	an	an	DET
aiti-13523	265	13	average	average	ADJ
aiti-13523	265	14	execution	execution	NOUN
aiti-13523	265	15	time	time	NOUN
aiti-13523	265	16	of	of	ADP
aiti-13523	265	17	40	40	NUM
aiti-13523	265	18	seconds	second	NOUN
aiti-13523	265	19	.	.	PUNCT
aiti-13523	266	1	despite	despite	SCONJ
aiti-13523	266	2	the	the	PRON
aiti-13523	266	3	despite	despite	SCONJ
aiti-13523	266	4	the	the	DET
aiti-13523	266	5	timeconsuming	timeconsuming	ADJ
aiti-13523	266	6	nature	nature	NOUN
aiti-13523	266	7	of	of	ADP
aiti-13523	266	8	the	the	DET
aiti-13523	266	9	execution	execution	NOUN
aiti-13523	266	10	,	,	PUNCT
aiti-13523	266	11	the	the	DET
aiti-13523	266	12	classification	classification	NOUN
aiti-13523	266	13	models	model	NOUN
aiti-13523	266	14	used	use	VERB
aiti-13523	266	15	in	in	ADP
aiti-13523	266	16	this	this	DET
aiti-13523	266	17	study	study	NOUN
aiti-13523	266	18	particularly	particularly	ADV
aiti-13523	266	19	lstm	lstm	NOUN
aiti-13523	266	20	and	and	CCONJ
aiti-13523	266	21	bert	bert	PROPN
aiti-13523	266	22	,	,	PUNCT
aiti-13523	266	23	achieved	achieve	VERB
aiti-13523	266	24	satisfactory	satisfactory	ADJ
aiti-13523	266	25	results	result	NOUN
aiti-13523	266	26	in	in	ADP
aiti-13523	266	27	terms	term	NOUN
aiti-13523	266	28	of	of	ADP
aiti-13523	266	29	f1	f1	NOUN
aiti-13523	266	30	-	-	PUNCT
aiti-13523	266	31	score	score	NOUN
aiti-13523	266	32	,	,	PUNCT
aiti-13523	266	33	comparing	compare	VERB
aiti-13523	266	34	them	they	PRON
aiti-13523	266	35	to	to	ADP
aiti-13523	266	36	the	the	DET
aiti-13523	266	37	models	model	NOUN
aiti-13523	266	38	proposed	propose	VERB
aiti-13523	266	39	in	in	ADP
aiti-13523	266	40	the	the	DET
aiti-13523	266	41	literature	literature	NOUN
aiti-13523	266	42	.	.	PUNCT
aiti-13523	267	1	table	table	NOUN
aiti-13523	267	2	4	4	NUM
aiti-13523	267	3	shows	show	VERB
aiti-13523	267	4	us	we	PRON
aiti-13523	267	5	the	the	DET
aiti-13523	267	6	different	different	ADJ
aiti-13523	267	7	f1	f1	ADJ
aiti-13523	267	8	-	-	PUNCT
aiti-13523	267	9	score	score	NOUN
aiti-13523	267	10	measurements	measurement	NOUN
aiti-13523	267	11	obtained	obtain	VERB
aiti-13523	267	12	by	by	ADP
aiti-13523	267	13	other	other	ADJ
aiti-13523	267	14	models	model	NOUN
aiti-13523	267	15	on	on	ADP
aiti-13523	267	16	the	the	DET
aiti-13523	267	17	emohd	emohd	NOUN
aiti-13523	267	18	database	database	NOUN
aiti-13523	267	19	,	,	PUNCT
aiti-13523	267	20	but	but	CCONJ
aiti-13523	267	21	also	also	ADV
aiti-13523	267	22	on	on	ADP
aiti-13523	267	23	other	other	ADJ
aiti-13523	267	24	works	work	NOUN
aiti-13523	267	25	using	use	VERB
aiti-13523	267	26	recurrent	recurrent	ADJ
aiti-13523	267	27	deep	deep	ADJ
aiti-13523	267	28	learning	learning	NOUN
aiti-13523	267	29	models	model	NOUN
aiti-13523	267	30	on	on	ADP
aiti-13523	267	31	other	other	ADJ
aiti-13523	267	32	textual	textual	ADJ
aiti-13523	267	33	databases	database	NOUN
aiti-13523	267	34	.	.	PUNCT
aiti-13523	268	1	table	table	NOUN
aiti-13523	268	2	4	4	NUM
aiti-13523	268	3	f1	f1	NOUN
aiti-13523	268	4	-	-	PUNCT
aiti-13523	268	5	score	score	NOUN
aiti-13523	268	6	of	of	ADP
aiti-13523	268	7	related	related	ADJ
aiti-13523	268	8	works	work	NOUN
aiti-13523	268	9	database	database	NOUN
aiti-13523	268	10	approach	approach	NOUN
aiti-13523	268	11	f1	f1	NOUN
aiti-13523	268	12	-	-	PUNCT
aiti-13523	268	13	score	score	NOUN
aiti-13523	268	14	emohd	emohd	NOUN
aiti-13523	268	15	this	this	DET
aiti-13523	268	16	approach	approach	NOUN
aiti-13523	268	17	with	with	ADP
aiti-13523	268	18	the	the	DET
aiti-13523	268	19	lstm	lstm	PROPN
aiti-13523	268	20	and	and	CCONJ
aiti-13523	268	21	bert	bert	PROPN
aiti-13523	268	22	model	model	NOUN
aiti-13523	268	23	89	89	NUM
aiti-13523	268	24	%	%	NOUN
aiti-13523	268	25	multi	multi	ADJ
aiti-13523	268	26	-	-	ADJ
aiti-13523	268	27	layered	layered	ADJ
aiti-13523	268	28	perceptron	perceptron	NOUN
aiti-13523	269	1	[	[	X
aiti-13523	269	2	1	1	NUM
aiti-13523	269	3	]	]	PUNCT
aiti-13523	269	4	87	87	NUM
aiti-13523	269	5	%	%	NOUN
aiti-13523	269	6	back	back	ADJ
aiti-13523	269	7	-	-	PUNCT
aiti-13523	269	8	propagation	propagation	NOUN
aiti-13523	269	9	neural	neural	ADJ
aiti-13523	269	10	network	network	NOUN
aiti-13523	269	11	(	(	PUNCT
aiti-13523	269	12	bpnn	bpnn	NOUN
aiti-13523	269	13	)	)	PUNCT
aiti-13523	269	14	based	base	VERB
aiti-13523	269	15	intelligent	intelligent	ADJ
aiti-13523	269	16	water	water	NOUN
aiti-13523	269	17	drop	drop	NOUN
aiti-13523	269	18	algorithm	algorithm	NOUN
aiti-13523	269	19	[	[	X
aiti-13523	269	20	14	14	NUM
aiti-13523	269	21	]	]	SYM
aiti-13523	269	22	96	96	NUM
aiti-13523	269	23	%	%	NOUN
aiti-13523	269	24	another	another	DET
aiti-13523	269	25	textual	textual	ADJ
aiti-13523	269	26	database	database	NOUN
aiti-13523	269	27	using	use	VERB
aiti-13523	269	28	recurrent	recurrent	ADJ
aiti-13523	269	29	deep	deep	ADJ
aiti-13523	269	30	learning	learn	VERB
aiti-13523	269	31	bi	bi	NOUN
aiti-13523	269	32	-	-	NOUN
aiti-13523	269	33	lstm	lstm	ADJ
aiti-13523	269	34	[	[	X
aiti-13523	269	35	10	10	NUM
aiti-13523	269	36	]	]	SYM
aiti-13523	269	37	94	94	NUM
aiti-13523	269	38	%	%	NOUN
aiti-13523	269	39	cnn	cnn	PROPN
aiti-13523	270	1	+	+	CCONJ
aiti-13523	270	2	lstm	lstm	NOUN
aiti-13523	270	3	[	[	X
aiti-13523	270	4	11	11	NUM
aiti-13523	270	5	]	]	SYM
aiti-13523	270	6	95	95	NUM
aiti-13523	270	7	%	%	NOUN
aiti-13523	270	8	bert	bert	NOUN
aiti-13523	270	9	+	+	CCONJ
aiti-13523	270	10	nbsvm	nbsvm	NOUN
aiti-13523	270	11	[	[	X
aiti-13523	270	12	13	13	NUM
aiti-13523	270	13	]	]	SYM
aiti-13523	270	14	73	73	NUM
aiti-13523	270	15	%	%	NOUN
aiti-13523	270	16	table	table	NOUN
aiti-13523	270	17	4	4	NUM
aiti-13523	270	18	highlights	highlight	NOUN
aiti-13523	270	19	that	that	PRON
aiti-13523	270	20	the	the	DET
aiti-13523	270	21	classification	classification	NOUN
aiti-13523	270	22	results	result	NOUN
aiti-13523	270	23	obtained	obtain	VERB
aiti-13523	270	24	by	by	ADP
aiti-13523	270	25	this	this	DET
aiti-13523	270	26	bert	bert	PROPN
aiti-13523	270	27	and	and	CCONJ
aiti-13523	270	28	lstm	lstm	NOUN
aiti-13523	270	29	models	model	NOUN
aiti-13523	270	30	outperformed	outperform	VERB
aiti-13523	270	31	the	the	DET
aiti-13523	270	32	multilayer	multilayer	ADJ
aiti-13523	270	33	perceptron	perceptron	PROPN
aiti-13523	270	34	implemented	implement	VERB
aiti-13523	270	35	by	by	ADP
aiti-13523	270	36	azam	azam	PROPN
aiti-13523	270	37	et	et	PROPN
aiti-13523	270	38	al	al	PROPN
aiti-13523	270	39	.	.	PUNCT
aiti-13523	271	1	[	[	X
aiti-13523	271	2	4	4	NUM
aiti-13523	271	3	]	]	PUNCT
aiti-13523	271	4	.	.	PUNCT
aiti-13523	272	1	although	although	SCONJ
aiti-13523	272	2	these	these	DET
aiti-13523	272	3	results	result	NOUN
aiti-13523	272	4	are	be	AUX
aiti-13523	272	5	satisfactory	satisfactory	ADJ
aiti-13523	272	6	,	,	PUNCT
aiti-13523	272	7	they	they	PRON
aiti-13523	272	8	remain	remain	VERB
aiti-13523	272	9	lower	low	ADJ
aiti-13523	272	10	than	than	ADP
aiti-13523	272	11	those	those	PRON
aiti-13523	272	12	of	of	ADP
aiti-13523	272	13	the	the	DET
aiti-13523	272	14	intelligent	intelligent	ADJ
aiti-13523	272	15	water	water	NOUN
aiti-13523	272	16	drop	drop	NOUN
aiti-13523	272	17	algorithm	algorithm	NOUN
aiti-13523	272	18	based	base	VERB
aiti-13523	272	19	on	on	ADP
aiti-13523	272	20	the	the	DET
aiti-13523	272	21	back	back	ADJ
aiti-13523	272	22	-	-	PUNCT
aiti-13523	272	23	propagation	propagation	NOUN
aiti-13523	272	24	neural	neural	ADJ
aiti-13523	272	25	network	network	NOUN
aiti-13523	272	26	(	(	PUNCT
aiti-13523	272	27	bpnn	bpnn	NOUN
aiti-13523	272	28	)	)	PUNCT
aiti-13523	272	29	model	model	NOUN
aiti-13523	272	30	[	[	X
aiti-13523	272	31	14	14	NUM
aiti-13523	272	32	]	]	PUNCT
aiti-13523	272	33	.	.	PUNCT
aiti-13523	273	1	it	it	PRON
aiti-13523	273	2	seems	seem	VERB
aiti-13523	273	3	obvious	obvious	ADJ
aiti-13523	273	4	that	that	SCONJ
aiti-13523	273	5	using	use	VERB
aiti-13523	273	6	the	the	DET
aiti-13523	273	7	intelligent	intelligent	ADJ
aiti-13523	273	8	water	water	NOUN
aiti-13523	273	9	drop	drop	NOUN
aiti-13523	273	10	algorithm	algorithm	NOUN
aiti-13523	273	11	for	for	ADP
aiti-13523	273	12	feature	feature	NOUN
aiti-13523	273	13	selection	selection	NOUN
aiti-13523	273	14	optimization	optimization	NOUN
aiti-13523	273	15	made	make	VERB
aiti-13523	273	16	a	a	DET
aiti-13523	273	17	difference	difference	NOUN
aiti-13523	273	18	and	and	CCONJ
aiti-13523	273	19	significantly	significantly	ADV
aiti-13523	273	20	improved	improve	VERB
aiti-13523	273	21	the	the	DET
aiti-13523	273	22	classification	classification	NOUN
aiti-13523	273	23	result	result	NOUN
aiti-13523	273	24	.	.	PUNCT
aiti-13523	274	1	compared	compare	VERB
aiti-13523	274	2	to	to	ADP
aiti-13523	274	3	the	the	DET
aiti-13523	274	4	results	result	NOUN
aiti-13523	274	5	of	of	ADP
aiti-13523	274	6	related	related	ADJ
aiti-13523	274	7	works	work	NOUN
aiti-13523	274	8	on	on	ADP
aiti-13523	274	9	different	different	ADJ
aiti-13523	274	10	text	text	NOUN
aiti-13523	274	11	databases	database	NOUN
aiti-13523	274	12	these	these	DET
aiti-13523	274	13	transformer	transformer	NOUN
aiti-13523	274	14	models	model	NOUN
aiti-13523	274	15	were	be	AUX
aiti-13523	274	16	more	more	ADV
aiti-13523	274	17	efficient	efficient	ADJ
aiti-13523	274	18	than	than	ADP
aiti-13523	274	19	those	those	PRON
aiti-13523	274	20	in	in	ADP
aiti-13523	274	21	umair	umair	NOUN
aiti-13523	274	22	et	et	PROPN
aiti-13523	274	23	al	al	PROPN
aiti-13523	274	24	.	.	PUNCT
aiti-13523	275	1	[	[	X
aiti-13523	275	2	13	13	NUM
aiti-13523	275	3	]	]	PUNCT
aiti-13523	275	4	,	,	PUNCT
aiti-13523	275	5	which	which	PRON
aiti-13523	275	6	only	only	ADV
aiti-13523	275	7	obtained	obtain	VERB
aiti-13523	275	8	an	an	DET
aiti-13523	275	9	f1	f1	NOUN
aiti-13523	275	10	-	-	PUNCT
aiti-13523	275	11	score	score	NOUN
aiti-13523	275	12	of	of	ADP
aiti-13523	275	13	73	73	NUM
aiti-13523	275	14	%	%	NOUN
aiti-13523	275	15	,	,	PUNCT
aiti-13523	275	16	also	also	ADV
aiti-13523	275	17	,	,	PUNCT
aiti-13523	275	18	recurrent	recurrent	ADJ
aiti-13523	275	19	lstm	lstm	NOUN
aiti-13523	275	20	models	model	NOUN
aiti-13523	275	21	used	use	VERB
aiti-13523	275	22	by	by	ADP
aiti-13523	275	23	tan	tan	PROPN
aiti-13523	275	24	et	et	PROPN
aiti-13523	275	25	al	al	PROPN
aiti-13523	275	26	.	.	PUNCT
aiti-13523	276	1	[	[	X
aiti-13523	276	2	10	10	NUM
aiti-13523	276	3	]	]	PUNCT
aiti-13523	276	4	,	,	PUNCT
aiti-13523	276	5	and	and	CCONJ
aiti-13523	276	6	meena	meena	PROPN
aiti-13523	276	7	et	et	PROPN
aiti-13523	276	8	al	al	PROPN
aiti-13523	276	9	.	.	PUNCT
aiti-13523	277	1	[	[	X
aiti-13523	277	2	11	11	NUM
aiti-13523	277	3	]	]	PUNCT
aiti-13523	277	4	were	be	AUX
aiti-13523	277	5	very	very	ADV
aiti-13523	277	6	successful	successful	ADJ
aiti-13523	277	7	with	with	ADP
aiti-13523	277	8	f1	f1	NOUN
aiti-13523	277	9	-	-	PUNCT
aiti-13523	277	10	scores	score	NOUN
aiti-13523	277	11	of	of	ADP
aiti-13523	277	12	94	94	NUM
aiti-13523	277	13	%	%	NOUN
aiti-13523	277	14	and	and	CCONJ
aiti-13523	277	15	95	95	NUM
aiti-13523	277	16	%	%	NOUN
aiti-13523	277	17	,	,	PUNCT
aiti-13523	277	18	these	these	DET
aiti-13523	277	19	results	result	NOUN
aiti-13523	277	20	which	which	PRON
aiti-13523	277	21	exceed	exceed	VERB
aiti-13523	277	22	this	this	DET
aiti-13523	277	23	study	study	NOUN
aiti-13523	277	24	are	be	AUX
aiti-13523	277	25	encouraging	encouraging	ADJ
aiti-13523	277	26	regarding	regard	VERB
aiti-13523	277	27	the	the	DET
aiti-13523	277	28	usability	usability	NOUN
aiti-13523	277	29	and	and	CCONJ
aiti-13523	277	30	performance	performance	NOUN
aiti-13523	277	31	of	of	ADP
aiti-13523	277	32	recursive	recursive	ADJ
aiti-13523	277	33	neural	neural	ADJ
aiti-13523	277	34	networks	network	NOUN
aiti-13523	277	35	in	in	ADP
aiti-13523	277	36	classification	classification	NOUN
aiti-13523	277	37	feelings	feeling	NOUN
aiti-13523	277	38	from	from	ADP
aiti-13523	277	39	textual	textual	ADJ
aiti-13523	277	40	data	datum	NOUN
aiti-13523	277	41	.	.	PUNCT
aiti-13523	278	1	4.6	4.6	NUM
aiti-13523	278	2	.	.	PUNCT
aiti-13523	279	1	classification	classification	NOUN
aiti-13523	279	2	diagnostic	diagnostic	ADJ
aiti-13523	279	3	as	as	SCONJ
aiti-13523	279	4	shown	show	VERB
aiti-13523	279	5	in	in	ADP
aiti-13523	279	6	table	table	NOUN
aiti-13523	279	7	1	1	NUM
aiti-13523	279	8	,	,	PUNCT
aiti-13523	279	9	the	the	DET
aiti-13523	279	10	results	result	NOUN
aiti-13523	279	11	obtained	obtain	VERB
aiti-13523	279	12	by	by	ADP
aiti-13523	279	13	the	the	DET
aiti-13523	279	14	basic	basic	ADJ
aiti-13523	279	15	logistic	logistic	ADJ
aiti-13523	279	16	regression	regression	NOUN
aiti-13523	279	17	machine	machine	NOUN
aiti-13523	279	18	learning	learn	VERB
aiti-13523	279	19	model	model	NOUN
aiti-13523	279	20	with	with	ADP
aiti-13523	279	21	the	the	DET
aiti-13523	279	22	word2vec	word2vec	PROPN
aiti-13523	279	23	method	method	NOUN
aiti-13523	279	24	are	be	AUX
aiti-13523	279	25	not	not	PART
aiti-13523	279	26	satisfactory	satisfactory	ADJ
aiti-13523	279	27	,	,	PUNCT
aiti-13523	279	28	the	the	DET
aiti-13523	279	29	f1	f1	NOUN
aiti-13523	279	30	-	-	PUNCT
aiti-13523	279	31	score	score	NOUN
aiti-13523	279	32	obtained	obtain	VERB
aiti-13523	279	33	was	be	AUX
aiti-13523	279	34	the	the	DET
aiti-13523	279	35	worst	bad	ADJ
aiti-13523	279	36	of	of	ADP
aiti-13523	279	37	all	all	PRON
aiti-13523	279	38	.	.	PUNCT
aiti-13523	280	1	to	to	PART
aiti-13523	280	2	explain	explain	VERB
aiti-13523	280	3	these	these	DET
aiti-13523	280	4	classification	classification	NOUN
aiti-13523	280	5	results	result	NOUN
aiti-13523	280	6	,	,	PUNCT
aiti-13523	280	7	it	it	PRON
aiti-13523	280	8	is	be	AUX
aiti-13523	280	9	relevant	relevant	ADJ
aiti-13523	280	10	to	to	ADP
aiti-13523	280	11	140	140	NUM
aiti-13523	280	12	advances	advance	NOUN
aiti-13523	280	13	in	in	ADP
aiti-13523	280	14	technology	technology	NOUN
aiti-13523	280	15	innovation	innovation	NOUN
aiti-13523	280	16	,	,	PUNCT
aiti-13523	280	17	vol	vol	NOUN
aiti-13523	280	18	.	.	PROPN
aiti-13523	281	1	9	9	NUM
aiti-13523	281	2	,	,	PUNCT
aiti-13523	281	3	no	no	INTJ
aiti-13523	281	4	.	.	NOUN
aiti-13523	281	5	2	2	NUM
aiti-13523	281	6	,	,	PUNCT
aiti-13523	281	7	2024	2024	NUM
aiti-13523	281	8	,	,	PUNCT
aiti-13523	281	9	pp	pp	ADJ
aiti-13523	281	10	.	.	PUNCT
aiti-13523	282	1	129	129	NUM
aiti-13523	282	2	-	-	SYM
aiti-13523	282	3	142	142	NUM
aiti-13523	282	4	understand	understand	VERB
aiti-13523	282	5	how	how	SCONJ
aiti-13523	282	6	these	these	DET
aiti-13523	282	7	classifications	classification	NOUN
aiti-13523	282	8	are	be	AUX
aiti-13523	282	9	made	make	VERB
aiti-13523	282	10	,	,	PUNCT
aiti-13523	282	11	so	so	ADV
aiti-13523	282	12	,	,	PUNCT
aiti-13523	282	13	the	the	DET
aiti-13523	282	14	lime	lime	NOUN
aiti-13523	282	15	model	model	NOUN
aiti-13523	282	16	is	be	AUX
aiti-13523	282	17	used	use	VERB
aiti-13523	282	18	to	to	PART
aiti-13523	282	19	see	see	VERB
aiti-13523	282	20	how	how	SCONJ
aiti-13523	282	21	the	the	DET
aiti-13523	282	22	predictions	prediction	NOUN
aiti-13523	282	23	of	of	ADP
aiti-13523	282	24	the	the	DET
aiti-13523	282	25	logistic	logistic	ADJ
aiti-13523	282	26	regression	regression	NOUN
aiti-13523	282	27	model	model	NOUN
aiti-13523	282	28	with	with	ADP
aiti-13523	282	29	word2vec	word2vec	PRON
aiti-13523	282	30	on	on	ADP
aiti-13523	282	31	the	the	DET
aiti-13523	282	32	emohd	emohd	NOUN
aiti-13523	282	33	database	database	NOUN
aiti-13523	282	34	were	be	AUX
aiti-13523	282	35	influenced	influence	VERB
aiti-13523	282	36	.	.	PUNCT
aiti-13523	283	1	for	for	ADP
aiti-13523	283	2	this	this	DET
aiti-13523	283	3	evaluation	evaluation	NOUN
aiti-13523	283	4	,	,	PUNCT
aiti-13523	283	5	a	a	DET
aiti-13523	283	6	selected	select	VERB
aiti-13523	283	7	of	of	ADP
aiti-13523	283	8	two	two	NUM
aiti-13523	283	9	classes	class	NOUN
aiti-13523	283	10	representing	represent	VERB
aiti-13523	283	11	opposite	opposite	ADJ
aiti-13523	283	12	feelings	feeling	NOUN
aiti-13523	283	13	:	:	PUNCT
aiti-13523	283	14	“	"	PUNCT
aiti-13523	283	15	sad	sad	ADJ
aiti-13523	283	16	”	"	PUNCT
aiti-13523	283	17	and	and	CCONJ
aiti-13523	283	18	“	"	PUNCT
aiti-13523	283	19	happy	happy	ADJ
aiti-13523	283	20	”	"	PUNCT
aiti-13523	283	21	.	.	PUNCT
aiti-13523	284	1	fig	fig	NOUN
aiti-13523	284	2	.	.	PUNCT
aiti-13523	285	1	5	5	NUM
aiti-13523	285	2	shows	show	VERB
aiti-13523	285	3	the	the	DET
aiti-13523	285	4	most	most	ADV
aiti-13523	285	5	important	important	ADJ
aiti-13523	285	6	words	word	NOUN
aiti-13523	285	7	deemed	deem	VERB
aiti-13523	285	8	relevant	relevant	ADJ
aiti-13523	285	9	or	or	CCONJ
aiti-13523	285	10	not	not	PART
aiti-13523	285	11	for	for	ADP
aiti-13523	285	12	these	these	DET
aiti-13523	285	13	two	two	NUM
aiti-13523	285	14	classes	class	NOUN
aiti-13523	285	15	.	.	PUNCT
aiti-13523	286	1	fig	fig	NOUN
aiti-13523	286	2	.	.	PUNCT
aiti-13523	287	1	5	5	NUM
aiti-13523	287	2	most	most	ADV
aiti-13523	287	3	important	important	ADJ
aiti-13523	287	4	words	word	NOUN
aiti-13523	287	5	for	for	ADP
aiti-13523	287	6	happy	happy	ADJ
aiti-13523	287	7	and	and	CCONJ
aiti-13523	287	8	sad	sad	ADJ
aiti-13523	287	9	class	class	NOUN
aiti-13523	287	10	it	it	PRON
aiti-13523	287	11	can	can	AUX
aiti-13523	287	12	be	be	AUX
aiti-13523	287	13	noted	note	VERB
aiti-13523	287	14	that	that	SCONJ
aiti-13523	287	15	the	the	DET
aiti-13523	287	16	category	category	NOUN
aiti-13523	287	17	of	of	ADP
aiti-13523	287	18	“	"	PUNCT
aiti-13523	287	19	happy	happy	ADJ
aiti-13523	287	20	”	"	PUNCT
aiti-13523	287	21	feelings	feeling	NOUN
aiti-13523	287	22	should	should	AUX
aiti-13523	287	23	be	be	AUX
aiti-13523	287	24	expressed	express	VERB
aiti-13523	287	25	through	through	ADP
aiti-13523	287	26	words	word	NOUN
aiti-13523	287	27	that	that	PRON
aiti-13523	287	28	evoke	evoke	VERB
aiti-13523	287	29	feelings	feeling	NOUN
aiti-13523	287	30	of	of	ADP
aiti-13523	287	31	joy	joy	NOUN
aiti-13523	287	32	and	and	CCONJ
aiti-13523	287	33	happiness	happiness	NOUN
aiti-13523	287	34	.	.	PUNCT
aiti-13523	288	1	relevant	relevant	ADJ
aiti-13523	288	2	terms	term	NOUN
aiti-13523	288	3	in	in	ADP
aiti-13523	288	4	this	this	DET
aiti-13523	288	5	class	class	NOUN
aiti-13523	288	6	include	include	VERB
aiti-13523	288	7	“	"	PUNCT
aiti-13523	288	8	pink	pink	ADJ
aiti-13523	288	9	”	"	PUNCT
aiti-13523	288	10	,	,	PUNCT
aiti-13523	288	11	“	"	PUNCT
aiti-13523	288	12	thanked	thank	VERB
aiti-13523	288	13	”	"	PUNCT
aiti-13523	288	14	,	,	PUNCT
aiti-13523	288	15	and	and	CCONJ
aiti-13523	288	16	“	"	PUNCT
aiti-13523	288	17	awareness	awareness	NOUN
aiti-13523	288	18	”	"	PUNCT
aiti-13523	288	19	,	,	PUNCT
aiti-13523	288	20	which	which	PRON
aiti-13523	288	21	inspire	inspire	VERB
aiti-13523	288	22	positive	positive	ADJ
aiti-13523	288	23	feelings	feeling	NOUN
aiti-13523	288	24	.	.	PUNCT
aiti-13523	289	1	terms	term	NOUN
aiti-13523	289	2	that	that	PRON
aiti-13523	289	3	do	do	AUX
aiti-13523	289	4	not	not	PART
aiti-13523	289	5	belong	belong	VERB
aiti-13523	289	6	to	to	ADP
aiti-13523	289	7	the	the	DET
aiti-13523	289	8	“	"	PUNCT
aiti-13523	289	9	happy	happy	ADJ
aiti-13523	289	10	”	"	PUNCT
aiti-13523	289	11	class	class	NOUN
aiti-13523	289	12	include	include	VERB
aiti-13523	289	13	“	"	PUNCT
aiti-13523	289	14	cancer	cancer	NOUN
aiti-13523	289	15	”	"	PUNCT
aiti-13523	289	16	,	,	PUNCT
aiti-13523	289	17	“	"	PUNCT
aiti-13523	289	18	army	army	NOUN
aiti-13523	289	19	”	"	PUNCT
aiti-13523	289	20	,	,	PUNCT
aiti-13523	289	21	and	and	CCONJ
aiti-13523	289	22	“	"	PUNCT
aiti-13523	289	23	hepatitis	hepatitis	NOUN
aiti-13523	289	24	”	"	PUNCT
aiti-13523	289	25	,	,	PUNCT
aiti-13523	289	26	which	which	PRON
aiti-13523	289	27	only	only	ADV
aiti-13523	289	28	inspire	inspire	VERB
aiti-13523	289	29	negative	negative	ADJ
aiti-13523	289	30	feelings	feeling	NOUN
aiti-13523	289	31	of	of	ADP
aiti-13523	289	32	sadness	sadness	NOUN
aiti-13523	289	33	.	.	PUNCT
aiti-13523	290	1	in	in	ADP
aiti-13523	290	2	the	the	DET
aiti-13523	290	3	“	"	PUNCT
aiti-13523	290	4	sad	sad	ADJ
aiti-13523	290	5	”	"	PUNCT
aiti-13523	290	6	feeling	feeling	NOUN
aiti-13523	290	7	class	class	NOUN
aiti-13523	290	8	,	,	PUNCT
aiti-13523	290	9	among	among	ADP
aiti-13523	290	10	the	the	DET
aiti-13523	290	11	important	important	ADJ
aiti-13523	290	12	terms	term	NOUN
aiti-13523	290	13	for	for	ADP
aiti-13523	290	14	the	the	DET
aiti-13523	290	15	classification	classification	NOUN
aiti-13523	290	16	considered	consider	VERB
aiti-13523	290	17	favorable	favorable	ADJ
aiti-13523	290	18	,	,	PUNCT
aiti-13523	290	19	found	find	VERB
aiti-13523	290	20	“	"	PUNCT
aiti-13523	290	21	toll	toll	NOUN
aiti-13523	290	22	”	"	PUNCT
aiti-13523	290	23	,	,	PUNCT
aiti-13523	290	24	“	"	PUNCT
aiti-13523	290	25	married	married	ADJ
aiti-13523	290	26	”	"	PUNCT
aiti-13523	290	27	,	,	PUNCT
aiti-13523	290	28	and	and	CCONJ
aiti-13523	290	29	“	"	PUNCT
aiti-13523	290	30	china	china	PROPN
aiti-13523	290	31	”	"	PUNCT
aiti-13523	290	32	,	,	PUNCT
aiti-13523	290	33	which	which	PRON
aiti-13523	290	34	are	be	AUX
aiti-13523	290	35	not	not	PART
aiti-13523	290	36	relevant	relevant	ADJ
aiti-13523	290	37	for	for	ADP
aiti-13523	290	38	identifying	identify	VERB
aiti-13523	290	39	a	a	DET
aiti-13523	290	40	feeling	feeling	NOUN
aiti-13523	290	41	of	of	ADP
aiti-13523	290	42	sadness	sadness	NOUN
aiti-13523	290	43	.	.	PUNCT
aiti-13523	291	1	detractor	detractor	NOUN
aiti-13523	291	2	words	word	NOUN
aiti-13523	291	3	include	include	VERB
aiti-13523	291	4	“	"	PUNCT
aiti-13523	291	5	outbreak	outbreak	NOUN
aiti-13523	291	6	”	"	PUNCT
aiti-13523	291	7	and	and	CCONJ
aiti-13523	291	8	“	"	PUNCT
aiti-13523	291	9	coronavirus	coronavirus	NOUN
aiti-13523	291	10	”	"	PUNCT
aiti-13523	291	11	,	,	PUNCT
aiti-13523	291	12	which	which	PRON
aiti-13523	291	13	are	be	AUX
aiti-13523	291	14	words	word	NOUN
aiti-13523	291	15	expressing	express	VERB
aiti-13523	291	16	illness	illness	NOUN
aiti-13523	291	17	and	and	CCONJ
aiti-13523	291	18	sad	sad	ADJ
aiti-13523	291	19	events	event	NOUN
aiti-13523	291	20	,	,	PUNCT
aiti-13523	291	21	but	but	CCONJ
aiti-13523	291	22	they	they	PRON
aiti-13523	291	23	appear	appear	VERB
aiti-13523	291	24	in	in	ADP
aiti-13523	291	25	the	the	DET
aiti-13523	291	26	list	list	NOUN
aiti-13523	291	27	of	of	ADP
aiti-13523	291	28	detractors	detractor	NOUN
aiti-13523	291	29	in	in	ADP
aiti-13523	291	30	the	the	DET
aiti-13523	291	31	“	"	PUNCT
aiti-13523	291	32	sad	sad	ADJ
aiti-13523	291	33	”	"	PUNCT
aiti-13523	291	34	class	class	NOUN
aiti-13523	291	35	.	.	PUNCT
aiti-13523	292	1	using	use	VERB
aiti-13523	292	2	lime	lime	NOUN
aiti-13523	292	3	,	,	PUNCT
aiti-13523	292	4	the	the	DET
aiti-13523	292	5	results	result	NOUN
aiti-13523	292	6	of	of	ADP
aiti-13523	292	7	the	the	DET
aiti-13523	292	8	classification	classification	NOUN
aiti-13523	292	9	model	model	NOUN
aiti-13523	292	10	are	be	AUX
aiti-13523	292	11	presented	present	VERB
aiti-13523	292	12	with	with	ADP
aiti-13523	292	13	some	some	DET
aiti-13523	292	14	details	detail	NOUN
aiti-13523	292	15	.	.	PUNCT
aiti-13523	293	1	a	a	DET
aiti-13523	293	2	perception	perception	NOUN
aiti-13523	293	3	of	of	ADP
aiti-13523	293	4	the	the	DET
aiti-13523	293	5	word2vec	word2vec	PROPN
aiti-13523	293	6	model	model	NOUN
aiti-13523	293	7	has	have	VERB
aiti-13523	293	8	difficulty	difficulty	NOUN
aiti-13523	293	9	identifying	identify	VERB
aiti-13523	293	10	the	the	DET
aiti-13523	293	11	appropriate	appropriate	ADJ
aiti-13523	293	12	lexical	lexical	ADJ
aiti-13523	293	13	representations	representation	NOUN
aiti-13523	293	14	to	to	PART
aiti-13523	293	15	support	support	VERB
aiti-13523	293	16	good	good	ADJ
aiti-13523	293	17	classification	classification	NOUN
aiti-13523	293	18	in	in	ADP
aiti-13523	293	19	certain	certain	ADJ
aiti-13523	293	20	classes	class	NOUN
aiti-13523	293	21	,	,	PUNCT
aiti-13523	293	22	such	such	ADJ
aiti-13523	293	23	as	as	ADP
aiti-13523	293	24	the	the	DET
aiti-13523	293	25	“	"	PUNCT
aiti-13523	293	26	sad	sad	ADJ
aiti-13523	293	27	”	"	PUNCT
aiti-13523	293	28	class	class	NOUN
aiti-13523	293	29	.	.	PUNCT
aiti-13523	294	1	this	this	PRON
aiti-13523	294	2	is	be	AUX
aiti-13523	294	3	not	not	PART
aiti-13523	294	4	the	the	DET
aiti-13523	294	5	case	case	NOUN
aiti-13523	294	6	for	for	ADP
aiti-13523	294	7	the	the	DET
aiti-13523	294	8	“	"	PUNCT
aiti-13523	294	9	happy	happy	ADJ
aiti-13523	294	10	”	"	PUNCT
aiti-13523	294	11	class	class	NOUN
aiti-13523	294	12	,	,	PUNCT
aiti-13523	294	13	where	where	SCONJ
aiti-13523	294	14	the	the	DET
aiti-13523	294	15	predictions	prediction	NOUN
aiti-13523	294	16	are	be	AUX
aiti-13523	294	17	consistent	consistent	ADJ
aiti-13523	294	18	.	.	PUNCT
aiti-13523	295	1	it	it	PRON
aiti-13523	295	2	is	be	AUX
aiti-13523	295	3	clear	clear	ADJ
aiti-13523	295	4	that	that	SCONJ
aiti-13523	295	5	a	a	DET
aiti-13523	295	6	feature	feature	NOUN
aiti-13523	295	7	of	of	ADP
aiti-13523	295	8	the	the	DET
aiti-13523	295	9	“	"	PUNCT
aiti-13523	295	10	sad	sad	ADJ
aiti-13523	295	11	”	"	PUNCT
aiti-13523	295	12	feeling	feel	VERB
aiti-13523	295	13	class	class	NOUN
aiti-13523	295	14	belongs	belong	VERB
aiti-13523	295	15	to	to	ADP
aiti-13523	295	16	the	the	DET
aiti-13523	295	17	minority	minority	NOUN
aiti-13523	295	18	classes	class	NOUN
aiti-13523	295	19	,	,	PUNCT
aiti-13523	295	20	made	make	VERB
aiti-13523	295	21	up	up	ADP
aiti-13523	295	22	of	of	ADP
aiti-13523	295	23	395	395	NUM
aiti-13523	295	24	negative	negative	ADJ
aiti-13523	295	25	feelings	feeling	NOUN
aiti-13523	295	26	.	.	PUNCT
aiti-13523	296	1	additionally	additionally	ADV
aiti-13523	296	2	,	,	PUNCT
aiti-13523	296	3	it	it	PRON
aiti-13523	296	4	is	be	AUX
aiti-13523	296	5	important	important	ADJ
aiti-13523	296	6	to	to	PART
aiti-13523	296	7	note	note	VERB
aiti-13523	296	8	that	that	SCONJ
aiti-13523	296	9	the	the	DET
aiti-13523	296	10	feeling	feeling	NOUN
aiti-13523	296	11	“	"	PUNCT
aiti-13523	296	12	sad	sad	ADJ
aiti-13523	296	13	”	"	PUNCT
aiti-13523	296	14	can	can	AUX
aiti-13523	296	15	easily	easily	ADV
aiti-13523	296	16	be	be	AUX
aiti-13523	296	17	confused	confuse	VERB
aiti-13523	296	18	with	with	ADP
aiti-13523	296	19	emotions	emotion	NOUN
aiti-13523	296	20	expressed	express	VERB
aiti-13523	296	21	in	in	ADP
aiti-13523	296	22	other	other	ADJ
aiti-13523	296	23	classes	class	NOUN
aiti-13523	296	24	such	such	ADJ
aiti-13523	296	25	as	as	ADP
aiti-13523	296	26	“	"	PUNCT
aiti-13523	296	27	angry	angry	ADJ
aiti-13523	296	28	”	"	PUNCT
aiti-13523	296	29	,	,	PUNCT
aiti-13523	296	30	“	"	PUNCT
aiti-13523	296	31	bored	bored	ADJ
aiti-13523	296	32	”	"	PUNCT
aiti-13523	296	33	,	,	PUNCT
aiti-13523	296	34	and	and	CCONJ
aiti-13523	296	35	“	"	PUNCT
aiti-13523	296	36	fear	fear	NOUN
aiti-13523	296	37	”	"	PUNCT
aiti-13523	296	38	,	,	PUNCT
aiti-13523	296	39	potentially	potentially	ADV
aiti-13523	296	40	leading	lead	VERB
aiti-13523	296	41	to	to	ADP
aiti-13523	296	42	misclassifications	misclassification	NOUN
aiti-13523	296	43	and	and	CCONJ
aiti-13523	296	44	confusion	confusion	NOUN
aiti-13523	296	45	.	.	PUNCT
aiti-13523	297	1	this	this	DET
aiti-13523	297	2	classification	classification	NOUN
aiti-13523	297	3	provided	provide	VERB
aiti-13523	297	4	by	by	ADP
aiti-13523	297	5	lime	lime	NOUN
aiti-13523	297	6	is	be	AUX
aiti-13523	297	7	very	very	ADV
aiti-13523	297	8	interesting	interesting	ADJ
aiti-13523	297	9	and	and	CCONJ
aiti-13523	297	10	can	can	AUX
aiti-13523	297	11	be	be	AUX
aiti-13523	297	12	used	use	VERB
aiti-13523	297	13	to	to	PART
aiti-13523	297	14	improve	improve	VERB
aiti-13523	297	15	the	the	DET
aiti-13523	297	16	performance	performance	NOUN
aiti-13523	297	17	of	of	ADP
aiti-13523	297	18	the	the	DET
aiti-13523	297	19	model	model	NOUN
aiti-13523	297	20	,	,	PUNCT
aiti-13523	297	21	thanks	thank	NOUN
aiti-13523	297	22	to	to	ADP
aiti-13523	297	23	the	the	DET
aiti-13523	297	24	addition	addition	NOUN
aiti-13523	297	25	of	of	ADP
aiti-13523	297	26	preprocessing	preprocessing	NOUN
aiti-13523	297	27	which	which	PRON
aiti-13523	297	28	removes	remove	VERB
aiti-13523	297	29	ambiguous	ambiguous	ADJ
aiti-13523	297	30	words	word	NOUN
aiti-13523	297	31	,	,	PUNCT
aiti-13523	297	32	or	or	CCONJ
aiti-13523	297	33	to	to	ADP
aiti-13523	297	34	the	the	DET
aiti-13523	297	35	parameterization	parameterization	NOUN
aiti-13523	297	36	of	of	ADP
aiti-13523	297	37	the	the	DET
aiti-13523	297	38	word2vec	word2vec	PROPN
aiti-13523	297	39	model	model	NOUN
aiti-13523	297	40	that	that	PRON
aiti-13523	297	41	thus	thus	ADV
aiti-13523	297	42	varies	vary	VERB
aiti-13523	297	43	the	the	DET
aiti-13523	297	44	contextual	contextual	ADJ
aiti-13523	297	45	size	size	NOUN
aiti-13523	297	46	and	and	CCONJ
aiti-13523	297	47	verifies	verifie	NOUN
aiti-13523	297	48	the	the	DET
aiti-13523	297	49	change	change	NOUN
aiti-13523	297	50	in	in	ADP
aiti-13523	297	51	obtained	obtain	VERB
aiti-13523	297	52	results	result	NOUN
aiti-13523	297	53	.	.	PUNCT
aiti-13523	298	1	5	5	X
aiti-13523	298	2	.	.	X
aiti-13523	298	3	conclusion	conclusion	NOUN
aiti-13523	298	4	and	and	CCONJ
aiti-13523	298	5	perspectives	perspective	NOUN
aiti-13523	298	6	in	in	ADP
aiti-13523	298	7	this	this	DET
aiti-13523	298	8	paper	paper	NOUN
aiti-13523	298	9	,	,	PUNCT
aiti-13523	298	10	an	an	DET
aiti-13523	298	11	approach	approach	NOUN
aiti-13523	298	12	was	be	AUX
aiti-13523	298	13	presented	present	VERB
aiti-13523	298	14	to	to	PART
aiti-13523	298	15	classify	classify	VERB
aiti-13523	298	16	sentiments	sentiment	NOUN
aiti-13523	298	17	from	from	ADP
aiti-13523	298	18	imbalanced	imbalanced	ADJ
aiti-13523	298	19	health	health	NOUN
aiti-13523	298	20	text	text	NOUN
aiti-13523	298	21	data	datum	NOUN
aiti-13523	298	22	.	.	PUNCT
aiti-13523	299	1	the	the	DET
aiti-13523	299	2	classification	classification	NOUN
aiti-13523	299	3	scores	score	NOUN
aiti-13523	299	4	obtained	obtain	VERB
aiti-13523	299	5	confirmed	confirm	VERB
aiti-13523	299	6	the	the	DET
aiti-13523	299	7	impact	impact	NOUN
aiti-13523	299	8	of	of	ADP
aiti-13523	299	9	imbalanced	imbalanced	ADJ
aiti-13523	299	10	data	datum	NOUN
aiti-13523	299	11	on	on	ADP
aiti-13523	299	12	classification	classification	NOUN
aiti-13523	299	13	and	and	CCONJ
aiti-13523	299	14	the	the	DET
aiti-13523	299	15	importance	importance	NOUN
aiti-13523	299	16	of	of	ADP
aiti-13523	299	17	selecting	select	VERB
aiti-13523	299	18	an	an	DET
aiti-13523	299	19	appropriate	appropriate	ADJ
aiti-13523	299	20	resampling	resampling	NOUN
aiti-13523	299	21	method	method	NOUN
aiti-13523	299	22	.	.	PUNCT
aiti-13523	300	1	for	for	ADP
aiti-13523	300	2	feature	feature	NOUN
aiti-13523	300	3	selection	selection	NOUN
aiti-13523	300	4	in	in	ADP
aiti-13523	300	5	this	this	DET
aiti-13523	300	6	case	case	NOUN
aiti-13523	300	7	,	,	PUNCT
aiti-13523	300	8	tf	tf	PROPN
aiti-13523	300	9	-	-	PUNCT
aiti-13523	300	10	idf	idf	PROPN
aiti-13523	300	11	performed	perform	VERB
aiti-13523	300	12	better	well	ADV
aiti-13523	300	13	than	than	ADP
aiti-13523	300	14	the	the	DET
aiti-13523	300	15	word2vec	word2vec	PROPN
aiti-13523	300	16	model	model	NOUN
aiti-13523	300	17	.	.	PUNCT
aiti-13523	301	1	the	the	DET
aiti-13523	301	2	results	result	NOUN
aiti-13523	301	3	also	also	ADV
aiti-13523	301	4	demonstrated	demonstrate	VERB
aiti-13523	301	5	the	the	DET
aiti-13523	301	6	superiority	superiority	NOUN
aiti-13523	301	7	of	of	ADP
aiti-13523	301	8	the	the	DET
aiti-13523	301	9	lstm	lstm	PROPN
aiti-13523	301	10	and	and	CCONJ
aiti-13523	301	11	bert	bert	PROPN
aiti-13523	301	12	deep	deep	ADJ
aiti-13523	301	13	learning	learning	NOUN
aiti-13523	301	14	models	model	NOUN
aiti-13523	301	15	,	,	PUNCT
aiti-13523	301	16	compared	compare	VERB
aiti-13523	301	17	to	to	ADP
aiti-13523	301	18	the	the	DET
aiti-13523	301	19	reference	reference	NOUN
aiti-13523	301	20	models	model	NOUN
aiti-13523	301	21	.	.	PUNCT
aiti-13523	302	1	it	it	PRON
aiti-13523	302	2	has	have	AUX
aiti-13523	302	3	also	also	ADV
aiti-13523	302	4	been	be	AUX
aiti-13523	302	5	found	find	VERB
aiti-13523	302	6	that	that	SCONJ
aiti-13523	302	7	models	model	NOUN
aiti-13523	302	8	like	like	ADP
aiti-13523	302	9	lime	lime	NOUN
aiti-13523	302	10	can	can	AUX
aiti-13523	302	11	help	help	AUX
aiti-13523	302	12	identify	identify	VERB
aiti-13523	302	13	words	word	NOUN
aiti-13523	302	14	that	that	PRON
aiti-13523	302	15	influence	influence	VERB
aiti-13523	302	16	the	the	DET
aiti-13523	302	17	classification	classification	NOUN
aiti-13523	302	18	of	of	ADP
aiti-13523	302	19	each	each	DET
aiti-13523	302	20	class	class	NOUN
aiti-13523	302	21	depending	depend	VERB
aiti-13523	302	22	on	on	ADP
aiti-13523	302	23	the	the	DET
aiti-13523	302	24	learning	learning	NOUN
aiti-13523	302	25	model	model	NOUN
aiti-13523	302	26	used	use	VERB
aiti-13523	302	27	.	.	PUNCT
aiti-13523	303	1	the	the	DET
aiti-13523	303	2	comparative	comparative	ADJ
aiti-13523	303	3	study	study	NOUN
aiti-13523	303	4	of	of	ADP
aiti-13523	303	5	related	relate	VERB
aiti-13523	303	6	research	research	NOUN
aiti-13523	303	7	works	work	NOUN
aiti-13523	303	8	demonstrated	demonstrate	VERB
aiti-13523	303	9	the	the	DET
aiti-13523	303	10	performance	performance	NOUN
aiti-13523	303	11	of	of	ADP
aiti-13523	303	12	deep	deep	ADJ
aiti-13523	303	13	learning	learning	NOUN
aiti-13523	303	14	models	model	NOUN
aiti-13523	303	15	such	such	ADJ
aiti-13523	303	16	as	as	ADP
aiti-13523	303	17	lstm	lstm	NOUN
aiti-13523	303	18	,	,	PUNCT
aiti-13523	303	19	bilstm	bilstm	NOUN
aiti-13523	303	20	,	,	PUNCT
aiti-13523	303	21	and	and	CCONJ
aiti-13523	303	22	hybrid	hybrid	ADJ
aiti-13523	303	23	models	model	NOUN
aiti-13523	303	24	,	,	PUNCT
aiti-13523	303	25	which	which	PRON
aiti-13523	303	26	is	be	AUX
aiti-13523	303	27	encouraging	encouraging	ADJ
aiti-13523	303	28	for	for	ADP
aiti-13523	303	29	the	the	DET
aiti-13523	303	30	usability	usability	NOUN
aiti-13523	303	31	of	of	ADP
aiti-13523	303	32	such	such	ADJ
aiti-13523	303	33	models	model	NOUN
aiti-13523	303	34	in	in	ADP
aiti-13523	303	35	the	the	DET
aiti-13523	303	36	field	field	NOUN
aiti-13523	303	37	of	of	ADP
aiti-13523	303	38	sentiment	sentiment	NOUN
aiti-13523	303	39	classification	classification	NOUN
aiti-13523	303	40	from	from	ADP
aiti-13523	303	41	textual	textual	ADJ
aiti-13523	303	42	data	datum	NOUN
aiti-13523	303	43	.	.	PUNCT
aiti-13523	304	1	advances	advance	NOUN
aiti-13523	304	2	in	in	ADP
aiti-13523	304	3	technology	technology	NOUN
aiti-13523	304	4	innovation	innovation	NOUN
aiti-13523	304	5	,	,	PUNCT
aiti-13523	304	6	vol	vol	NOUN
aiti-13523	304	7	.	.	PROPN
aiti-13523	305	1	9	9	NUM
aiti-13523	305	2	,	,	PUNCT
aiti-13523	305	3	no	no	INTJ
aiti-13523	305	4	.	.	NOUN
aiti-13523	305	5	2	2	NUM
aiti-13523	305	6	,	,	PUNCT
aiti-13523	305	7	2024	2024	NUM
aiti-13523	305	8	,	,	PUNCT
aiti-13523	305	9	pp	pp	ADJ
aiti-13523	305	10	.	.	PUNCT
aiti-13523	306	1	129	129	NUM
aiti-13523	306	2	-	-	SYM
aiti-13523	306	3	142	142	NUM
aiti-13523	306	4	141	141	NUM
aiti-13523	306	5	even	even	ADV
aiti-13523	306	6	though	though	SCONJ
aiti-13523	306	7	the	the	DET
aiti-13523	306	8	emohd	emohd	PROPN
aiti-13523	306	9	database	database	NOUN
aiti-13523	306	10	explored	explore	VERB
aiti-13523	306	11	in	in	ADP
aiti-13523	306	12	this	this	DET
aiti-13523	306	13	study	study	NOUN
aiti-13523	306	14	is	be	AUX
aiti-13523	306	15	interesting	interesting	ADJ
aiti-13523	306	16	in	in	ADP
aiti-13523	306	17	terms	term	NOUN
aiti-13523	306	18	of	of	ADP
aiti-13523	306	19	application	application	NOUN
aiti-13523	306	20	in	in	ADP
aiti-13523	306	21	cognitive	cognitive	ADJ
aiti-13523	306	22	psychology	psychology	NOUN
aiti-13523	306	23	,	,	PUNCT
aiti-13523	306	24	in	in	ADP
aiti-13523	306	25	particular	particular	ADJ
aiti-13523	306	26	,	,	PUNCT
aiti-13523	306	27	to	to	PART
aiti-13523	306	28	help	help	AUX
aiti-13523	306	29	identify	identify	VERB
aiti-13523	306	30	the	the	DET
aiti-13523	306	31	mental	mental	ADJ
aiti-13523	306	32	state	state	NOUN
aiti-13523	306	33	of	of	ADP
aiti-13523	306	34	patients	patient	NOUN
aiti-13523	306	35	suffering	suffer	VERB
aiti-13523	306	36	from	from	ADP
aiti-13523	306	37	serious	serious	ADJ
aiti-13523	306	38	illnesses	illness	NOUN
aiti-13523	306	39	and	and	CCONJ
aiti-13523	306	40	to	to	PART
aiti-13523	306	41	promote	promote	VERB
aiti-13523	306	42	a	a	DET
aiti-13523	306	43	healing	healing	NOUN
aiti-13523	306	44	process	process	NOUN
aiti-13523	306	45	by	by	ADP
aiti-13523	306	46	addressing	address	VERB
aiti-13523	306	47	negative	negative	ADJ
aiti-13523	306	48	thoughts	thought	NOUN
aiti-13523	306	49	of	of	ADP
aiti-13523	306	50	patients	patient	NOUN
aiti-13523	306	51	thanks	thank	NOUN
aiti-13523	306	52	to	to	ADP
aiti-13523	306	53	a	a	DET
aiti-13523	306	54	dedicated	dedicated	ADJ
aiti-13523	306	55	diagnosis	diagnosis	NOUN
aiti-13523	306	56	providing	provide	VERB
aiti-13523	306	57	an	an	DET
aiti-13523	306	58	automatic	automatic	ADJ
aiti-13523	306	59	system	system	NOUN
aiti-13523	306	60	based	base	VERB
aiti-13523	306	61	on	on	ADP
aiti-13523	306	62	robust	robust	ADJ
aiti-13523	306	63	learning	learning	NOUN
aiti-13523	306	64	models	model	NOUN
aiti-13523	306	65	for	for	ADP
aiti-13523	306	66	sentiment	sentiment	NOUN
aiti-13523	306	67	analysis	analysis	NOUN
aiti-13523	306	68	;	;	PUNCT
aiti-13523	306	69	nevertheless	nevertheless	ADV
aiti-13523	306	70	,	,	PUNCT
aiti-13523	306	71	emohd	emohd	PROPN
aiti-13523	306	72	presents	present	VERB
aiti-13523	306	73	many	many	ADJ
aiti-13523	306	74	limitations	limitation	NOUN
aiti-13523	306	75	in	in	ADP
aiti-13523	306	76	terms	term	NOUN
aiti-13523	306	77	of	of	ADP
aiti-13523	306	78	unbalanced	unbalanced	ADJ
aiti-13523	306	79	data	datum	NOUN
aiti-13523	306	80	,	,	PUNCT
aiti-13523	306	81	but	but	CCONJ
aiti-13523	306	82	also	also	ADV
aiti-13523	306	83	in	in	ADP
aiti-13523	306	84	terms	term	NOUN
aiti-13523	306	85	of	of	ADP
aiti-13523	306	86	ambiguity	ambiguity	NOUN
aiti-13523	306	87	of	of	ADP
aiti-13523	306	88	classes	class	NOUN
aiti-13523	306	89	like	like	ADP
aiti-13523	306	90	the	the	DET
aiti-13523	306	91	sad	sad	ADJ
aiti-13523	306	92	,	,	PUNCT
aiti-13523	306	93	angry	angry	ADJ
aiti-13523	306	94	,	,	PUNCT
aiti-13523	306	95	and	and	CCONJ
aiti-13523	306	96	bored	bored	ADJ
aiti-13523	306	97	classes	class	NOUN
aiti-13523	306	98	are	be	AUX
aiti-13523	306	99	very	very	ADV
aiti-13523	306	100	close	close	ADJ
aiti-13523	306	101	and	and	CCONJ
aiti-13523	306	102	can	can	AUX
aiti-13523	306	103	lead	lead	VERB
aiti-13523	306	104	to	to	ADP
aiti-13523	306	105	confusion	confusion	NOUN
aiti-13523	306	106	a	a	DET
aiti-13523	306	107	term	term	NOUN
aiti-13523	306	108	representing	represent	VERB
aiti-13523	306	109	a	a	DET
aiti-13523	306	110	negative	negative	ADJ
aiti-13523	306	111	thought	thought	NOUN
aiti-13523	306	112	:	:	PUNCT
aiti-13523	306	113	for	for	ADP
aiti-13523	306	114	example	example	NOUN
aiti-13523	306	115	,	,	PUNCT
aiti-13523	306	116	the	the	DET
aiti-13523	306	117	word	word	NOUN
aiti-13523	306	118	war	war	NOUN
aiti-13523	306	119	can	can	AUX
aiti-13523	306	120	be	be	AUX
aiti-13523	306	121	classified	classify	VERB
aiti-13523	306	122	into	into	ADP
aiti-13523	306	123	these	these	DET
aiti-13523	306	124	3	3	NUM
aiti-13523	306	125	classes	class	NOUN
aiti-13523	306	126	.	.	PUNCT
aiti-13523	307	1	in	in	ADP
aiti-13523	307	2	this	this	DET
aiti-13523	307	3	context	context	NOUN
aiti-13523	307	4	,	,	PUNCT
aiti-13523	307	5	some	some	DET
aiti-13523	307	6	limitations	limitation	NOUN
aiti-13523	307	7	were	be	AUX
aiti-13523	307	8	observed	observe	VERB
aiti-13523	307	9	for	for	ADP
aiti-13523	307	10	future	future	ADJ
aiti-13523	307	11	research	research	NOUN
aiti-13523	307	12	,	,	PUNCT
aiti-13523	307	13	it	it	PRON
aiti-13523	307	14	is	be	AUX
aiti-13523	307	15	wise	wise	ADJ
aiti-13523	307	16	to	to	PART
aiti-13523	307	17	explore	explore	VERB
aiti-13523	307	18	other	other	ADJ
aiti-13523	307	19	sentiment	sentiment	NOUN
aiti-13523	307	20	databases	database	NOUN
aiti-13523	307	21	in	in	ADP
aiti-13523	307	22	the	the	DET
aiti-13523	307	23	health	health	NOUN
aiti-13523	307	24	domain	domain	NOUN
aiti-13523	307	25	using	use	VERB
aiti-13523	307	26	recursive	recursive	ADJ
aiti-13523	307	27	models	model	NOUN
aiti-13523	307	28	and	and	CCONJ
aiti-13523	307	29	transformers	transformer	NOUN
aiti-13523	307	30	.	.	PUNCT
aiti-13523	308	1	this	this	PRON
aiti-13523	308	2	is	be	AUX
aiti-13523	308	3	a	a	DET
aiti-13523	308	4	relevant	relevant	ADJ
aiti-13523	308	5	area	area	NOUN
aiti-13523	308	6	for	for	ADP
aiti-13523	308	7	analyzing	analyze	VERB
aiti-13523	308	8	the	the	DET
aiti-13523	308	9	impact	impact	NOUN
aiti-13523	308	10	of	of	ADP
aiti-13523	308	11	positive	positive	ADJ
aiti-13523	308	12	or	or	CCONJ
aiti-13523	308	13	negative	negative	ADJ
aiti-13523	308	14	feelings	feeling	NOUN
aiti-13523	308	15	toward	toward	ADP
aiti-13523	308	16	patients	patient	NOUN
aiti-13523	308	17	.	.	PUNCT
aiti-13523	309	1	this	this	PRON
aiti-13523	309	2	can	can	AUX
aiti-13523	309	3	be	be	AUX
aiti-13523	309	4	very	very	ADV
aiti-13523	309	5	beneficial	beneficial	ADJ
aiti-13523	309	6	in	in	ADP
aiti-13523	309	7	the	the	DET
aiti-13523	309	8	field	field	NOUN
aiti-13523	309	9	of	of	ADP
aiti-13523	309	10	health	health	NOUN
aiti-13523	309	11	,	,	PUNCT
aiti-13523	309	12	both	both	CCONJ
aiti-13523	309	13	in	in	ADP
aiti-13523	309	14	the	the	DET
aiti-13523	309	15	healing	healing	NOUN
aiti-13523	309	16	process	process	NOUN
aiti-13523	309	17	of	of	ADP
aiti-13523	309	18	patients	patient	NOUN
aiti-13523	309	19	and	and	CCONJ
aiti-13523	309	20	in	in	ADP
aiti-13523	309	21	the	the	DET
aiti-13523	309	22	field	field	NOUN
aiti-13523	309	23	of	of	ADP
aiti-13523	309	24	psychology	psychology	NOUN
aiti-13523	309	25	.	.	PUNCT
aiti-13523	310	1	conflicts	conflict	NOUN
aiti-13523	310	2	of	of	ADP
aiti-13523	310	3	interest	interest	NOUN
aiti-13523	310	4	the	the	DET
aiti-13523	310	5	authors	author	NOUN
aiti-13523	310	6	declare	declare	VERB
aiti-13523	310	7	no	no	DET
aiti-13523	310	8	conflicts	conflict	NOUN
aiti-13523	310	9	of	of	ADP
aiti-13523	310	10	interest	interest	NOUN
aiti-13523	310	11	.	.	PUNCT
aiti-13523	311	1	references	reference	NOUN
aiti-13523	311	2	[	[	X
aiti-13523	311	3	1	1	NUM
aiti-13523	311	4	]	]	X
aiti-13523	311	5	y.	y.	PROPN
aiti-13523	311	6	madani	madani	PROPN
aiti-13523	311	7	,	,	PUNCT
aiti-13523	311	8	m.	m.	PROPN
aiti-13523	311	9	erritali	erritali	PROPN
aiti-13523	311	10	,	,	PUNCT
aiti-13523	311	11	and	and	CCONJ
aiti-13523	311	12	b.	b.	PROPN
aiti-13523	311	13	bouikhalene	bouikhalene	PROPN
aiti-13523	311	14	,	,	PUNCT
aiti-13523	311	15	“	"	PUNCT
aiti-13523	311	16	a	a	DET
aiti-13523	311	17	new	new	ADJ
aiti-13523	311	18	sentiment	sentiment	NOUN
aiti-13523	311	19	analysis	analysis	NOUN
aiti-13523	311	20	method	method	NOUN
aiti-13523	311	21	to	to	PART
aiti-13523	311	22	detect	detect	VERB
aiti-13523	311	23	and	and	CCONJ
aiti-13523	311	24	analyse	analyse	VERB
aiti-13523	311	25	sentiments	sentiment	NOUN
aiti-13523	311	26	of	of	ADP
aiti-13523	311	27	covid-19	covid-19	PROPN
aiti-13523	311	28	moroccan	moroccan	ADJ
aiti-13523	311	29	tweets	tweet	NOUN
aiti-13523	311	30	using	use	VERB
aiti-13523	311	31	a	a	DET
aiti-13523	311	32	recommender	recommender	NOUN
aiti-13523	311	33	approach	approach	NOUN
aiti-13523	311	34	,	,	PUNCT
aiti-13523	311	35	”	"	PUNCT
aiti-13523	311	36	multimedia	multimedia	NOUN
aiti-13523	311	37	tools	tool	NOUN
aiti-13523	311	38	and	and	CCONJ
aiti-13523	311	39	applications	application	NOUN
aiti-13523	311	40	,	,	PUNCT
aiti-13523	311	41	vol	vol	NOUN
aiti-13523	311	42	.	.	PROPN
aiti-13523	311	43	82	82	NUM
aiti-13523	311	44	,	,	PUNCT
aiti-13523	311	45	no	no	INTJ
aiti-13523	311	46	.	.	NOUN
aiti-13523	311	47	18	18	NUM
aiti-13523	311	48	,	,	PUNCT
aiti-13523	311	49	pp	pp	ADJ
aiti-13523	311	50	.	.	PUNCT
aiti-13523	312	1	27819	27819	NUM
aiti-13523	312	2	-	-	SYM
aiti-13523	312	3	27838	27838	NUM
aiti-13523	312	4	,	,	PUNCT
aiti-13523	312	5	july	july	PROPN
aiti-13523	312	6	2023	2023	NUM
aiti-13523	312	7	.	.	PUNCT
aiti-13523	313	1	[	[	X
aiti-13523	313	2	2	2	NUM
aiti-13523	313	3	]	]	PUNCT
aiti-13523	313	4	k.	k.	PROPN
aiti-13523	313	5	chakraborty	chakraborty	PROPN
aiti-13523	313	6	,	,	PUNCT
aiti-13523	313	7	s.	s.	PROPN
aiti-13523	313	8	bhatia	bhatia	PROPN
aiti-13523	313	9	,	,	PUNCT
aiti-13523	313	10	s.	s.	PROPN
aiti-13523	313	11	bhattacharyya	bhattacharyya	PROPN
aiti-13523	313	12	,	,	PUNCT
aiti-13523	313	13	j.	j.	PROPN
aiti-13523	313	14	platos	platos	PROPN
aiti-13523	313	15	,	,	PUNCT
aiti-13523	313	16	r.	r.	NOUN
aiti-13523	313	17	bag	bag	PROPN
aiti-13523	313	18	,	,	PUNCT
aiti-13523	313	19	and	and	CCONJ
aiti-13523	313	20	a.	a.	PROPN
aiti-13523	313	21	e.	e.	PROPN
aiti-13523	313	22	hassanien	hassanien	PROPN
aiti-13523	313	23	,	,	PUNCT
aiti-13523	313	24	“	"	PUNCT
aiti-13523	313	25	sentiment	sentiment	NOUN
aiti-13523	313	26	analysis	analysis	NOUN
aiti-13523	313	27	of	of	ADP
aiti-13523	313	28	covid-19	covid-19	PROPN
aiti-13523	313	29	tweets	tweet	NOUN
aiti-13523	313	30	by	by	ADP
aiti-13523	313	31	deep	deep	ADJ
aiti-13523	313	32	learning	learning	NOUN
aiti-13523	313	33	classifiers	classifier	NOUN
aiti-13523	313	34	—	—	PUNCT
aiti-13523	313	35	a	a	DET
aiti-13523	313	36	study	study	NOUN
aiti-13523	313	37	to	to	PART
aiti-13523	313	38	show	show	VERB
aiti-13523	313	39	how	how	SCONJ
aiti-13523	313	40	popularity	popularity	NOUN
aiti-13523	313	41	is	be	AUX
aiti-13523	313	42	affecting	affect	VERB
aiti-13523	313	43	accuracy	accuracy	NOUN
aiti-13523	313	44	in	in	ADP
aiti-13523	313	45	social	social	ADJ
aiti-13523	313	46	media	medium	NOUN
aiti-13523	313	47	,	,	PUNCT
aiti-13523	313	48	”	"	PUNCT
aiti-13523	313	49	applied	apply	VERB
aiti-13523	313	50	soft	soft	ADJ
aiti-13523	313	51	computing	computing	NOUN
aiti-13523	313	52	,	,	PUNCT
aiti-13523	313	53	vol	vol	NOUN
aiti-13523	313	54	.	.	PROPN
aiti-13523	314	1	97	97	NUM
aiti-13523	314	2	,	,	PUNCT
aiti-13523	314	3	part	part	NOUN
aiti-13523	314	4	a	a	X
aiti-13523	314	5	,	,	PUNCT
aiti-13523	314	6	article	article	NOUN
aiti-13523	314	7	no	no	NOUN
aiti-13523	314	8	.	.	PROPN
aiti-13523	314	9	106754	106754	NUM
aiti-13523	314	10	,	,	PUNCT
aiti-13523	314	11	december	december	PROPN
aiti-13523	314	12	2020	2020	NUM
aiti-13523	314	13	.	.	PUNCT
aiti-13523	315	1	[	[	X
aiti-13523	315	2	3	3	X
aiti-13523	315	3	]	]	X
aiti-13523	315	4	h.	h.	PROPN
aiti-13523	315	5	xu	xu	PROPN
aiti-13523	315	6	,	,	PUNCT
aiti-13523	315	7	r.	r.	PROPN
aiti-13523	315	8	liu	liu	PROPN
aiti-13523	315	9	,	,	PUNCT
aiti-13523	315	10	z.	z.	PROPN
aiti-13523	315	11	luo	luo	PROPN
aiti-13523	315	12	,	,	PUNCT
aiti-13523	315	13	and	and	CCONJ
aiti-13523	315	14	m.	m.	PROPN
aiti-13523	315	15	xu	xu	PROPN
aiti-13523	315	16	,	,	PUNCT
aiti-13523	315	17	“	"	PUNCT
aiti-13523	315	18	covid-19	covid-19	PROPN
aiti-13523	315	19	vaccine	vaccine	NOUN
aiti-13523	315	20	sensing	sense	VERB
aiti-13523	315	21	:	:	PUNCT
aiti-13523	315	22	sentiment	sentiment	NOUN
aiti-13523	315	23	analysis	analysis	NOUN
aiti-13523	315	24	and	and	CCONJ
aiti-13523	315	25	subject	subject	ADJ
aiti-13523	315	26	distillation	distillation	NOUN
aiti-13523	315	27	from	from	ADP
aiti-13523	315	28	twitter	twitter	PROPN
aiti-13523	315	29	data	datum	NOUN
aiti-13523	315	30	,	,	PUNCT
aiti-13523	315	31	”	"	PUNCT
aiti-13523	315	32	telematics	telematic	NOUN
aiti-13523	315	33	and	and	CCONJ
aiti-13523	315	34	informatics	informatic	NOUN
aiti-13523	315	35	reports	report	NOUN
aiti-13523	315	36	,	,	PUNCT
aiti-13523	315	37	vol	vol	NOUN
aiti-13523	315	38	.	.	PROPN
aiti-13523	315	39	8	8	NUM
aiti-13523	315	40	,	,	PUNCT
aiti-13523	315	41	article	article	NOUN
aiti-13523	315	42	no	no	NOUN
aiti-13523	315	43	.	.	PROPN
aiti-13523	315	44	100016	100016	NUM
aiti-13523	315	45	,	,	PUNCT
aiti-13523	315	46	december	december	PROPN
aiti-13523	315	47	2022	2022	NUM
aiti-13523	315	48	.	.	PUNCT
aiti-13523	316	1	[	[	X
aiti-13523	316	2	4	4	NUM
aiti-13523	316	3	]	]	X
aiti-13523	316	4	n.	n.	PROPN
aiti-13523	316	5	azam	azam	PROPN
aiti-13523	316	6	,	,	PUNCT
aiti-13523	316	7	t.	t.	PROPN
aiti-13523	316	8	ahmad	ahmad	PROPN
aiti-13523	316	9	,	,	PUNCT
aiti-13523	316	10	and	and	CCONJ
aiti-13523	316	11	n.	n.	PROPN
aiti-13523	316	12	ul	ul	PROPN
aiti-13523	316	13	haq	haq	PROPN
aiti-13523	316	14	,	,	PUNCT
aiti-13523	316	15	“	"	PUNCT
aiti-13523	316	16	automatic	automatic	ADJ
aiti-13523	316	17	emotion	emotion	NOUN
aiti-13523	316	18	recognition	recognition	NOUN
aiti-13523	316	19	in	in	ADP
aiti-13523	316	20	healthcare	healthcare	PROPN
aiti-13523	316	21	data	datum	NOUN
aiti-13523	316	22	using	use	VERB
aiti-13523	316	23	supervised	supervised	ADJ
aiti-13523	316	24	machine	machine	NOUN
aiti-13523	316	25	learning	learning	NOUN
aiti-13523	316	26	,	,	PUNCT
aiti-13523	316	27	”	"	PUNCT
aiti-13523	316	28	peerj	peerj	PROPN
aiti-13523	316	29	computer	computer	NOUN
aiti-13523	316	30	science	science	NOUN
aiti-13523	316	31	,	,	PUNCT
aiti-13523	316	32	vol	vol	NOUN
aiti-13523	316	33	.	.	PROPN
aiti-13523	316	34	7	7	NUM
aiti-13523	316	35	,	,	PUNCT
aiti-13523	316	36	article	article	NOUN
aiti-13523	316	37	no	no	NOUN
aiti-13523	316	38	.	.	PUNCT
aiti-13523	317	1	e751	e751	PROPN
aiti-13523	317	2	,	,	PUNCT
aiti-13523	317	3	2021	2021	NUM
aiti-13523	317	4	.	.	PUNCT
aiti-13523	318	1	[	[	X
aiti-13523	318	2	5	5	X
aiti-13523	318	3	]	]	PUNCT
aiti-13523	318	4	s.	s.	PROPN
aiti-13523	318	5	m.	m.	PROPN
aiti-13523	318	6	srinivasan	srinivasan	PROPN
aiti-13523	318	7	,	,	PUNCT
aiti-13523	318	8	r.	r.	PROPN
aiti-13523	318	9	s.	s.	PROPN
aiti-13523	318	10	sangwan	sangwan	PROPN
aiti-13523	318	11	,	,	PUNCT
aiti-13523	318	12	c.	c.	PROPN
aiti-13523	318	13	j.	j.	PROPN
aiti-13523	318	14	neill	neill	PROPN
aiti-13523	318	15	,	,	PUNCT
aiti-13523	318	16	and	and	CCONJ
aiti-13523	318	17	t.	t.	PROPN
aiti-13523	318	18	zu	zu	PROPN
aiti-13523	318	19	,	,	PUNCT
aiti-13523	318	20	“	"	PUNCT
aiti-13523	318	21	twitter	twitter	NOUN
aiti-13523	318	22	data	datum	NOUN
aiti-13523	318	23	for	for	ADP
aiti-13523	318	24	predicting	predict	VERB
aiti-13523	318	25	election	election	NOUN
aiti-13523	318	26	results	result	NOUN
aiti-13523	318	27	:	:	PUNCT
aiti-13523	318	28	insights	insight	NOUN
aiti-13523	318	29	from	from	ADP
aiti-13523	318	30	emotion	emotion	NOUN
aiti-13523	318	31	classification	classification	NOUN
aiti-13523	318	32	,	,	PUNCT
aiti-13523	318	33	”	"	PUNCT
aiti-13523	318	34	ieee	ieee	NOUN
aiti-13523	318	35	technology	technology	NOUN
aiti-13523	318	36	and	and	CCONJ
aiti-13523	318	37	society	society	NOUN
aiti-13523	318	38	magazine	magazine	NOUN
aiti-13523	318	39	,	,	PUNCT
aiti-13523	318	40	vol	vol	NOUN
aiti-13523	318	41	.	.	PROPN
aiti-13523	319	1	38	38	NUM
aiti-13523	319	2	,	,	PUNCT
aiti-13523	319	3	no	no	INTJ
aiti-13523	319	4	.	.	NOUN
aiti-13523	319	5	1	1	NUM
aiti-13523	319	6	,	,	PUNCT
aiti-13523	319	7	pp	pp	ADJ
aiti-13523	319	8	.	.	PUNCT
aiti-13523	320	1	58	58	NUM
aiti-13523	320	2	-	-	SYM
aiti-13523	320	3	63	63	NUM
aiti-13523	320	4	,	,	PUNCT
aiti-13523	320	5	march	march	PROPN
aiti-13523	320	6	2019	2019	NUM
aiti-13523	320	7	.	.	PUNCT
aiti-13523	321	1	[	[	X
aiti-13523	321	2	6	6	NUM
aiti-13523	321	3	]	]	PUNCT
aiti-13523	321	4	w.	w.	PROPN
aiti-13523	321	5	lin	lin	PROPN
aiti-13523	321	6	and	and	CCONJ
aiti-13523	321	7	l.	l.	PROPN
aiti-13523	321	8	c.	c.	PROPN
aiti-13523	321	9	liao	liao	PROPN
aiti-13523	321	10	,	,	PUNCT
aiti-13523	321	11	“	"	PUNCT
aiti-13523	321	12	lexicon	lexicon	NOUN
aiti-13523	321	13	-	-	PUNCT
aiti-13523	321	14	based	base	VERB
aiti-13523	321	15	prompt	prompt	NOUN
aiti-13523	321	16	for	for	ADP
aiti-13523	321	17	financial	financial	ADJ
aiti-13523	321	18	dimensional	dimensional	ADJ
aiti-13523	321	19	sentiment	sentiment	NOUN
aiti-13523	321	20	analysis	analysis	NOUN
aiti-13523	321	21	,	,	PUNCT
aiti-13523	321	22	”	"	PUNCT
aiti-13523	321	23	expert	expert	NOUN
aiti-13523	321	24	systems	system	NOUN
aiti-13523	321	25	with	with	ADP
aiti-13523	321	26	applications	application	NOUN
aiti-13523	321	27	,	,	PUNCT
aiti-13523	321	28	vol	vol	NOUN
aiti-13523	321	29	.	.	PROPN
aiti-13523	321	30	244	244	NUM
aiti-13523	321	31	,	,	PUNCT
aiti-13523	321	32	article	article	NOUN
aiti-13523	321	33	no	no	NOUN
aiti-13523	321	34	.	.	PROPN
aiti-13523	321	35	122936	122936	NUM
aiti-13523	321	36	,	,	PUNCT
aiti-13523	321	37	june	june	PROPN
aiti-13523	321	38	2024	2024	NUM
aiti-13523	321	39	.	.	PUNCT
aiti-13523	322	1	[	[	X
aiti-13523	322	2	7	7	X
aiti-13523	322	3	]	]	X
aiti-13523	322	4	r.	r.	PROPN
aiti-13523	322	5	catelli	catelli	PROPN
aiti-13523	322	6	,	,	PUNCT
aiti-13523	322	7	s.	s.	PROPN
aiti-13523	322	8	pelosi	pelosi	PROPN
aiti-13523	322	9	,	,	PUNCT
aiti-13523	322	10	c.	c.	PROPN
aiti-13523	322	11	comito	comito	PROPN
aiti-13523	322	12	,	,	PUNCT
aiti-13523	322	13	c.	c.	PROPN
aiti-13523	322	14	pizzuti	pizzuti	PROPN
aiti-13523	322	15	,	,	PUNCT
aiti-13523	322	16	and	and	CCONJ
aiti-13523	322	17	m.	m.	PROPN
aiti-13523	322	18	esposito	esposito	PROPN
aiti-13523	322	19	,	,	PUNCT
aiti-13523	322	20	“	"	PUNCT
aiti-13523	322	21	lexicon	lexicon	NOUN
aiti-13523	322	22	-	-	PUNCT
aiti-13523	322	23	based	base	VERB
aiti-13523	322	24	sentiment	sentiment	NOUN
aiti-13523	322	25	analysis	analysis	NOUN
aiti-13523	322	26	to	to	PART
aiti-13523	322	27	detect	detect	VERB
aiti-13523	322	28	opinions	opinion	NOUN
aiti-13523	322	29	and	and	CCONJ
aiti-13523	322	30	attitude	attitude	NOUN
aiti-13523	322	31	towards	towards	ADP
aiti-13523	322	32	covid-19	covid-19	PROPN
aiti-13523	322	33	vaccines	vaccine	NOUN
aiti-13523	322	34	on	on	ADP
aiti-13523	322	35	twitter	twitter	NOUN
aiti-13523	322	36	in	in	ADP
aiti-13523	322	37	italy	italy	PROPN
aiti-13523	322	38	,	,	PUNCT
aiti-13523	322	39	”	"	PUNCT
aiti-13523	322	40	computers	computer	NOUN
aiti-13523	322	41	in	in	ADP
aiti-13523	322	42	biology	biology	NOUN
aiti-13523	322	43	and	and	CCONJ
aiti-13523	322	44	medicine	medicine	NOUN
aiti-13523	322	45	,	,	PUNCT
aiti-13523	322	46	vol	vol	NOUN
aiti-13523	322	47	.	.	PROPN
aiti-13523	322	48	158	158	NUM
aiti-13523	322	49	,	,	PUNCT
aiti-13523	322	50	article	article	NOUN
aiti-13523	322	51	no	no	NOUN
aiti-13523	322	52	.	.	PROPN
aiti-13523	322	53	106876	106876	NUM
aiti-13523	322	54	,	,	PUNCT
aiti-13523	322	55	may	may	AUX
aiti-13523	322	56	2023	2023	NUM
aiti-13523	322	57	.	.	PUNCT
aiti-13523	323	1	[	[	X
aiti-13523	323	2	8	8	NUM
aiti-13523	323	3	]	]	X
aiti-13523	323	4	d.	d.	PROPN
aiti-13523	323	5	c.	c.	PROPN
aiti-13523	323	6	j.	j.	PROPN
aiti-13523	323	7	w.	w.	PROPN
aiti-13523	323	8	wise	wise	PROPN
aiti-13523	323	9	,	,	PUNCT
aiti-13523	323	10	s.	s.	PROPN
aiti-13523	323	11	ambareesh	ambareesh	PROPN
aiti-13523	323	12	,	,	PUNCT
aiti-13523	323	13	p.	p.	PROPN
aiti-13523	323	14	babu	babu	PROPN
aiti-13523	323	15	,	,	PUNCT
aiti-13523	323	16	d.	d.	PROPN
aiti-13523	323	17	sugumar	sugumar	PROPN
aiti-13523	323	18	,	,	PUNCT
aiti-13523	323	19	j.	j.	PROPN
aiti-13523	323	20	p.	p.	PROPN
aiti-13523	323	21	bhimavarapu	bhimavarapu	PROPN
aiti-13523	323	22	,	,	PUNCT
aiti-13523	323	23	and	and	CCONJ
aiti-13523	323	24	a.	a.	PROPN
aiti-13523	323	25	s.	s.	PROPN
aiti-13523	323	26	kumar	kumar	PROPN
aiti-13523	323	27	,	,	PUNCT
aiti-13523	323	28	“	"	PUNCT
aiti-13523	323	29	latent	latent	ADJ
aiti-13523	323	30	semantic	semantic	ADJ
aiti-13523	323	31	analysis	analysis	NOUN
aiti-13523	323	32	based	base	VERB
aiti-13523	323	33	sentimental	sentimental	ADJ
aiti-13523	323	34	analysis	analysis	NOUN
aiti-13523	323	35	of	of	ADP
aiti-13523	323	36	tweets	tweet	NOUN
aiti-13523	323	37	in	in	ADP
aiti-13523	323	38	social	social	ADJ
aiti-13523	323	39	media	medium	NOUN
aiti-13523	323	40	for	for	ADP
aiti-13523	323	41	the	the	DET
aiti-13523	323	42	classification	classification	NOUN
aiti-13523	323	43	of	of	ADP
aiti-13523	323	44	cyberbullying	cyberbullye	VERB
aiti-13523	323	45	text	text	NOUN
aiti-13523	323	46	,	,	PUNCT
aiti-13523	323	47	”	"	PUNCT
aiti-13523	323	48	international	international	ADJ
aiti-13523	323	49	journal	journal	NOUN
aiti-13523	323	50	of	of	ADP
aiti-13523	323	51	intelligent	intelligent	ADJ
aiti-13523	323	52	systems	system	NOUN
aiti-13523	323	53	and	and	CCONJ
aiti-13523	323	54	applications	application	NOUN
aiti-13523	323	55	in	in	ADP
aiti-13523	323	56	engineering	engineering	NOUN
aiti-13523	323	57	,	,	PUNCT
aiti-13523	323	58	vol	vol	NOUN
aiti-13523	323	59	.	.	PROPN
aiti-13523	323	60	12	12	NUM
aiti-13523	323	61	,	,	PUNCT
aiti-13523	323	62	no	no	INTJ
aiti-13523	323	63	.	.	NOUN
aiti-13523	323	64	7s	7	NOUN
aiti-13523	323	65	,	,	PUNCT
aiti-13523	323	66	pp	pp	ADJ
aiti-13523	323	67	.	.	PUNCT
aiti-13523	324	1	26	26	NUM
aiti-13523	324	2	-	-	SYM
aiti-13523	324	3	35	35	NUM
aiti-13523	324	4	,	,	PUNCT
aiti-13523	324	5	2024	2024	NUM
aiti-13523	324	6	.	.	PUNCT
aiti-13523	325	1	[	[	X
aiti-13523	325	2	9	9	NUM
aiti-13523	325	3	]	]	X
aiti-13523	325	4	r.	r.	NOUN
aiti-13523	325	5	bhaskaran	bhaskaran	PROPN
aiti-13523	325	6	,	,	PUNCT
aiti-13523	325	7	s.	s.	PROPN
aiti-13523	325	8	saravanan	saravanan	PROPN
aiti-13523	325	9	,	,	PUNCT
aiti-13523	325	10	m.	m.	PROPN
aiti-13523	325	11	kavitha	kavitha	PROPN
aiti-13523	325	12	,	,	PUNCT
aiti-13523	325	13	c.	c.	PROPN
aiti-13523	325	14	jeyalakshmi	jeyalakshmi	PROPN
aiti-13523	325	15	,	,	PUNCT
aiti-13523	325	16	s.	s.	PROPN
aiti-13523	325	17	kadry	kadry	PROPN
aiti-13523	325	18	,	,	PUNCT
aiti-13523	325	19	h.	h.	PROPN
aiti-13523	325	20	t.	t.	PROPN
aiti-13523	325	21	rauf	rauf	PROPN
aiti-13523	325	22	,	,	PUNCT
aiti-13523	325	23	et	et	PROPN
aiti-13523	325	24	al	al	PROPN
aiti-13523	325	25	.	.	PROPN
aiti-13523	325	26	,	,	PUNCT
aiti-13523	325	27	“	"	PUNCT
aiti-13523	325	28	intelligent	intelligent	ADJ
aiti-13523	325	29	machine	machine	NOUN
aiti-13523	325	30	learning	learn	VERB
aiti-13523	325	31	with	with	ADP
aiti-13523	325	32	metaheuristics	metaheuristic	NOUN
aiti-13523	325	33	based	base	VERB
aiti-13523	325	34	sentiment	sentiment	NOUN
aiti-13523	325	35	analysis	analysis	NOUN
aiti-13523	325	36	and	and	CCONJ
aiti-13523	325	37	classification	classification	NOUN
aiti-13523	325	38	,	,	PUNCT
aiti-13523	325	39	”	"	PUNCT
aiti-13523	325	40	computer	computer	NOUN
aiti-13523	325	41	systems	system	NOUN
aiti-13523	325	42	science	science	NOUN
aiti-13523	325	43	and	and	CCONJ
aiti-13523	325	44	engineering	engineering	NOUN
aiti-13523	325	45	,	,	PUNCT
aiti-13523	325	46	vol	vol	NOUN
aiti-13523	325	47	.	.	PROPN
aiti-13523	325	48	44	44	NUM
aiti-13523	325	49	,	,	PUNCT
aiti-13523	325	50	no	no	INTJ
aiti-13523	325	51	.	.	NOUN
aiti-13523	325	52	1	1	NUM
aiti-13523	325	53	,	,	PUNCT
aiti-13523	325	54	pp	pp	ADJ
aiti-13523	325	55	.	.	PUNCT
aiti-13523	325	56	235	235	NUM
aiti-13523	325	57	-	-	SYM
aiti-13523	325	58	247	247	NUM
aiti-13523	325	59	,	,	PUNCT
aiti-13523	325	60	2023	2023	NUM
aiti-13523	325	61	.	.	PUNCT
aiti-13523	326	1	[	[	X
aiti-13523	326	2	10	10	NUM
aiti-13523	326	3	]	]	X
aiti-13523	326	4	y.	y.	PROPN
aiti-13523	326	5	y.	y.	PROPN
aiti-13523	326	6	tan	tan	PROPN
aiti-13523	326	7	,	,	PUNCT
aiti-13523	326	8	c.	c.	PROPN
aiti-13523	326	9	o.	o.	PROPN
aiti-13523	326	10	chow	chow	PROPN
aiti-13523	326	11	,	,	PUNCT
aiti-13523	326	12	j.	j.	PROPN
aiti-13523	326	13	kanesan	kanesan	PROPN
aiti-13523	326	14	,	,	PUNCT
aiti-13523	326	15	j.	j.	PROPN
aiti-13523	326	16	h.	h.	PROPN
aiti-13523	326	17	chuah	chuah	PROPN
aiti-13523	326	18	,	,	PUNCT
aiti-13523	326	19	and	and	CCONJ
aiti-13523	326	20	y.	y.	PROPN
aiti-13523	326	21	l.	l.	PROPN
aiti-13523	326	22	lim	lim	PROPN
aiti-13523	326	23	,	,	PUNCT
aiti-13523	326	24	“	"	PUNCT
aiti-13523	326	25	sentiment	sentiment	NOUN
aiti-13523	326	26	analysis	analysis	NOUN
aiti-13523	326	27	and	and	CCONJ
aiti-13523	326	28	sarcasm	sarcasm	NOUN
aiti-13523	326	29	detection	detection	NOUN
aiti-13523	326	30	using	use	VERB
aiti-13523	326	31	deep	deep	ADJ
aiti-13523	326	32	multi	multi	ADJ
aiti-13523	326	33	-	-	ADJ
aiti-13523	326	34	task	task	ADJ
aiti-13523	326	35	learning	learning	NOUN
aiti-13523	326	36	,	,	PUNCT
aiti-13523	326	37	”	"	PUNCT
aiti-13523	326	38	wireless	wireless	ADJ
aiti-13523	326	39	personal	personal	ADJ
aiti-13523	326	40	communications	communication	NOUN
aiti-13523	326	41	,	,	PUNCT
aiti-13523	326	42	vol	vol	NOUN
aiti-13523	326	43	.	.	PROPN
aiti-13523	326	44	129	129	NUM
aiti-13523	326	45	,	,	PUNCT
aiti-13523	326	46	no	no	INTJ
aiti-13523	326	47	.	.	NOUN
aiti-13523	326	48	3	3	NUM
aiti-13523	326	49	,	,	PUNCT
aiti-13523	326	50	pp	pp	ADJ
aiti-13523	326	51	.	.	PUNCT
aiti-13523	326	52	2213	2213	NUM
aiti-13523	326	53	-	-	SYM
aiti-13523	326	54	2237	2237	NUM
aiti-13523	326	55	,	,	PUNCT
aiti-13523	326	56	april	april	PROPN
aiti-13523	326	57	2023	2023	NUM
aiti-13523	326	58	.	.	PUNCT
aiti-13523	327	1	[	[	X
aiti-13523	327	2	11	11	NUM
aiti-13523	327	3	]	]	X
aiti-13523	327	4	g.	g.	PROPN
aiti-13523	327	5	meena	meena	PROPN
aiti-13523	327	6	,	,	PUNCT
aiti-13523	327	7	k.	k.	PROPN
aiti-13523	327	8	k.	k.	PROPN
aiti-13523	327	9	mohbey	mohbey	PROPN
aiti-13523	327	10	,	,	PUNCT
aiti-13523	327	11	s.	s.	PROPN
aiti-13523	327	12	kumar	kumar	PROPN
aiti-13523	327	13	,	,	PUNCT
aiti-13523	327	14	and	and	CCONJ
aiti-13523	327	15	k.	k.	PROPN
aiti-13523	327	16	lokesh	lokesh	PROPN
aiti-13523	327	17	,	,	PUNCT
aiti-13523	327	18	“	"	PUNCT
aiti-13523	327	19	a	a	DET
aiti-13523	327	20	hybrid	hybrid	ADJ
aiti-13523	327	21	deep	deep	ADJ
aiti-13523	327	22	learning	learning	NOUN
aiti-13523	327	23	approach	approach	NOUN
aiti-13523	327	24	for	for	ADP
aiti-13523	327	25	detecting	detect	VERB
aiti-13523	327	26	sentiment	sentiment	NOUN
aiti-13523	327	27	polarities	polarity	NOUN
aiti-13523	327	28	and	and	CCONJ
aiti-13523	327	29	knowledge	knowledge	NOUN
aiti-13523	327	30	graph	graph	NOUN
aiti-13523	327	31	representation	representation	NOUN
aiti-13523	327	32	on	on	ADP
aiti-13523	327	33	monkeypox	monkeypox	NOUN
aiti-13523	327	34	tweets	tweet	NOUN
aiti-13523	327	35	,	,	PUNCT
aiti-13523	327	36	”	"	PUNCT
aiti-13523	327	37	decision	decision	NOUN
aiti-13523	327	38	analytics	analytic	NOUN
aiti-13523	327	39	journal	journal	NOUN
aiti-13523	327	40	,	,	PUNCT
aiti-13523	327	41	vol	vol	NOUN
aiti-13523	327	42	.	.	PROPN
aiti-13523	327	43	7	7	NUM
aiti-13523	327	44	,	,	PUNCT
aiti-13523	327	45	article	article	NOUN
aiti-13523	327	46	no	no	NOUN
aiti-13523	327	47	.	.	PROPN
aiti-13523	327	48	100243	100243	NUM
aiti-13523	327	49	,	,	PUNCT
aiti-13523	327	50	june	june	PROPN
aiti-13523	327	51	2023	2023	NUM
aiti-13523	327	52	.	.	PUNCT
aiti-13523	328	1	[	[	X
aiti-13523	328	2	12	12	NUM
aiti-13523	328	3	]	]	PUNCT
aiti-13523	328	4	r.	r.	PROPN
aiti-13523	328	5	k.	k.	PROPN
aiti-13523	328	6	das	das	PROPN
aiti-13523	328	7	,	,	PUNCT
aiti-13523	328	8	m.	m.	PROPN
aiti-13523	328	9	islam	islam	PROPN
aiti-13523	328	10	,	,	PUNCT
aiti-13523	328	11	m.	m.	PROPN
aiti-13523	328	12	m.	m.	PROPN
aiti-13523	328	13	hasan	hasan	PROPN
aiti-13523	328	14	,	,	PUNCT
aiti-13523	328	15	s.	s.	PROPN
aiti-13523	328	16	razia	razia	PROPN
aiti-13523	328	17	,	,	PUNCT
aiti-13523	328	18	m.	m.	NOUN
aiti-13523	328	19	hassan	hassan	PROPN
aiti-13523	328	20	,	,	PUNCT
aiti-13523	328	21	and	and	CCONJ
aiti-13523	328	22	s.	s.	PROPN
aiti-13523	328	23	a.	a.	PROPN
aiti-13523	328	24	khushbu	khushbu	PROPN
aiti-13523	328	25	,	,	PUNCT
aiti-13523	328	26	“	"	PUNCT
aiti-13523	328	27	sentiment	sentiment	NOUN
aiti-13523	328	28	analysis	analysis	NOUN
aiti-13523	328	29	in	in	ADP
aiti-13523	328	30	multilingual	multilingual	ADJ
aiti-13523	328	31	context	context	NOUN
aiti-13523	328	32	:	:	PUNCT
aiti-13523	328	33	comparative	comparative	ADJ
aiti-13523	328	34	analysis	analysis	NOUN
aiti-13523	328	35	of	of	ADP
aiti-13523	328	36	machine	machine	NOUN
aiti-13523	328	37	learning	learning	NOUN
aiti-13523	328	38	and	and	CCONJ
aiti-13523	328	39	hybrid	hybrid	ADJ
aiti-13523	328	40	deep	deep	ADJ
aiti-13523	328	41	learning	learning	NOUN
aiti-13523	328	42	models	model	NOUN
aiti-13523	328	43	,	,	PUNCT
aiti-13523	328	44	”	"	PUNCT
aiti-13523	328	45	heliyon	heliyon	NOUN
aiti-13523	328	46	,	,	PUNCT
aiti-13523	328	47	vol	vol	NOUN
aiti-13523	328	48	.	.	PROPN
aiti-13523	329	1	9	9	NUM
aiti-13523	329	2	,	,	PUNCT
aiti-13523	329	3	no	no	INTJ
aiti-13523	329	4	.	.	NOUN
aiti-13523	329	5	9	9	NUM
aiti-13523	329	6	,	,	PUNCT
aiti-13523	329	7	article	article	NOUN
aiti-13523	329	8	no	no	INTJ
aiti-13523	329	9	.	.	PUNCT
aiti-13523	330	1	e20281	e20281	PROPN
aiti-13523	330	2	,	,	PUNCT
aiti-13523	330	3	september	september	PROPN
aiti-13523	330	4	2023	2023	NUM
aiti-13523	330	5	.	.	PUNCT
aiti-13523	331	1	[	[	X
aiti-13523	331	2	13	13	NUM
aiti-13523	331	3	]	]	PUNCT
aiti-13523	331	4	a.	a.	NOUN
aiti-13523	331	5	umair	umair	NOUN
aiti-13523	331	6	,	,	PUNCT
aiti-13523	331	7	e.	e.	PROPN
aiti-13523	331	8	masciari	masciari	PROPN
aiti-13523	331	9	,	,	PUNCT
aiti-13523	331	10	and	and	CCONJ
aiti-13523	331	11	m.	m.	PROPN
aiti-13523	331	12	h.	h.	PROPN
aiti-13523	331	13	ullah	ullah	PROPN
aiti-13523	331	14	,	,	PUNCT
aiti-13523	331	15	“	"	PUNCT
aiti-13523	331	16	vaccine	vaccine	NOUN
aiti-13523	331	17	sentiment	sentiment	NOUN
aiti-13523	331	18	analysis	analysis	NOUN
aiti-13523	331	19	using	use	VERB
aiti-13523	331	20	bert	bert	PROPN
aiti-13523	331	21	+	+	CCONJ
aiti-13523	331	22	nbsvm	nbsvm	NOUN
aiti-13523	331	23	and	and	CCONJ
aiti-13523	331	24	geo	geo	PROPN
aiti-13523	331	25	-	-	PUNCT
aiti-13523	331	26	spatial	spatial	ADJ
aiti-13523	331	27	approaches	approach	NOUN
aiti-13523	331	28	,	,	PUNCT
aiti-13523	331	29	”	"	PUNCT
aiti-13523	331	30	the	the	DET
aiti-13523	331	31	journal	journal	NOUN
aiti-13523	331	32	of	of	ADP
aiti-13523	331	33	supercomputing	supercomputing	NOUN
aiti-13523	331	34	,	,	PUNCT
aiti-13523	331	35	vol	vol	NOUN
aiti-13523	331	36	.	.	PROPN
aiti-13523	331	37	79	79	NUM
aiti-13523	331	38	,	,	PUNCT
aiti-13523	331	39	no	no	INTJ
aiti-13523	331	40	.	.	NOUN
aiti-13523	331	41	15	15	NUM
aiti-13523	331	42	,	,	PUNCT
aiti-13523	331	43	pp	pp	ADJ
aiti-13523	331	44	.	.	PUNCT
aiti-13523	331	45	17355	17355	NUM
aiti-13523	331	46	-	-	SYM
aiti-13523	331	47	17385	17385	NUM
aiti-13523	331	48	,	,	PUNCT
aiti-13523	331	49	october	october	PROPN
aiti-13523	331	50	2023	2023	NUM
aiti-13523	331	51	.	.	PUNCT
aiti-13523	332	1	142	142	NUM
aiti-13523	332	2	advances	advance	NOUN
aiti-13523	332	3	in	in	ADP
aiti-13523	332	4	technology	technology	NOUN
aiti-13523	332	5	innovation	innovation	NOUN
aiti-13523	332	6	,	,	PUNCT
aiti-13523	332	7	vol	vol	NOUN
aiti-13523	332	8	.	.	PROPN
aiti-13523	332	9	9	9	NUM
aiti-13523	332	10	,	,	PUNCT
aiti-13523	332	11	no	no	INTJ
aiti-13523	332	12	.	.	NOUN
aiti-13523	332	13	2	2	NUM
aiti-13523	332	14	,	,	PUNCT
aiti-13523	332	15	2024	2024	NUM
aiti-13523	332	16	,	,	PUNCT
aiti-13523	332	17	pp	pp	ADJ
aiti-13523	332	18	.	.	PUNCT
aiti-13523	333	1	129	129	NUM
aiti-13523	333	2	-	-	SYM
aiti-13523	333	3	142	142	NUM
aiti-13523	334	1	[	[	X
aiti-13523	334	2	14	14	NUM
aiti-13523	334	3	]	]	X
aiti-13523	334	4	g.	g.	PROPN
aiti-13523	334	5	b.	b.	PROPN
aiti-13523	334	6	mohammad	mohammad	PROPN
aiti-13523	334	7	,	,	PUNCT
aiti-13523	334	8	s.	s.	PROPN
aiti-13523	334	9	potluri	potluri	PROPN
aiti-13523	334	10	,	,	PUNCT
aiti-13523	334	11	a.	a.	PROPN
aiti-13523	334	12	kumar	kumar	PROPN
aiti-13523	334	13	,	,	PUNCT
aiti-13523	334	14	r.	r.	PROPN
aiti-13523	334	15	kumar	kumar	PROPN
aiti-13523	334	16	,	,	PUNCT
aiti-13523	334	17	p.	p.	PROPN
aiti-13523	334	18	dileep	dileep	PROPN
aiti-13523	334	19	,	,	PUNCT
aiti-13523	334	20	r.	r.	PROPN
aiti-13523	334	21	tiwari	tiwari	PROPN
aiti-13523	334	22	,	,	PUNCT
aiti-13523	334	23	et	et	PROPN
aiti-13523	334	24	al	al	PROPN
aiti-13523	334	25	.	.	PROPN
aiti-13523	334	26	,	,	PUNCT
aiti-13523	334	27	“	"	PUNCT
aiti-13523	334	28	an	an	DET
aiti-13523	334	29	artificial	artificial	ADJ
aiti-13523	334	30	intelligence	intelligence	NOUN
aiti-13523	334	31	-	-	PUNCT
aiti-13523	334	32	based	base	VERB
aiti-13523	334	33	reactive	reactive	ADJ
aiti-13523	334	34	health	health	NOUN
aiti-13523	334	35	care	care	NOUN
aiti-13523	334	36	system	system	NOUN
aiti-13523	334	37	for	for	ADP
aiti-13523	334	38	emotion	emotion	NOUN
aiti-13523	334	39	detections	detection	NOUN
aiti-13523	334	40	,	,	PUNCT
aiti-13523	334	41	”	"	PUNCT
aiti-13523	334	42	computational	computational	ADJ
aiti-13523	334	43	intelligence	intelligence	NOUN
aiti-13523	334	44	and	and	CCONJ
aiti-13523	334	45	neuroscience	neuroscience	NOUN
aiti-13523	334	46	,	,	PUNCT
aiti-13523	334	47	vol	vol	NOUN
aiti-13523	334	48	.	.	NOUN
aiti-13523	334	49	2022	2022	NUM
aiti-13523	334	50	,	,	PUNCT
aiti-13523	334	51	article	article	NOUN
aiti-13523	334	52	no	no	NOUN
aiti-13523	334	53	.	.	PROPN
aiti-13523	334	54	8787023	8787023	NUM
aiti-13523	334	55	,	,	PUNCT
aiti-13523	334	56	2022	2022	NUM
aiti-13523	334	57	,	,	PUNCT
aiti-13523	334	58	[	[	X
aiti-13523	334	59	15	15	NUM
aiti-13523	334	60	]	]	X
aiti-13523	334	61	k.	k.	PROPN
aiti-13523	334	62	denecke	denecke	PROPN
aiti-13523	334	63	and	and	CCONJ
aiti-13523	334	64	d.	d.	PROPN
aiti-13523	334	65	reichenpfader	reichenpfader	PROPN
aiti-13523	334	66	,	,	PUNCT
aiti-13523	334	67	“	"	PUNCT
aiti-13523	334	68	sentiment	sentiment	NOUN
aiti-13523	334	69	analysis	analysis	NOUN
aiti-13523	334	70	of	of	ADP
aiti-13523	334	71	clinical	clinical	ADJ
aiti-13523	334	72	narratives	narrative	NOUN
aiti-13523	334	73	:	:	PUNCT
aiti-13523	334	74	a	a	DET
aiti-13523	334	75	scoping	scope	VERB
aiti-13523	334	76	review	review	NOUN
aiti-13523	334	77	,	,	PUNCT
aiti-13523	334	78	”	"	PUNCT
aiti-13523	334	79	journal	journal	NOUN
aiti-13523	334	80	of	of	ADP
aiti-13523	334	81	biomedical	biomedical	ADJ
aiti-13523	334	82	informatics	informatic	NOUN
aiti-13523	334	83	,	,	PUNCT
aiti-13523	334	84	vol	vol	NOUN
aiti-13523	334	85	.	.	PROPN
aiti-13523	334	86	140	140	NUM
aiti-13523	334	87	,	,	PUNCT
aiti-13523	334	88	article	article	NOUN
aiti-13523	334	89	no	no	NOUN
aiti-13523	334	90	.	.	PUNCT
aiti-13523	334	91	104336	104336	NUM
aiti-13523	334	92	,	,	PUNCT
aiti-13523	334	93	april	april	PROPN
aiti-13523	334	94	2023	2023	NUM
aiti-13523	334	95	.	.	PUNCT
aiti-13523	335	1	[	[	X
aiti-13523	335	2	16	16	NUM
aiti-13523	335	3	]	]	X
aiti-13523	335	4	s.	s.	PROPN
aiti-13523	335	5	gohil	gohil	PROPN
aiti-13523	335	6	,	,	PUNCT
aiti-13523	335	7	s.	s.	PROPN
aiti-13523	335	8	vuik	vuik	NOUN
aiti-13523	335	9	,	,	PUNCT
aiti-13523	335	10	and	and	CCONJ
aiti-13523	335	11	a.	a.	NOUN
aiti-13523	335	12	darzi	darzi	NOUN
aiti-13523	335	13	,	,	PUNCT
aiti-13523	335	14	“	"	PUNCT
aiti-13523	335	15	sentiment	sentiment	NOUN
aiti-13523	335	16	analysis	analysis	NOUN
aiti-13523	335	17	of	of	ADP
aiti-13523	335	18	health	health	NOUN
aiti-13523	335	19	care	care	NOUN
aiti-13523	335	20	tweets	tweet	NOUN
aiti-13523	335	21	:	:	PUNCT
aiti-13523	335	22	review	review	NOUN
aiti-13523	335	23	of	of	ADP
aiti-13523	335	24	the	the	DET
aiti-13523	335	25	methods	method	NOUN
aiti-13523	335	26	used	use	VERB
aiti-13523	335	27	,	,	PUNCT
aiti-13523	335	28	”	"	PUNCT
aiti-13523	335	29	jmir	jmir	PROPN
aiti-13523	335	30	public	public	ADJ
aiti-13523	335	31	health	health	NOUN
aiti-13523	335	32	and	and	CCONJ
aiti-13523	335	33	surveillance	surveillance	NOUN
aiti-13523	335	34	,	,	PUNCT
aiti-13523	335	35	vol	vol	NOUN
aiti-13523	335	36	.	.	PROPN
aiti-13523	335	37	4	4	NUM
aiti-13523	335	38	,	,	PUNCT
aiti-13523	335	39	no	no	INTJ
aiti-13523	335	40	.	.	NOUN
aiti-13523	335	41	2	2	NUM
aiti-13523	335	42	,	,	PUNCT
aiti-13523	335	43	article	article	NOUN
aiti-13523	335	44	no	no	INTJ
aiti-13523	335	45	.	.	PUNCT
aiti-13523	335	46	e43	e43	PROPN
aiti-13523	335	47	,	,	PUNCT
aiti-13523	335	48	april	april	PROPN
aiti-13523	335	49	-	-	PUNCT
aiti-13523	335	50	june	june	PROPN
aiti-13523	335	51	2018	2018	NUM
aiti-13523	335	52	.	.	PUNCT
aiti-13523	336	1	[	[	X
aiti-13523	336	2	17	17	NUM
aiti-13523	336	3	]	]	PUNCT
aiti-13523	336	4	p.	p.	NOUN
aiti-13523	336	5	padmavathy	padmavathy	ADJ
aiti-13523	336	6	and	and	CCONJ
aiti-13523	336	7	s.	s.	PROPN
aiti-13523	336	8	pakkir	pakkir	PROPN
aiti-13523	336	9	mohideen	mohideen	PROPN
aiti-13523	336	10	,	,	PUNCT
aiti-13523	336	11	“	"	PUNCT
aiti-13523	336	12	an	an	DET
aiti-13523	336	13	efficient	efficient	ADJ
aiti-13523	336	14	two	two	NUM
aiti-13523	336	15	-	-	PUNCT
aiti-13523	336	16	pass	pass	NOUN
aiti-13523	336	17	classifier	classifier	NOUN
aiti-13523	336	18	system	system	NOUN
aiti-13523	336	19	for	for	ADP
aiti-13523	336	20	patient	patient	ADJ
aiti-13523	336	21	opinion	opinion	NOUN
aiti-13523	336	22	mining	mining	NOUN
aiti-13523	336	23	to	to	PART
aiti-13523	336	24	analyze	analyze	VERB
aiti-13523	336	25	drugs	drug	NOUN
aiti-13523	336	26	satisfaction	satisfaction	NOUN
aiti-13523	336	27	,	,	PUNCT
aiti-13523	336	28	”	"	PUNCT
aiti-13523	336	29	biomedical	biomedical	ADJ
aiti-13523	336	30	signal	signal	NOUN
aiti-13523	336	31	processing	processing	NOUN
aiti-13523	336	32	and	and	CCONJ
aiti-13523	336	33	control	control	NOUN
aiti-13523	336	34	,	,	PUNCT
aiti-13523	336	35	vol	vol	NOUN
aiti-13523	336	36	.	.	PROPN
aiti-13523	336	37	57	57	NUM
aiti-13523	336	38	,	,	PUNCT
aiti-13523	336	39	article	article	NOUN
aiti-13523	336	40	no	no	NOUN
aiti-13523	336	41	.	.	PROPN
aiti-13523	336	42	101755	101755	NUM
aiti-13523	336	43	,	,	PUNCT
aiti-13523	336	44	march	march	PROPN
aiti-13523	336	45	2020	2020	NUM
aiti-13523	336	46	.	.	PUNCT
aiti-13523	337	1	[	[	X
aiti-13523	337	2	18	18	NUM
aiti-13523	337	3	]	]	X
aiti-13523	337	4	y.	y.	PROPN
aiti-13523	337	5	bhangdia	bhangdia	PROPN
aiti-13523	337	6	,	,	PUNCT
aiti-13523	337	7	r.	r.	PROPN
aiti-13523	337	8	bhansali	bhansali	PROPN
aiti-13523	337	9	,	,	PUNCT
aiti-13523	337	10	n.	n.	PROPN
aiti-13523	337	11	chaudhari	chaudhari	PROPN
aiti-13523	337	12	,	,	PUNCT
aiti-13523	337	13	d.	d.	PROPN
aiti-13523	337	14	chandnani	chandnani	PROPN
aiti-13523	337	15	,	,	PUNCT
aiti-13523	337	16	and	and	CCONJ
aiti-13523	337	17	m.	m.	PROPN
aiti-13523	337	18	l.	l.	PROPN
aiti-13523	337	19	dhore	dhore	PROPN
aiti-13523	337	20	,	,	PUNCT
aiti-13523	337	21	“	"	PUNCT
aiti-13523	337	22	speech	speech	NOUN
aiti-13523	337	23	emotion	emotion	NOUN
aiti-13523	337	24	recognition	recognition	NOUN
aiti-13523	337	25	and	and	CCONJ
aiti-13523	337	26	sentiment	sentiment	NOUN
aiti-13523	337	27	analysis	analysis	NOUN
aiti-13523	337	28	based	base	VERB
aiti-13523	337	29	therapist	therapist	NOUN
aiti-13523	337	30	bot	bot	NOUN
aiti-13523	337	31	,	,	PUNCT
aiti-13523	337	32	”	"	PUNCT
aiti-13523	337	33	third	third	ADJ
aiti-13523	337	34	international	international	ADJ
aiti-13523	337	35	conference	conference	NOUN
aiti-13523	337	36	on	on	ADP
aiti-13523	337	37	inventive	inventive	ADJ
aiti-13523	337	38	research	research	NOUN
aiti-13523	337	39	in	in	ADP
aiti-13523	337	40	computing	computing	NOUN
aiti-13523	337	41	applications	application	NOUN
aiti-13523	337	42	,	,	PUNCT
aiti-13523	337	43	pp	pp	ADJ
aiti-13523	337	44	.	.	PUNCT
aiti-13523	338	1	96	96	NUM
aiti-13523	338	2	-	-	SYM
aiti-13523	338	3	101	101	NUM
aiti-13523	338	4	,	,	PUNCT
aiti-13523	338	5	september	september	PROPN
aiti-13523	338	6	2021	2021	NUM
aiti-13523	338	7	.	.	PUNCT
aiti-13523	339	1	[	[	X
aiti-13523	339	2	19	19	NUM
aiti-13523	339	3	]	]	PUNCT
aiti-13523	339	4	a.	a.	NOUN
aiti-13523	339	5	saranya	saranya	PROPN
aiti-13523	339	6	and	and	CCONJ
aiti-13523	339	7	r.	r.	PROPN
aiti-13523	339	8	subhashini	subhashini	PROPN
aiti-13523	339	9	,	,	PUNCT
aiti-13523	339	10	“	"	PUNCT
aiti-13523	339	11	a	a	DET
aiti-13523	339	12	systematic	systematic	ADJ
aiti-13523	339	13	review	review	NOUN
aiti-13523	339	14	of	of	ADP
aiti-13523	339	15	explainable	explainable	ADJ
aiti-13523	339	16	artificial	artificial	ADJ
aiti-13523	339	17	intelligence	intelligence	NOUN
aiti-13523	339	18	models	model	NOUN
aiti-13523	339	19	and	and	CCONJ
aiti-13523	339	20	applications	application	NOUN
aiti-13523	339	21	:	:	PUNCT
aiti-13523	339	22	recent	recent	ADJ
aiti-13523	339	23	developments	development	NOUN
aiti-13523	339	24	and	and	CCONJ
aiti-13523	339	25	future	future	ADJ
aiti-13523	339	26	trends	trend	NOUN
aiti-13523	339	27	,	,	PUNCT
aiti-13523	339	28	”	"	PUNCT
aiti-13523	339	29	decision	decision	NOUN
aiti-13523	339	30	analytics	analytic	NOUN
aiti-13523	339	31	journal	journal	NOUN
aiti-13523	339	32	,	,	PUNCT
aiti-13523	339	33	vol	vol	NOUN
aiti-13523	339	34	.	.	PROPN
aiti-13523	339	35	7	7	NUM
aiti-13523	339	36	,	,	PUNCT
aiti-13523	339	37	article	article	NOUN
aiti-13523	339	38	no	no	NOUN
aiti-13523	339	39	.	.	PROPN
aiti-13523	339	40	100230	100230	NUM
aiti-13523	339	41	,	,	PUNCT
aiti-13523	339	42	june	june	PROPN
aiti-13523	339	43	2023	2023	NUM
aiti-13523	339	44	.	.	PUNCT
aiti-13523	340	1	[	[	X
aiti-13523	340	2	20	20	NUM
aiti-13523	340	3	]	]	PUNCT
aiti-13523	340	4	m.	m.	NOUN
aiti-13523	340	5	t.	t.	PROPN
aiti-13523	340	6	ribeiro	ribeiro	PROPN
aiti-13523	340	7	,	,	PUNCT
aiti-13523	340	8	s.	s.	PROPN
aiti-13523	340	9	singh	singh	PROPN
aiti-13523	340	10	,	,	PUNCT
aiti-13523	340	11	and	and	CCONJ
aiti-13523	340	12	c.	c.	PROPN
aiti-13523	340	13	guestrin	guestrin	PROPN
aiti-13523	340	14	,	,	PUNCT
aiti-13523	340	15	“	"	PUNCT
aiti-13523	340	16	‘	'	PUNCT
aiti-13523	340	17	why	why	SCONJ
aiti-13523	340	18	should	should	AUX
aiti-13523	340	19	i	i	PRON
aiti-13523	340	20	trust	trust	VERB
aiti-13523	340	21	you	you	PRON
aiti-13523	340	22	?	?	PUNCT
aiti-13523	340	23	’	'	PUNCT
aiti-13523	340	24	:	:	PUNCT
aiti-13523	340	25	explaining	explain	VERB
aiti-13523	340	26	the	the	DET
aiti-13523	340	27	predictions	prediction	NOUN
aiti-13523	340	28	of	of	ADP
aiti-13523	340	29	any	any	DET
aiti-13523	340	30	classifier	classifier	NOUN
aiti-13523	340	31	,	,	PUNCT
aiti-13523	340	32	”	"	PUNCT
aiti-13523	340	33	proceedings	proceeding	NOUN
aiti-13523	340	34	of	of	ADP
aiti-13523	340	35	the	the	DET
aiti-13523	340	36	22nd	22nd	PROPN
aiti-13523	340	37	acm	acm	PROPN
aiti-13523	340	38	sigkdd	sigkdd	PROPN
aiti-13523	340	39	international	international	ADJ
aiti-13523	340	40	conference	conference	NOUN
aiti-13523	340	41	on	on	ADP
aiti-13523	340	42	knowledge	knowledge	NOUN
aiti-13523	340	43	discovery	discovery	PROPN
aiti-13523	340	44	and	and	CCONJ
aiti-13523	340	45	data	datum	NOUN
aiti-13523	340	46	mining	mining	NOUN
aiti-13523	340	47	,	,	PUNCT
aiti-13523	340	48	pp	pp	ADJ
aiti-13523	340	49	.	.	PUNCT
aiti-13523	341	1	11351144	11351144	NUM
aiti-13523	341	2	,	,	PUNCT
aiti-13523	341	3	august	august	PROPN
aiti-13523	341	4	2016	2016	NUM
aiti-13523	341	5	.	.	PUNCT
aiti-13523	342	1	[	[	X
aiti-13523	342	2	21	21	NUM
aiti-13523	342	3	]	]	X
aiti-13523	342	4	i.	i.	PROPN
aiti-13523	342	5	mani	mani	PROPN
aiti-13523	342	6	and	and	CCONJ
aiti-13523	342	7	j.	j.	PROPN
aiti-13523	342	8	zhang	zhang	PROPN
aiti-13523	342	9	,	,	PUNCT
aiti-13523	342	10	“	"	PUNCT
aiti-13523	342	11	knn	knn	PROPN
aiti-13523	342	12	approach	approach	NOUN
aiti-13523	342	13	to	to	ADP
aiti-13523	342	14	unbalanced	unbalanced	ADJ
aiti-13523	342	15	data	datum	NOUN
aiti-13523	342	16	distributions	distribution	NOUN
aiti-13523	342	17	:	:	PUNCT
aiti-13523	342	18	a	a	DET
aiti-13523	342	19	case	case	NOUN
aiti-13523	342	20	study	study	NOUN
aiti-13523	342	21	involving	involve	VERB
aiti-13523	342	22	information	information	NOUN
aiti-13523	342	23	extraction	extraction	NOUN
aiti-13523	342	24	,	,	PUNCT
aiti-13523	342	25	”	"	PUNCT
aiti-13523	342	26	proceedings	proceeding	NOUN
aiti-13523	342	27	of	of	ADP
aiti-13523	342	28	workshop	workshop	NOUN
aiti-13523	342	29	on	on	ADP
aiti-13523	342	30	learning	learn	VERB
aiti-13523	342	31	from	from	ADP
aiti-13523	342	32	imbalanced	imbalanced	ADJ
aiti-13523	342	33	datasets	dataset	NOUN
aiti-13523	342	34	,	,	PUNCT
aiti-13523	342	35	pp.1	pp.1	NOUN
aiti-13523	342	36	-	-	PUNCT
aiti-13523	342	37	7	7	NUM
aiti-13523	342	38	,	,	PUNCT
aiti-13523	342	39	august	august	PROPN
aiti-13523	342	40	2003	2003	NUM
aiti-13523	342	41	.	.	PUNCT
aiti-13523	343	1	[	[	X
aiti-13523	343	2	22	22	NUM
aiti-13523	343	3	]	]	PUNCT
aiti-13523	343	4	a.	a.	NOUN
aiti-13523	343	5	fernandez	fernandez	PROPN
aiti-13523	343	6	,	,	PUNCT
aiti-13523	343	7	s.	s.	PROPN
aiti-13523	343	8	garcia	garcia	PROPN
aiti-13523	343	9	,	,	PUNCT
aiti-13523	343	10	f.	f.	PROPN
aiti-13523	343	11	herrera	herrera	PROPN
aiti-13523	343	12	,	,	PUNCT
aiti-13523	343	13	and	and	CCONJ
aiti-13523	343	14	n.v	n.v	PROPN
aiti-13523	343	15	.	.	PROPN
aiti-13523	343	16	chawla	chawla	PROPN
aiti-13523	343	17	,	,	PUNCT
aiti-13523	343	18	“	"	PUNCT
aiti-13523	343	19	smote	smote	VERB
aiti-13523	343	20	for	for	ADP
aiti-13523	343	21	learning	learn	VERB
aiti-13523	343	22	from	from	ADP
aiti-13523	343	23	imbalanced	imbalanced	ADJ
aiti-13523	343	24	data	datum	NOUN
aiti-13523	343	25	:	:	PUNCT
aiti-13523	343	26	progress	progress	NOUN
aiti-13523	343	27	and	and	CCONJ
aiti-13523	343	28	challenges	challenge	NOUN
aiti-13523	343	29	,	,	PUNCT
aiti-13523	343	30	marking	mark	VERB
aiti-13523	343	31	the	the	DET
aiti-13523	343	32	15	15	NUM
aiti-13523	343	33	-	-	PUNCT
aiti-13523	343	34	year	year	NOUN
aiti-13523	343	35	anniversary	anniversary	NOUN
aiti-13523	343	36	,	,	PUNCT
aiti-13523	343	37	”	"	PUNCT
aiti-13523	343	38	journal	journal	NOUN
aiti-13523	343	39	of	of	ADP
aiti-13523	343	40	artificial	artificial	ADJ
aiti-13523	343	41	intelligence	intelligence	NOUN
aiti-13523	343	42	research	research	NOUN
aiti-13523	343	43	,	,	PUNCT
aiti-13523	343	44	vol	vol	NOUN
aiti-13523	343	45	.	.	PROPN
aiti-13523	343	46	61	61	NUM
aiti-13523	343	47	,	,	PUNCT
aiti-13523	343	48	pp	pp	ADJ
aiti-13523	343	49	.	.	PUNCT
aiti-13523	343	50	863	863	NUM
aiti-13523	343	51	-	-	SYM
aiti-13523	343	52	905	905	NUM
aiti-13523	343	53	,	,	PUNCT
aiti-13523	343	54	2018	2018	NUM
aiti-13523	343	55	.	.	PUNCT
aiti-13523	344	1	[	[	X
aiti-13523	344	2	23	23	NUM
aiti-13523	344	3	]	]	X
aiti-13523	344	4	h.	h.	PROPN
aiti-13523	344	5	he	he	PRON
aiti-13523	344	6	,	,	PUNCT
aiti-13523	344	7	y.	y.	PROPN
aiti-13523	344	8	bai	bai	PROPN
aiti-13523	344	9	,	,	PUNCT
aiti-13523	344	10	e.	e.	PROPN
aiti-13523	344	11	a.	a.	PROPN
aiti-13523	344	12	garcia	garcia	PROPN
aiti-13523	344	13	,	,	PUNCT
aiti-13523	344	14	and	and	CCONJ
aiti-13523	344	15	s.	s.	PROPN
aiti-13523	344	16	li	li	PROPN
aiti-13523	344	17	,	,	PUNCT
aiti-13523	344	18	“	"	PUNCT
aiti-13523	344	19	adasyn	adasyn	NOUN
aiti-13523	344	20	:	:	PUNCT
aiti-13523	344	21	adaptive	adaptive	ADJ
aiti-13523	344	22	synthetic	synthetic	ADJ
aiti-13523	344	23	sampling	sample	VERB
aiti-13523	344	24	approach	approach	NOUN
aiti-13523	344	25	for	for	ADP
aiti-13523	344	26	imbalanced	imbalanced	ADJ
aiti-13523	344	27	learning	learning	NOUN
aiti-13523	344	28	,	,	PUNCT
aiti-13523	344	29	”	"	PUNCT
aiti-13523	344	30	ieee	ieee	PROPN
aiti-13523	344	31	international	international	ADJ
aiti-13523	344	32	joint	joint	ADJ
aiti-13523	344	33	conference	conference	NOUN
aiti-13523	344	34	on	on	ADP
aiti-13523	344	35	neural	neural	ADJ
aiti-13523	344	36	networks	network	NOUN
aiti-13523	344	37	(	(	PUNCT
aiti-13523	344	38	ieee	ieee	PROPN
aiti-13523	344	39	world	world	PROPN
aiti-13523	344	40	congress	congress	PROPN
aiti-13523	344	41	on	on	ADP
aiti-13523	344	42	computational	computational	ADJ
aiti-13523	344	43	intelligence	intelligence	NOUN
aiti-13523	344	44	)	)	PUNCT
aiti-13523	344	45	,	,	PUNCT
aiti-13523	344	46	pp	pp	ADP
aiti-13523	344	47	.	.	PUNCT
aiti-13523	344	48	1322	1322	NUM
aiti-13523	344	49	-	-	SYM
aiti-13523	344	50	1328	1328	NUM
aiti-13523	344	51	,	,	PUNCT
aiti-13523	344	52	june	june	PROPN
aiti-13523	344	53	2008	2008	NUM
aiti-13523	344	54	.	.	PUNCT
aiti-13523	345	1	[	[	X
aiti-13523	345	2	24	24	NUM
aiti-13523	345	3	]	]	X
aiti-13523	345	4	y.	y.	PROPN
aiti-13523	345	5	zhang	zhang	PROPN
aiti-13523	345	6	,	,	PUNCT
aiti-13523	345	7	r.	r.	PROPN
aiti-13523	345	8	jin	jin	PROPN
aiti-13523	345	9	,	,	PUNCT
aiti-13523	345	10	and	and	CCONJ
aiti-13523	345	11	z.	z.	PROPN
aiti-13523	345	12	h.	h.	PROPN
aiti-13523	345	13	zhou	zhou	PROPN
aiti-13523	345	14	,	,	PUNCT
aiti-13523	345	15	“	"	PUNCT
aiti-13523	345	16	understanding	understand	VERB
aiti-13523	345	17	bag	bag	NOUN
aiti-13523	345	18	-	-	PUNCT
aiti-13523	345	19	of	of	ADP
aiti-13523	345	20	-	-	PUNCT
aiti-13523	345	21	words	word	NOUN
aiti-13523	345	22	model	model	NOUN
aiti-13523	345	23	:	:	PUNCT
aiti-13523	345	24	a	a	DET
aiti-13523	345	25	statistical	statistical	ADJ
aiti-13523	345	26	framework	framework	NOUN
aiti-13523	345	27	,	,	PUNCT
aiti-13523	345	28	”	"	PUNCT
aiti-13523	345	29	international	international	ADJ
aiti-13523	345	30	journal	journal	NOUN
aiti-13523	345	31	of	of	ADP
aiti-13523	345	32	machine	machine	NOUN
aiti-13523	345	33	learning	learning	NOUN
aiti-13523	345	34	and	and	CCONJ
aiti-13523	345	35	cybernetics	cybernetic	NOUN
aiti-13523	345	36	,	,	PUNCT
aiti-13523	345	37	vol	vol	NOUN
aiti-13523	345	38	.	.	PROPN
aiti-13523	345	39	1	1	NUM
aiti-13523	345	40	,	,	PUNCT
aiti-13523	345	41	no	no	INTJ
aiti-13523	345	42	.	.	NOUN
aiti-13523	345	43	1	1	NUM
aiti-13523	345	44	-	-	SYM
aiti-13523	345	45	4	4	NUM
aiti-13523	345	46	,	,	PUNCT
aiti-13523	345	47	pp	pp	ADJ
aiti-13523	345	48	.	.	PUNCT
aiti-13523	346	1	43	43	NUM
aiti-13523	346	2	-	-	SYM
aiti-13523	346	3	52	52	NUM
aiti-13523	346	4	,	,	PUNCT
aiti-13523	346	5	december	december	PROPN
aiti-13523	346	6	2010	2010	NUM
aiti-13523	346	7	.	.	PUNCT
aiti-13523	347	1	[	[	X
aiti-13523	347	2	25	25	NUM
aiti-13523	347	3	]	]	X
aiti-13523	347	4	g.	g.	PROPN
aiti-13523	347	5	salton	salton	PROPN
aiti-13523	347	6	and	and	CCONJ
aiti-13523	347	7	m.	m.	PROPN
aiti-13523	347	8	j.	j.	PROPN
aiti-13523	347	9	mcgill	mcgill	PROPN
aiti-13523	347	10	,	,	PUNCT
aiti-13523	347	11	introduction	introduction	NOUN
aiti-13523	347	12	to	to	ADP
aiti-13523	347	13	modern	modern	ADJ
aiti-13523	347	14	information	information	NOUN
aiti-13523	347	15	retrieval	retrieval	NOUN
aiti-13523	347	16	,	,	PUNCT
aiti-13523	347	17	international	international	ADJ
aiti-13523	347	18	student	student	NOUN
aiti-13523	347	19	ed	ed	NOUN
aiti-13523	347	20	.	.	PROPN
aiti-13523	347	21	,	,	PUNCT
aiti-13523	347	22	auckland	auckland	PROPN
aiti-13523	347	23	:	:	PUNCT
aiti-13523	347	24	mcgraw	mcgraw	PROPN
aiti-13523	347	25	-	-	PUNCT
aiti-13523	347	26	hill	hill	NOUN
aiti-13523	347	27	international,1983	international,1983	NOUN
aiti-13523	347	28	.	.	PUNCT
aiti-13523	348	1	[	[	X
aiti-13523	348	2	26	26	NUM
aiti-13523	348	3	]	]	X
aiti-13523	348	4	y.	y.	PROPN
aiti-13523	348	5	r.	r.	PROPN
aiti-13523	348	6	chao	chao	PROPN
aiti-13523	348	7	and	and	CCONJ
aiti-13523	348	8	g.	g.	PROPN
aiti-13523	348	9	k.	k.	PROPN
aiti-13523	348	10	zipf	zipf	PROPN
aiti-13523	348	11	,	,	PUNCT
aiti-13523	348	12	“	"	PUNCT
aiti-13523	348	13	human	human	ADJ
aiti-13523	348	14	behavior	behavior	NOUN
aiti-13523	348	15	and	and	CCONJ
aiti-13523	348	16	the	the	DET
aiti-13523	348	17	principle	principle	NOUN
aiti-13523	348	18	of	of	ADP
aiti-13523	348	19	least	least	ADJ
aiti-13523	348	20	effort	effort	NOUN
aiti-13523	348	21	:	:	PUNCT
aiti-13523	348	22	an	an	DET
aiti-13523	348	23	introduction	introduction	NOUN
aiti-13523	348	24	to	to	ADP
aiti-13523	348	25	human	human	ADJ
aiti-13523	348	26	ecology	ecology	NOUN
aiti-13523	348	27	,	,	PUNCT
aiti-13523	348	28	”	"	PUNCT
aiti-13523	348	29	language	language	NOUN
aiti-13523	348	30	,	,	PUNCT
aiti-13523	348	31	vol	vol	NOUN
aiti-13523	348	32	.	.	PROPN
aiti-13523	349	1	26	26	NUM
aiti-13523	349	2	,	,	PUNCT
aiti-13523	349	3	no	no	INTJ
aiti-13523	349	4	.	.	NOUN
aiti-13523	349	5	3	3	NUM
aiti-13523	349	6	,	,	PUNCT
aiti-13523	349	7	pp	pp	ADJ
aiti-13523	349	8	.	.	PUNCT
aiti-13523	350	1	394	394	NUM
aiti-13523	350	2	-	-	SYM
aiti-13523	350	3	401	401	NUM
aiti-13523	350	4	,	,	PUNCT
aiti-13523	350	5	july	july	PROPN
aiti-13523	350	6	-	-	PUNCT
aiti-13523	350	7	september	september	PROPN
aiti-13523	350	8	1950	1950	NUM
aiti-13523	350	9	.	.	PUNCT
aiti-13523	351	1	[	[	X
aiti-13523	351	2	27	27	NUM
aiti-13523	351	3	]	]	PUNCT
aiti-13523	351	4	t.	t.	PROPN
aiti-13523	351	5	mikolov	mikolov	PROPN
aiti-13523	351	6	,	,	PUNCT
aiti-13523	351	7	k.	k.	PROPN
aiti-13523	351	8	chen	chen	PROPN
aiti-13523	351	9	,	,	PUNCT
aiti-13523	351	10	g.	g.	PROPN
aiti-13523	351	11	corrado	corrado	PROPN
aiti-13523	351	12	,	,	PUNCT
aiti-13523	351	13	and	and	CCONJ
aiti-13523	351	14	j.	j.	PROPN
aiti-13523	351	15	dean	dean	PROPN
aiti-13523	351	16	,	,	PUNCT
aiti-13523	351	17	“	"	PUNCT
aiti-13523	351	18	efficient	efficient	ADJ
aiti-13523	351	19	estimation	estimation	NOUN
aiti-13523	351	20	of	of	ADP
aiti-13523	351	21	word	word	NOUN
aiti-13523	351	22	representations	representation	NOUN
aiti-13523	351	23	in	in	ADP
aiti-13523	351	24	vector	vector	NOUN
aiti-13523	351	25	space	space	NOUN
aiti-13523	351	26	,	,	PUNCT
aiti-13523	351	27	”	"	PUNCT
aiti-13523	351	28	https://arxiv.org/pdf/1301.3781.pdf	https://arxiv.org/pdf/1301.3781.pdf	PROPN
aiti-13523	351	29	,	,	PUNCT
aiti-13523	351	30	january	january	PROPN
aiti-13523	351	31	16	16	NUM
aiti-13523	351	32	,	,	PUNCT
aiti-13523	351	33	2013	2013	NUM
aiti-13523	351	34	.	.	PUNCT
aiti-13523	352	1	[	[	X
aiti-13523	352	2	28	28	NUM
aiti-13523	352	3	]	]	X
aiti-13523	352	4	c.	c.	PROPN
aiti-13523	352	5	y.	y.	PROPN
aiti-13523	352	6	j.	j.	PROPN
aiti-13523	352	7	peng	peng	PROPN
aiti-13523	352	8	,	,	PUNCT
aiti-13523	352	9	k.	k.	PROPN
aiti-13523	352	10	l.	l.	PROPN
aiti-13523	352	11	lee	lee	PROPN
aiti-13523	352	12	,	,	PUNCT
aiti-13523	352	13	and	and	CCONJ
aiti-13523	352	14	g.	g.	PROPN
aiti-13523	352	15	m.	m.	PROPN
aiti-13523	352	16	ingersoll	ingersoll	PROPN
aiti-13523	352	17	,	,	PUNCT
aiti-13523	352	18	“	"	PUNCT
aiti-13523	352	19	an	an	DET
aiti-13523	352	20	introduction	introduction	NOUN
aiti-13523	352	21	to	to	ADP
aiti-13523	352	22	logistic	logistic	ADJ
aiti-13523	352	23	regression	regression	NOUN
aiti-13523	352	24	analysis	analysis	NOUN
aiti-13523	352	25	and	and	CCONJ
aiti-13523	352	26	reporting	reporting	NOUN
aiti-13523	352	27	,	,	PUNCT
aiti-13523	352	28	”	"	PUNCT
aiti-13523	352	29	the	the	DET
aiti-13523	352	30	journal	journal	NOUN
aiti-13523	352	31	of	of	ADP
aiti-13523	352	32	educational	educational	ADJ
aiti-13523	352	33	research	research	NOUN
aiti-13523	352	34	,	,	PUNCT
aiti-13523	352	35	vol	vol	NOUN
aiti-13523	352	36	.	.	PROPN
aiti-13523	352	37	96	96	NUM
aiti-13523	352	38	,	,	PUNCT
aiti-13523	352	39	no	no	INTJ
aiti-13523	352	40	.	.	NOUN
aiti-13523	352	41	1	1	NUM
aiti-13523	352	42	,	,	PUNCT
aiti-13523	352	43	pp	pp	ADJ
aiti-13523	352	44	.	.	PUNCT
aiti-13523	353	1	3	3	NUM
aiti-13523	353	2	-	-	SYM
aiti-13523	353	3	14	14	NUM
aiti-13523	353	4	,	,	PUNCT
aiti-13523	353	5	2002	2002	NUM
aiti-13523	353	6	.	.	PUNCT
aiti-13523	354	1	[	[	X
aiti-13523	354	2	29	29	NUM
aiti-13523	354	3	]	]	X
aiti-13523	354	4	c.	c.	NOUN
aiti-13523	354	5	sammut	sammut	NOUN
aiti-13523	354	6	and	and	CCONJ
aiti-13523	354	7	g.	g.	PROPN
aiti-13523	354	8	webb	webb	PROPN
aiti-13523	354	9	,	,	PUNCT
aiti-13523	354	10	encyclopedia	encyclopedia	NOUN
aiti-13523	354	11	of	of	ADP
aiti-13523	354	12	machine	machine	NOUN
aiti-13523	354	13	learning	learning	NOUN
aiti-13523	354	14	and	and	CCONJ
aiti-13523	354	15	data	datum	NOUN
aiti-13523	354	16	mining	mining	NOUN
aiti-13523	354	17	,	,	PUNCT
aiti-13523	354	18	living	live	VERB
aiti-13523	354	19	ed	ed	NOUN
aiti-13523	354	20	.	.	PUNCT
aiti-13523	354	21	boston	boston	PROPN
aiti-13523	354	22	:	:	PUNCT
aiti-13523	354	23	springer	springer	NOUN
aiti-13523	354	24	,	,	PUNCT
aiti-13523	354	25	2016	2016	NUM
aiti-13523	354	26	.	.	PUNCT
aiti-13523	355	1	[	[	X
aiti-13523	355	2	30	30	NUM
aiti-13523	355	3	]	]	X
aiti-13523	355	4	g.	g.	PROPN
aiti-13523	355	5	ke	ke	PROPN
aiti-13523	355	6	,	,	PUNCT
aiti-13523	355	7	q.	q.	PROPN
aiti-13523	355	8	meng	meng	PROPN
aiti-13523	355	9	,	,	PUNCT
aiti-13523	355	10	t.	t.	PROPN
aiti-13523	355	11	finley	finley	PROPN
aiti-13523	355	12	,	,	PUNCT
aiti-13523	355	13	t.	t.	PROPN
aiti-13523	355	14	wang	wang	PROPN
aiti-13523	355	15	,	,	PUNCT
aiti-13523	355	16	w.	w.	PROPN
aiti-13523	355	17	chen	chen	PROPN
aiti-13523	355	18	,	,	PUNCT
aiti-13523	355	19	w.	w.	PROPN
aiti-13523	355	20	ma	ma	PROPN
aiti-13523	355	21	,	,	PUNCT
aiti-13523	355	22	et	et	PROPN
aiti-13523	355	23	al	al	PROPN
aiti-13523	355	24	.	.	PROPN
aiti-13523	355	25	,	,	PUNCT
aiti-13523	355	26	“	"	PUNCT
aiti-13523	355	27	lightgbm	lightgbm	ADJ
aiti-13523	355	28	:	:	PUNCT
aiti-13523	355	29	a	a	DET
aiti-13523	355	30	highly	highly	ADV
aiti-13523	355	31	efficient	efficient	ADJ
aiti-13523	355	32	gradient	gradient	NOUN
aiti-13523	355	33	boosting	boost	VERB
aiti-13523	355	34	decision	decision	NOUN
aiti-13523	355	35	tree	tree	NOUN
aiti-13523	355	36	,	,	PUNCT
aiti-13523	355	37	”	"	PUNCT
aiti-13523	355	38	advances	advance	NOUN
aiti-13523	355	39	in	in	ADP
aiti-13523	355	40	neural	neural	ADJ
aiti-13523	355	41	information	information	NOUN
aiti-13523	355	42	processing	processing	NOUN
aiti-13523	355	43	systems	system	NOUN
aiti-13523	355	44	30	30	NUM
aiti-13523	355	45	(	(	PUNCT
aiti-13523	355	46	nips	nip	NOUN
aiti-13523	355	47	2017	2017	NUM
aiti-13523	355	48	)	)	PUNCT
aiti-13523	355	49	,	,	PUNCT
aiti-13523	355	50	pp	pp	PROPN
aiti-13523	355	51	.	.	PUNCT
aiti-13523	356	1	1	1	NUM
aiti-13523	356	2	-	-	SYM
aiti-13523	356	3	9	9	NUM
aiti-13523	356	4	,	,	PUNCT
aiti-13523	356	5	december	december	PROPN
aiti-13523	356	6	2017	2017	NUM
aiti-13523	356	7	.	.	PUNCT
aiti-13523	357	1	copyright	copyright	NOUN
aiti-13523	357	2	©	©	PROPN
aiti-13523	357	3	by	by	ADP
aiti-13523	357	4	the	the	DET
aiti-13523	357	5	authors	author	NOUN
aiti-13523	357	6	.	.	PUNCT
aiti-13523	358	1	licensee	licensee	PROPN
aiti-13523	358	2	taeti	taeti	PROPN
aiti-13523	358	3	,	,	PUNCT
aiti-13523	358	4	taiwan	taiwan	PROPN
aiti-13523	358	5	.	.	PUNCT
aiti-13523	359	1	this	this	DET
aiti-13523	359	2	article	article	NOUN
aiti-13523	359	3	is	be	AUX
aiti-13523	359	4	an	an	DET
aiti-13523	359	5	open	open	ADJ
aiti-13523	359	6	-	-	PUNCT
aiti-13523	359	7	access	access	NOUN
aiti-13523	359	8	article	article	NOUN
aiti-13523	359	9	distributed	distribute	VERB
aiti-13523	359	10	under	under	ADP
aiti-13523	359	11	the	the	DET
aiti-13523	359	12	terms	term	NOUN
aiti-13523	359	13	and	and	CCONJ
aiti-13523	359	14	conditions	condition	NOUN
aiti-13523	359	15	of	of	ADP
aiti-13523	359	16	the	the	DET
aiti-13523	359	17	creative	creative	ADJ
aiti-13523	359	18	commons	common	NOUN
aiti-13523	359	19	attribution	attribution	NOUN
aiti-13523	359	20	(	(	PUNCT
aiti-13523	359	21	cc	cc	NOUN
aiti-13523	359	22	by	by	ADP
aiti-13523	359	23	-	-	PUNCT
aiti-13523	359	24	nc	nc	NOUN
aiti-13523	359	25	)	)	PUNCT
aiti-13523	359	26	license	license	NOUN
aiti-13523	359	27	(	(	PUNCT
aiti-13523	359	28	https://creativecommons.org/licenses/by-nc/4.0/	https://creativecommons.org/licenses/by-nc/4.0/	NOUN
aiti-13523	359	29	)	)	PUNCT
aiti-13523	359	30	.	.	PUNCT