id	sid	tid	token	lemma	pos
cana-3460	1	1	communications	communication	NOUN
cana-3460	1	2	on	on	ADP
cana-3460	1	3	applied	apply	VERB
cana-3460	1	4	nonlinear	nonlinear	ADJ
cana-3460	1	5	analysis	analysis	NOUN
cana-3460	1	6	issn	issn	NOUN
cana-3460	1	7	:	:	PUNCT
cana-3460	1	8	1074	1074	NUM
cana-3460	1	9	-	-	PUNCT
cana-3460	1	10	133x	133x	NUM
cana-3460	1	11	vol	vol	NOUN
cana-3460	1	12	32	32	NUM
cana-3460	1	13	no	no	NOUN
cana-3460	1	14	.	.	PUNCT
cana-3460	2	1	7s	7	NOUN
cana-3460	2	2	(	(	PUNCT
cana-3460	2	3	2025	2025	NUM
cana-3460	2	4	)	)	PUNCT
cana-3460	2	5	504	504	NUM
cana-3460	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3460	2	7	natural	natural	ADJ
cana-3460	2	8	language	language	NOUN
cana-3460	2	9	processing	processing	NOUN
cana-3460	2	10	techniques	technique	NOUN
cana-3460	2	11	for	for	ADP
cana-3460	2	12	sentiment	sentiment	NOUN
cana-3460	2	13	analysis	analysis	NOUN
cana-3460	2	14	in	in	ADP
cana-3460	2	15	social	social	ADJ
cana-3460	2	16	media	medium	NOUN
cana-3460	2	17	dr	dr	PROPN
cana-3460	2	18	.	.	PROPN
cana-3460	2	19	pramod	pramod	PROPN
cana-3460	2	20	kumar1	kumar1	PROPN
cana-3460	2	21	,	,	PUNCT
cana-3460	2	22	t.v	t.v	PROPN
cana-3460	2	23	.	.	PROPN
cana-3460	2	24	chandra	chandra	PROPN
cana-3460	2	25	sekhar2	sekhar2	PROPN
cana-3460	2	26	,	,	PUNCT
cana-3460	2	27	joyir	joyir	PROPN
cana-3460	2	28	siram	siram	PROPN
cana-3460	2	29	murtem3	murtem3	PROPN
cana-3460	2	30	,	,	PUNCT
cana-3460	2	31	t.vijayakumar4	t.vijayakumar4	PROPN
cana-3460	2	32	,	,	PUNCT
cana-3460	2	33	dr	dr	PROPN
cana-3460	2	34	kiran	kiran	PROPN
cana-3460	2	35	kumar	kumar	PROPN
cana-3460	2	36	reddy	reddy	PROPN
cana-3460	2	37	penubaka5	penubaka5	PROPN
cana-3460	2	38	,	,	PUNCT
cana-3460	2	39	sekhar	sekhar	PROPN
cana-3460	2	40	m6	m6	PROPN
cana-3460	2	41	1associate	1associate	NUM
cana-3460	2	42	professor	professor	NOUN
cana-3460	2	43	,	,	PUNCT
cana-3460	2	44	faculty	faculty	NOUN
cana-3460	2	45	of	of	ADP
cana-3460	2	46	commerce	commerce	NOUN
cana-3460	2	47	and	and	CCONJ
cana-3460	2	48	management	management	NOUN
cana-3460	2	49	,	,	PUNCT
cana-3460	2	50	assam	assam	PROPN
cana-3460	2	51	down	down	ADP
cana-3460	2	52	town	town	PROPN
cana-3460	2	53	university	university	PROPN
cana-3460	2	54	kamrup	kamrup	PROPN
cana-3460	2	55	metro	metro	PROPN
cana-3460	2	56	,	,	PUNCT
cana-3460	2	57	guwahati	guwahati	PROPN
cana-3460	2	58	,	,	PUNCT
cana-3460	2	59	assam.email	assam.email	PROPN
cana-3460	2	60	i	i	PROPN
cana-3460	2	61	d	d	PROPN
cana-3460	2	62	pramodtiwaripatna@gmail.com	pramodtiwaripatna@gmail.com	X
cana-3460	2	63	2asst.prof	2asst.prof	NUM
cana-3460	2	64	,	,	PUNCT
cana-3460	2	65	department	department	NOUN
cana-3460	2	66	of	of	ADP
cana-3460	2	67	ece	ece	PROPN
cana-3460	2	68	,	,	PUNCT
cana-3460	2	69	geethanjali	geethanjali	VERB
cana-3460	2	70	college	college	PROPN
cana-3460	2	71	of	of	ADP
cana-3460	2	72	engineering	engineering	NOUN
cana-3460	2	73	and	and	CCONJ
cana-3460	2	74	technology	technology	NOUN
cana-3460	2	75	,	,	PUNCT
cana-3460	2	76	cheeryal	cheeryal	ADJ
cana-3460	2	77	,	,	PUNCT
cana-3460	2	78	keesara	keesara	PROPN
cana-3460	2	79	,	,	PUNCT
cana-3460	2	80	hyderabad50130	hyderabad50130	PROPN
cana-3460	2	81	.	.	PUNCT
cana-3460	3	1	cell:9494612450	cell:9494612450	PROPN
cana-3460	3	2	.	.	PUNCT
cana-3460	3	3	email	email	NOUN
cana-3460	4	1	i	i	PROPN
cana-3460	4	2	d	d	PROPN
cana-3460	4	3	:	:	PUNCT
cana-3460	4	4	chandutadepalli@gmail.com	chandutadepalli@gmail.com	PROPN
cana-3460	5	1	3lecturer	3lecturer	NUM
cana-3460	5	2	,	,	PUNCT
cana-3460	5	3	cse	cse	PROPN
cana-3460	5	4	,	,	PUNCT
cana-3460	5	5	rajiv	rajiv	PROPN
cana-3460	5	6	gandhi	gandhi	PROPN
cana-3460	5	7	govt	govt	PROPN
cana-3460	5	8	college	college	PROPN
cana-3460	5	9	,	,	PUNCT
cana-3460	5	10	papumpare	papumpare	NOUN
cana-3460	5	11	,	,	PUNCT
cana-3460	5	12	itanagar	itanagar	PROPN
cana-3460	5	13	,	,	PUNCT
cana-3460	5	14	arunachal	arunachal	PROPN
cana-3460	5	15	pradesh	pradesh	PROPN
cana-3460	5	16	.	.	PUNCT
cana-3460	6	1	4assistant	4assistant	NUM
cana-3460	6	2	professor	professor	NOUN
cana-3460	6	3	,	,	PUNCT
cana-3460	6	4	artificial	artificial	ADJ
cana-3460	6	5	intelligence	intelligence	NOUN
cana-3460	6	6	and	and	CCONJ
cana-3460	6	7	machine	machine	NOUN
cana-3460	6	8	learning	learning	NOUN
cana-3460	6	9	,	,	PUNCT
cana-3460	6	10	dr.mahalingam	dr.mahalingam	ADJ
cana-3460	6	11	college	college	NOUN
cana-3460	6	12	of	of	ADP
cana-3460	6	13	engineering	engineering	NOUN
cana-3460	6	14	and	and	CCONJ
cana-3460	6	15	technology	technology	NOUN
cana-3460	6	16	,	,	PUNCT
cana-3460	6	17	coimbatore	coimbatore	PROPN
cana-3460	6	18	,	,	PUNCT
cana-3460	6	19	pollachi	pollachi	NOUN
cana-3460	6	20	,	,	PUNCT
cana-3460	6	21	tamilnadu	tamilnadu	NOUN
cana-3460	6	22	.	.	PUNCT
cana-3460	7	1	mail	mail	NOUN
cana-3460	8	1	i	i	PROPN
cana-3460	8	2	d	d	PROPN
cana-3460	8	3	:	:	PUNCT
cana-3460	8	4	tvijay787@gmail.com	tvijay787@gmail.com	X
cana-3460	9	1	5professor	5professor	NUM
cana-3460	9	2	,	,	PUNCT
cana-3460	9	3	aiml	aiml	NOUN
cana-3460	9	4	,	,	PUNCT
cana-3460	9	5	mlr	mlr	PROPN
cana-3460	9	6	institute	institute	PROPN
cana-3460	9	7	of	of	ADP
cana-3460	9	8	technology	technology	PROPN
cana-3460	9	9	,	,	PUNCT
cana-3460	9	10	medchal	medchal	ADJ
cana-3460	9	11	,	,	PUNCT
cana-3460	9	12	hyderabad	hyderabad	PROPN
cana-3460	9	13	,	,	PUNCT
cana-3460	9	14	telangana	telangana	PROPN
cana-3460	9	15	.	.	PUNCT
cana-3460	10	1	email	email	NOUN
cana-3460	11	1	i	i	PROPN
cana-3460	11	2	d	d	PROPN
cana-3460	11	3	kiran.penubaka@gmail.com	kiran.penubaka@gmail.com	PROPN
cana-3460	11	4	6assistant	6assistant	NUM
cana-3460	11	5	professor	professor	NOUN
cana-3460	11	6	,	,	PUNCT
cana-3460	11	7	electronics	electronic	NOUN
cana-3460	11	8	and	and	CCONJ
cana-3460	11	9	communication	communication	NOUN
cana-3460	11	10	engineering	engineering	NOUN
cana-3460	11	11	,	,	PUNCT
cana-3460	11	12	vignan	vignan	NOUN
cana-3460	11	13	's	's	PART
cana-3460	11	14	foundation	foundation	NOUN
cana-3460	11	15	for	for	ADP
cana-3460	11	16	science	science	NOUN
cana-3460	11	17	,	,	PUNCT
cana-3460	11	18	technology	technology	NOUN
cana-3460	11	19	and	and	CCONJ
cana-3460	11	20	research	research	NOUN
cana-3460	11	21	,	,	PUNCT
cana-3460	11	22	guntur	guntur	PROPN
cana-3460	11	23	,	,	PUNCT
cana-3460	11	24	andhra	andhra	PROPN
cana-3460	11	25	pradesh	pradesh	PROPN
cana-3460	11	26	.	.	PUNCT
cana-3460	12	1	email	email	NOUN
cana-3460	12	2	i	i	PROPN
cana-3460	12	3	d	d	PROPN
cana-3460	12	4	-sekhar.snha@gmail.com	-sekhar.snha@gmail.com	PROPN
cana-3460	12	5	article	article	NOUN
cana-3460	12	6	history	history	NOUN
cana-3460	12	7	:	:	PUNCT
cana-3460	12	8	received	receive	VERB
cana-3460	12	9	:	:	PUNCT
cana-3460	12	10	26	26	NUM
cana-3460	12	11	-	-	SYM
cana-3460	12	12	10	10	NUM
cana-3460	12	13	-	-	PUNCT
cana-3460	12	14	2024	2024	NUM
cana-3460	12	15	revised:10	revised:10	NOUN
cana-3460	12	16	-	-	PUNCT
cana-3460	12	17	11	11	NUM
cana-3460	12	18	-	-	PUNCT
cana-3460	12	19	2024	2024	NUM
cana-3460	12	20	accepted:18	accepted:18	PROPN
cana-3460	12	21	-	-	PUNCT
cana-3460	12	22	12	12	NUM
cana-3460	12	23	-	-	PUNCT
cana-3460	12	24	2024	2024	NUM
cana-3460	12	25	abstract	abstract	NOUN
cana-3460	12	26	:	:	PUNCT
cana-3460	12	27	this	this	DET
cana-3460	12	28	research	research	NOUN
cana-3460	12	29	has	have	AUX
cana-3460	12	30	used	use	VERB
cana-3460	12	31	the	the	DET
cana-3460	12	32	techniques	technique	NOUN
cana-3460	12	33	of	of	ADP
cana-3460	12	34	natural	natural	ADJ
cana-3460	12	35	language	language	NOUN
cana-3460	12	36	processing	processing	NOUN
cana-3460	12	37	to	to	PART
cana-3460	12	38	explore	explore	VERB
cana-3460	12	39	how	how	SCONJ
cana-3460	12	40	to	to	PART
cana-3460	12	41	do	do	VERB
cana-3460	12	42	sentiment	sentiment	NOUN
cana-3460	12	43	analysis	analysis	NOUN
cana-3460	12	44	on	on	ADP
cana-3460	12	45	social	social	ADJ
cana-3460	12	46	media	medium	NOUN
cana-3460	12	47	by	by	ADP
cana-3460	12	48	using	use	VERB
cana-3460	12	49	three	three	NUM
cana-3460	12	50	algorithms	algorithm	NOUN
cana-3460	12	51	,	,	PUNCT
cana-3460	12	52	g	g	NOUN
cana-3460	12	53	-	-	PUNCT
cana-3460	12	54	lstm	lstm	ADJ
cana-3460	12	55	,	,	PUNCT
cana-3460	12	56	rmdeasd	rmdeasd	NOUN
cana-3460	12	57	,	,	PUNCT
cana-3460	12	58	and	and	CCONJ
cana-3460	12	59	bert	bert	NOUN
cana-3460	12	60	.	.	PUNCT
cana-3460	13	1	it	it	PRON
cana-3460	13	2	tested	test	VERB
cana-3460	13	3	how	how	SCONJ
cana-3460	13	4	the	the	DET
cana-3460	13	5	models	model	NOUN
cana-3460	13	6	perform	perform	VERB
cana-3460	13	7	on	on	ADP
cana-3460	13	8	a	a	DET
cana-3460	13	9	different	different	ADJ
cana-3460	13	10	set	set	NOUN
cana-3460	13	11	of	of	ADP
cana-3460	13	12	domains	domain	NOUN
cana-3460	13	13	like	like	ADP
cana-3460	13	14	disaster	disaster	NOUN
cana-3460	13	15	management	management	NOUN
cana-3460	13	16	,	,	PUNCT
cana-3460	13	17	corporate	corporate	ADJ
cana-3460	13	18	performance	performance	NOUN
cana-3460	13	19	,	,	PUNCT
cana-3460	13	20	and	and	CCONJ
cana-3460	13	21	consumer	consumer	NOUN
cana-3460	13	22	behavior	behavior	NOUN
cana-3460	13	23	for	for	ADP
cana-3460	13	24	the	the	DET
cana-3460	13	25	purpose	purpose	NOUN
cana-3460	13	26	of	of	ADP
cana-3460	13	27	sentiment	sentiment	NOUN
cana-3460	13	28	classification	classification	NOUN
cana-3460	13	29	.	.	PUNCT
cana-3460	14	1	the	the	DET
cana-3460	14	2	study	study	NOUN
cana-3460	14	3	utilized	utilize	VERB
cana-3460	14	4	more	more	ADJ
cana-3460	14	5	than	than	ADP
cana-3460	14	6	500,000	500,000	NUM
cana-3460	14	7	social	social	ADJ
cana-3460	14	8	media	medium	NOUN
cana-3460	14	9	posts	post	NOUN
cana-3460	14	10	as	as	ADP
cana-3460	14	11	the	the	DET
cana-3460	14	12	dataset	dataset	NOUN
cana-3460	14	13	,	,	PUNCT
cana-3460	14	14	with	with	ADP
cana-3460	14	15	accuracy	accuracy	NOUN
cana-3460	14	16	rates	rate	NOUN
cana-3460	14	17	of	of	ADP
cana-3460	14	18	88.4	88.4	NUM
cana-3460	14	19	%	%	NOUN
cana-3460	14	20	for	for	ADP
cana-3460	14	21	g	g	NOUN
cana-3460	14	22	-	-	PUNCT
cana-3460	14	23	lstm	lstm	ADJ
cana-3460	14	24	,	,	PUNCT
cana-3460	14	25	85.7	85.7	NUM
cana-3460	14	26	%	%	NOUN
cana-3460	14	27	for	for	ADP
cana-3460	14	28	rmdeasd	rmdeasd	NOUN
cana-3460	14	29	,	,	PUNCT
cana-3460	14	30	and	and	CCONJ
cana-3460	14	31	91.2	91.2	NUM
cana-3460	14	32	%	%	NOUN
cana-3460	14	33	for	for	ADP
cana-3460	14	34	bert	bert	PROPN
cana-3460	14	35	.	.	PUNCT
cana-3460	15	1	results	result	NOUN
cana-3460	15	2	reveal	reveal	VERB
cana-3460	15	3	that	that	SCONJ
cana-3460	15	4	bert	bert	PROPN
cana-3460	15	5	surpassed	surpass	VERB
cana-3460	15	6	the	the	DET
cana-3460	15	7	other	other	ADJ
cana-3460	15	8	models	model	NOUN
cana-3460	15	9	in	in	ADP
cana-3460	15	10	terms	term	NOUN
cana-3460	15	11	of	of	ADP
cana-3460	15	12	accuracy	accuracy	NOUN
cana-3460	15	13	and	and	CCONJ
cana-3460	15	14	contextual	contextual	ADJ
cana-3460	15	15	understanding	understanding	NOUN
cana-3460	15	16	in	in	ADP
cana-3460	15	17	aspect	aspect	NOUN
cana-3460	15	18	-	-	PUNCT
cana-3460	15	19	based	base	VERB
cana-3460	15	20	sentiment	sentiment	NOUN
cana-3460	15	21	analysis	analysis	NOUN
cana-3460	15	22	.	.	PUNCT
cana-3460	16	1	moreover	moreover	ADV
cana-3460	16	2	,	,	PUNCT
cana-3460	16	3	the	the	DET
cana-3460	16	4	hybrid	hybrid	ADJ
cana-3460	16	5	model	model	NOUN
cana-3460	16	6	g	g	NOUN
cana-3460	16	7	-	-	PUNCT
cana-3460	16	8	lstm	lstm	NOUN
cana-3460	16	9	was	be	AUX
cana-3460	16	10	effective	effective	ADJ
cana-3460	16	11	in	in	ADP
cana-3460	16	12	disaster	disaster	NOUN
cana-3460	16	13	-	-	PUNCT
cana-3460	16	14	related	relate	VERB
cana-3460	16	15	tweets	tweet	NOUN
cana-3460	16	16	by	by	ADP
cana-3460	16	17	achieving	achieve	VERB
cana-3460	16	18	a	a	DET
cana-3460	16	19	92.3	92.3	NUM
cana-3460	16	20	%	%	NOUN
cana-3460	16	21	accuracy	accuracy	NOUN
cana-3460	16	22	in	in	ADP
cana-3460	16	23	real	real	ADJ
cana-3460	16	24	-	-	PUNCT
cana-3460	16	25	time	time	NOUN
cana-3460	16	26	sentiment	sentiment	NOUN
cana-3460	16	27	classification	classification	NOUN
cana-3460	16	28	.	.	PUNCT
cana-3460	17	1	comparisons	comparison	NOUN
cana-3460	17	2	with	with	ADP
cana-3460	17	3	related	related	ADJ
cana-3460	17	4	work	work	NOUN
cana-3460	17	5	show	show	VERB
cana-3460	17	6	that	that	SCONJ
cana-3460	17	7	the	the	DET
cana-3460	17	8	proposed	propose	VERB
cana-3460	17	9	models	model	NOUN
cana-3460	17	10	significantly	significantly	ADV
cana-3460	17	11	improve	improve	VERB
cana-3460	17	12	the	the	DET
cana-3460	17	13	accuracy	accuracy	NOUN
cana-3460	17	14	and	and	CCONJ
cana-3460	17	15	robustness	robustness	NOUN
cana-3460	17	16	of	of	ADP
cana-3460	17	17	sentiment	sentiment	NOUN
cana-3460	17	18	analysis	analysis	NOUN
cana-3460	17	19	over	over	ADP
cana-3460	17	20	traditional	traditional	ADJ
cana-3460	17	21	machine	machine	NOUN
cana-3460	17	22	learning	learning	NOUN
cana-3460	17	23	methods	method	NOUN
cana-3460	17	24	.	.	PUNCT
cana-3460	18	1	challenges	challenge	NOUN
cana-3460	18	2	such	such	ADJ
cana-3460	18	3	as	as	ADP
cana-3460	18	4	sentiment	sentiment	NOUN
cana-3460	18	5	classification	classification	NOUN
cana-3460	18	6	in	in	ADP
cana-3460	18	7	low	low	ADJ
cana-3460	18	8	-	-	PUNCT
cana-3460	18	9	resource	resource	NOUN
cana-3460	18	10	languages	language	NOUN
cana-3460	18	11	are	be	AUX
cana-3460	18	12	also	also	ADV
cana-3460	18	13	addressed	address	VERB
cana-3460	18	14	,	,	PUNCT
cana-3460	18	15	providing	provide	VERB
cana-3460	18	16	insights	insight	NOUN
cana-3460	18	17	on	on	ADP
cana-3460	18	18	how	how	SCONJ
cana-3460	18	19	to	to	PART
cana-3460	18	20	improve	improve	VERB
cana-3460	18	21	model	model	NOUN
cana-3460	18	22	applicability	applicability	NOUN
cana-3460	18	23	in	in	ADP
cana-3460	18	24	diverse	diverse	ADJ
cana-3460	18	25	linguistic	linguistic	ADJ
cana-3460	18	26	contexts	contexts	NOUN
cana-3460	18	27	.	.	PUNCT
cana-3460	19	1	the	the	DET
cana-3460	19	2	findings	finding	NOUN
cana-3460	19	3	add	add	VERB
cana-3460	19	4	to	to	ADP
cana-3460	19	5	the	the	DET
cana-3460	19	6	increasing	increase	VERB
cana-3460	19	7	body	body	NOUN
cana-3460	19	8	of	of	ADP
cana-3460	19	9	research	research	NOUN
cana-3460	19	10	in	in	ADP
cana-3460	19	11	sentiment	sentiment	NOUN
cana-3460	19	12	analysis	analysis	NOUN
cana-3460	19	13	and	and	CCONJ
cana-3460	19	14	indicate	indicate	VERB
cana-3460	19	15	its	its	PRON
cana-3460	19	16	potential	potential	ADJ
cana-3460	19	17	applications	application	NOUN
cana-3460	19	18	in	in	ADP
cana-3460	19	19	several	several	ADJ
cana-3460	19	20	industries	industry	NOUN
cana-3460	19	21	,	,	PUNCT
cana-3460	19	22	such	such	ADJ
cana-3460	19	23	as	as	ADP
cana-3460	19	24	healthcare	healthcare	NOUN
cana-3460	19	25	,	,	PUNCT
cana-3460	19	26	marketing	marketing	NOUN
cana-3460	19	27	,	,	PUNCT
cana-3460	19	28	and	and	CCONJ
cana-3460	19	29	public	public	ADJ
cana-3460	19	30	opinion	opinion	NOUN
cana-3460	19	31	analysis	analysis	NOUN
cana-3460	19	32	.	.	PUNCT
cana-3460	20	1	keywords	keyword	NOUN
cana-3460	20	2	:	:	PUNCT
cana-3460	20	3	sentiment	sentiment	NOUN
cana-3460	20	4	analysis	analysis	NOUN
cana-3460	20	5	,	,	PUNCT
cana-3460	20	6	natural	natural	ADJ
cana-3460	20	7	language	language	NOUN
cana-3460	20	8	processing	processing	NOUN
cana-3460	20	9	,	,	PUNCT
cana-3460	20	10	g	g	NOUN
cana-3460	20	11	-	-	PUNCT
cana-3460	20	12	lstm	lstm	ADJ
cana-3460	20	13	,	,	PUNCT
cana-3460	20	14	rmdeasd	rmdeasd	NOUN
cana-3460	20	15	,	,	PUNCT
cana-3460	20	16	bert	bert	PROPN
cana-3460	20	17	.	.	PUNCT
cana-3460	21	1	i.	i.	PROPN
cana-3460	21	2	introduction	introduction	NOUN
cana-3460	21	3	rising	rise	VERB
cana-3460	21	4	as	as	SCONJ
cana-3460	21	5	social	social	ADJ
cana-3460	21	6	media	medium	NOUN
cana-3460	21	7	platforms	platform	NOUN
cana-3460	21	8	change	change	VERB
cana-3460	21	9	individuals	individual	NOUN
cana-3460	21	10	'	'	PART
cana-3460	21	11	communication	communication	NOUN
cana-3460	21	12	,	,	PUNCT
cana-3460	21	13	opinions	opinion	NOUN
cana-3460	21	14	'	'	PART
cana-3460	21	15	spreading	spread	VERB
cana-3460	21	16	,	,	PUNCT
cana-3460	21	17	and	and	CCONJ
cana-3460	21	18	emotions	emotion	NOUN
cana-3460	21	19	.	.	PUNCT
cana-3460	22	1	trillions	trillion	NOUN
cana-3460	22	2	of	of	ADP
cana-3460	22	3	active	active	ADJ
cana-3460	22	4	users	user	NOUN
cana-3460	22	5	will	will	AUX
cana-3460	22	6	generate	generate	VERB
cana-3460	22	7	massive	massive	ADJ
cana-3460	22	8	amounts	amount	NOUN
cana-3460	22	9	of	of	ADP
cana-3460	22	10	information	information	NOUN
cana-3460	22	11	and	and	CCONJ
cana-3460	22	12	data	datum	NOUN
cana-3460	22	13	every	every	DET
cana-3460	22	14	day	day	NOUN
cana-3460	22	15	,	,	PUNCT
cana-3460	22	16	necessitating	necessitate	VERB
cana-3460	22	17	the	the	DET
cana-3460	22	18	understanding	understanding	NOUN
cana-3460	22	19	of	of	ADP
cana-3460	22	20	emotions	emotion	NOUN
cana-3460	22	21	within	within	ADP
cana-3460	22	22	social	social	ADJ
cana-3460	22	23	media	medium	NOUN
cana-3460	22	24	content	content	NOUN
cana-3460	22	25	;	;	PUNCT
cana-3460	22	26	this	this	PRON
cana-3460	22	27	is	be	AUX
cana-3460	22	28	important	important	ADJ
cana-3460	22	29	to	to	ADP
cana-3460	22	30	all	all	DET
cana-3460	22	31	businesses	business	NOUN
cana-3460	22	32	,	,	PUNCT
cana-3460	22	33	governments	government	NOUN
cana-3460	22	34	,	,	PUNCT
cana-3460	22	35	or	or	CCONJ
cana-3460	22	36	researchers	researcher	NOUN
cana-3460	22	37	.	.	PUNCT
cana-3460	23	1	sentiment	sentiment	NOUN
cana-3460	23	2	analysis	analysis	NOUN
cana-3460	23	3	-	-	PUNCT
cana-3460	23	4	also	also	ADV
cana-3460	23	5	known	know	VERB
cana-3460	23	6	as	as	ADP
cana-3460	23	7	opinion	opinion	NOUN
cana-3460	23	8	mining	mining	NOUN
cana-3460	23	9	-	-	PUNCT
cana-3460	23	10	concerns	concern	NOUN
cana-3460	23	11	the	the	DET
cana-3460	23	12	process	process	NOUN
cana-3460	23	13	applied	apply	VERB
cana-3460	23	14	based	base	VERB
cana-3460	23	15	on	on	ADP
cana-3460	23	16	nlp	nlp	ADJ
cana-3460	23	17	techniques	technique	NOUN
cana-3460	23	18	that	that	PRON
cana-3460	23	19	involve	involve	VERB
cana-3460	23	20	discernment	discernment	NOUN
cana-3460	23	21	of	of	ADP
cana-3460	23	22	the	the	DET
cana-3460	23	23	sentiment	sentiment	NOUN
cana-3460	23	24	carried	carry	VERB
cana-3460	23	25	or	or	CCONJ
cana-3460	23	26	mailto:pramodtiwaripatna@gmail.com	mailto:pramodtiwaripatna@gmail.com	NOUN
cana-3460	23	27	mailto:tvijay787@gmail.com	mailto:tvijay787@gmail.com	PROPN
cana-3460	23	28	communications	communication	NOUN
cana-3460	23	29	on	on	ADP
cana-3460	23	30	applied	apply	VERB
cana-3460	23	31	nonlinear	nonlinear	ADJ
cana-3460	23	32	analysis	analysis	NOUN
cana-3460	23	33	issn	issn	NOUN
cana-3460	23	34	:	:	PUNCT
cana-3460	23	35	1074	1074	NUM
cana-3460	23	36	-	-	PUNCT
cana-3460	23	37	133x	133x	NUM
cana-3460	23	38	vol	vol	NOUN
cana-3460	23	39	32	32	NUM
cana-3460	23	40	no	no	NOUN
cana-3460	23	41	.	.	PUNCT
cana-3460	24	1	7s	7	NOUN
cana-3460	24	2	(	(	PUNCT
cana-3460	24	3	2025	2025	NUM
cana-3460	24	4	)	)	PUNCT
cana-3460	24	5	505	505	NUM
cana-3460	24	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-3460	24	7	expressed	express	VERB
cana-3460	24	8	in	in	ADP
cana-3460	24	9	text	text	NOUN
cana-3460	24	10	data	datum	NOUN
cana-3460	25	1	[	[	X
cana-3460	25	2	1	1	NUM
cana-3460	25	3	]	]	PUNCT
cana-3460	25	4	.	.	PUNCT
cana-3460	26	1	this	this	DET
cana-3460	26	2	study	study	NOUN
cana-3460	26	3	tries	try	VERB
cana-3460	26	4	to	to	PART
cana-3460	26	5	look	look	VERB
cana-3460	26	6	into	into	ADP
cana-3460	26	7	the	the	DET
cana-3460	26	8	potential	potential	ADJ
cana-3460	26	9	use	use	NOUN
cana-3460	26	10	of	of	ADP
cana-3460	26	11	nlp	nlp	ADJ
cana-3460	26	12	techniques	technique	NOUN
cana-3460	26	13	for	for	ADP
cana-3460	26	14	sentiment	sentiment	NOUN
cana-3460	26	15	analysis	analysis	NOUN
cana-3460	26	16	on	on	ADP
cana-3460	26	17	social	social	ADJ
cana-3460	26	18	media	medium	NOUN
cana-3460	26	19	.	.	PUNCT
cana-3460	27	1	social	social	ADJ
cana-3460	27	2	media	medium	NOUN
cana-3460	27	3	platforms	platform	NOUN
cana-3460	27	4	like	like	ADP
cana-3460	27	5	twitter	twitter	NOUN
cana-3460	27	6	,	,	PUNCT
cana-3460	27	7	facebook	facebook	PROPN
cana-3460	27	8	,	,	PUNCT
cana-3460	27	9	instagram	instagram	PROPN
cana-3460	27	10	,	,	PUNCT
cana-3460	27	11	and	and	CCONJ
cana-3460	27	12	reddit	reddit	NOUN
cana-3460	27	13	will	will	AUX
cana-3460	27	14	be	be	AUX
cana-3460	27	15	a	a	DET
cana-3460	27	16	goldmine	goldmine	NOUN
cana-3460	27	17	in	in	ADP
cana-3460	27	18	sourcing	source	VERB
cana-3460	27	19	real	real	ADJ
cana-3460	27	20	-	-	PUNCT
cana-3460	27	21	time	time	NOUN
cana-3460	27	22	information	information	NOUN
cana-3460	27	23	about	about	ADP
cana-3460	27	24	people	people	NOUN
cana-3460	27	25	's	's	PART
cana-3460	27	26	opinions	opinion	NOUN
cana-3460	27	27	,	,	PUNCT
cana-3460	27	28	consumer	consumer	NOUN
cana-3460	27	29	responses	response	NOUN
cana-3460	27	30	,	,	PUNCT
cana-3460	27	31	and	and	CCONJ
cana-3460	27	32	societal	societal	ADJ
cana-3460	27	33	trends	trend	NOUN
cana-3460	27	34	.	.	PUNCT
cana-3460	28	1	there	there	PRON
cana-3460	28	2	is	be	VERB
cana-3460	28	3	a	a	DET
cana-3460	28	4	possibility	possibility	NOUN
cana-3460	28	5	for	for	ADP
cana-3460	28	6	any	any	DET
cana-3460	28	7	underlying	underlying	ADJ
cana-3460	28	8	sentiment	sentiment	NOUN
cana-3460	28	9	,	,	PUNCT
cana-3460	28	10	whether	whether	SCONJ
cana-3460	28	11	it	it	PRON
cana-3460	28	12	's	be	AUX
cana-3460	28	13	positive	positive	ADJ
cana-3460	28	14	,	,	PUNCT
cana-3460	28	15	negative	negative	ADJ
cana-3460	28	16	,	,	PUNCT
cana-3460	28	17	or	or	CCONJ
cana-3460	28	18	even	even	ADV
cana-3460	28	19	neutral	neutral	ADJ
cana-3460	28	20	,	,	PUNCT
cana-3460	28	21	that	that	SCONJ
cana-3460	28	22	user	user	NOUN
cana-3460	28	23	-	-	PUNCT
cana-3460	28	24	generated	generate	VERB
cana-3460	28	25	content	content	NOUN
cana-3460	28	26	,	,	PUNCT
cana-3460	28	27	such	such	ADJ
cana-3460	28	28	as	as	ADP
cana-3460	28	29	those	those	PRON
cana-3460	28	30	in	in	ADP
cana-3460	28	31	the	the	DET
cana-3460	28	32	form	form	NOUN
cana-3460	28	33	of	of	ADP
cana-3460	28	34	tweets	tweet	NOUN
cana-3460	28	35	,	,	PUNCT
cana-3460	28	36	comments	comment	NOUN
cana-3460	28	37	,	,	PUNCT
cana-3460	28	38	and	and	CCONJ
cana-3460	28	39	posts	post	NOUN
cana-3460	28	40	may	may	AUX
cana-3460	28	41	bring	bring	VERB
cana-3460	28	42	to	to	ADP
cana-3460	28	43	light	light	NOUN
cana-3460	28	44	[	[	X
cana-3460	28	45	2	2	NUM
cana-3460	28	46	]	]	PUNCT
cana-3460	28	47	.	.	PUNCT
cana-3460	29	1	businesses	business	NOUN
cana-3460	29	2	rely	rely	VERB
cana-3460	29	3	on	on	ADP
cana-3460	29	4	these	these	DET
cana-3460	29	5	insights	insight	NOUN
cana-3460	29	6	considerably	considerably	ADV
cana-3460	29	7	concerning	concern	VERB
cana-3460	29	8	brand	brand	NOUN
cana-3460	29	9	reputation	reputation	NOUN
cana-3460	29	10	management	management	NOUN
cana-3460	29	11	,	,	PUNCT
cana-3460	29	12	research	research	NOUN
cana-3460	29	13	work	work	NOUN
cana-3460	29	14	,	,	PUNCT
cana-3460	29	15	and	and	CCONJ
cana-3460	29	16	customer	customer	NOUN
cana-3460	29	17	feedback	feedback	NOUN
cana-3460	29	18	analyses	analysis	NOUN
cana-3460	29	19	.	.	PUNCT
cana-3460	30	1	this	this	PRON
cana-3460	30	2	also	also	ADV
cana-3460	30	3	helps	help	VERB
cana-3460	30	4	in	in	ADP
cana-3460	30	5	understanding	understand	VERB
cana-3460	30	6	sentiment	sentiment	NOUN
cana-3460	30	7	in	in	ADP
cana-3460	30	8	political	political	ADJ
cana-3460	30	9	discourse	discourse	NOUN
cana-3460	30	10	,	,	PUNCT
cana-3460	30	11	social	social	ADJ
cana-3460	30	12	movements	movement	NOUN
cana-3460	30	13	,	,	PUNCT
cana-3460	30	14	and	and	CCONJ
cana-3460	30	15	mental	mental	ADJ
cana-3460	30	16	health	health	NOUN
cana-3460	30	17	trends	trend	NOUN
cana-3460	30	18	.	.	PUNCT
cana-3460	31	1	traditional	traditional	ADJ
cana-3460	31	2	methods	method	NOUN
cana-3460	31	3	of	of	ADP
cana-3460	31	4	sentiment	sentiment	NOUN
cana-3460	31	5	analysis	analysis	NOUN
cana-3460	31	6	use	use	NOUN
cana-3460	31	7	lexicons	lexicon	NOUN
cana-3460	31	8	,	,	PUNCT
cana-3460	31	9	rule	rule	NOUN
cana-3460	31	10	-	-	PUNCT
cana-3460	31	11	based	base	VERB
cana-3460	31	12	systems	system	NOUN
cana-3460	31	13	,	,	PUNCT
cana-3460	31	14	and	and	CCONJ
cana-3460	31	15	machine	machine	NOUN
cana-3460	31	16	learning	learn	VERB
cana-3460	31	17	algorithms	algorithm	NOUN
cana-3460	31	18	[	[	X
cana-3460	31	19	3	3	NUM
cana-3460	31	20	]	]	PUNCT
cana-3460	31	21	.	.	PUNCT
cana-3460	32	1	however	however	ADV
cana-3460	32	2	,	,	PUNCT
cana-3460	32	3	the	the	DET
cana-3460	32	4	latest	late	ADJ
cana-3460	32	5	breakthroughs	breakthrough	NOUN
cana-3460	32	6	in	in	ADP
cana-3460	32	7	nlp	nlp	NOUN
cana-3460	32	8	are	be	AUX
cana-3460	32	9	yielding	yield	VERB
cana-3460	32	10	more	more	ADV
cana-3460	32	11	advanced	advanced	ADJ
cana-3460	32	12	approaches	approach	NOUN
cana-3460	32	13	than	than	ADP
cana-3460	32	14	just	just	ADV
cana-3460	32	15	deep	deep	ADJ
cana-3460	32	16	learning	learning	NOUN
cana-3460	32	17	models	model	NOUN
cana-3460	32	18	.	.	PUNCT
cana-3460	33	1	for	for	ADP
cana-3460	33	2	instance	instance	NOUN
cana-3460	33	3	,	,	PUNCT
cana-3460	33	4	such	such	ADJ
cana-3460	33	5	models	model	NOUN
cana-3460	33	6	that	that	PRON
cana-3460	33	7	have	have	AUX
cana-3460	33	8	captured	capture	VERB
cana-3460	33	9	contextual	contextual	ADJ
cana-3460	33	10	nuances	nuance	NOUN
cana-3460	33	11	and	and	CCONJ
cana-3460	33	12	processed	process	VERB
cana-3460	33	13	ambiguous	ambiguous	ADJ
cana-3460	33	14	language	language	NOUN
cana-3460	33	15	can	can	AUX
cana-3460	33	16	be	be	AUX
cana-3460	33	17	deployed	deploy	VERB
cana-3460	33	18	to	to	PART
cana-3460	33	19	improve	improve	VERB
cana-3460	33	20	the	the	DET
cana-3460	33	21	accuracy	accuracy	NOUN
cana-3460	33	22	and	and	CCONJ
cana-3460	33	23	efficiency	efficiency	NOUN
cana-3460	33	24	of	of	ADP
cana-3460	33	25	sentiment	sentiment	NOUN
cana-3460	33	26	classification	classification	NOUN
cana-3460	33	27	.	.	PUNCT
cana-3460	34	1	indeed	indeed	ADV
cana-3460	34	2	,	,	PUNCT
cana-3460	34	3	newer	new	ADJ
cana-3460	34	4	techniques	technique	NOUN
cana-3460	34	5	such	such	ADJ
cana-3460	34	6	as	as	ADP
cana-3460	34	7	transformer	transformer	NOUN
cana-3460	34	8	-	-	PUNCT
cana-3460	34	9	based	base	VERB
cana-3460	34	10	models	model	NOUN
cana-3460	34	11	like	like	ADP
cana-3460	34	12	bert	bert	PROPN
cana-3460	34	13	have	have	AUX
cana-3460	34	14	revolutionized	revolutionize	VERB
cana-3460	34	15	the	the	DET
cana-3460	34	16	state	state	NOUN
cana-3460	34	17	-	-	PUNCT
cana-3460	34	18	of	of	ADP
cana-3460	34	19	-	-	PUNCT
cana-3460	34	20	theart	theart	NOUN
cana-3460	34	21	for	for	ADP
cana-3460	34	22	accuracy	accuracy	NOUN
cana-3460	34	23	and	and	CCONJ
cana-3460	34	24	efficiency	efficiency	NOUN
cana-3460	34	25	in	in	ADP
cana-3460	34	26	sentiment	sentiment	NOUN
cana-3460	34	27	classification	classification	NOUN
cana-3460	34	28	.	.	PUNCT
cana-3460	35	1	this	this	DET
cana-3460	35	2	study	study	NOUN
cana-3460	35	3	will	will	AUX
cana-3460	35	4	review	review	VERB
cana-3460	35	5	the	the	DET
cana-3460	35	6	various	various	ADJ
cana-3460	35	7	techniques	technique	NOUN
cana-3460	35	8	that	that	PRON
cana-3460	35	9	nlp	nlp	NOUN
cana-3460	35	10	applies	apply	VERB
cana-3460	35	11	to	to	ADP
cana-3460	35	12	sentiment	sentiment	NOUN
cana-3460	35	13	analysis	analysis	NOUN
cana-3460	35	14	,	,	PUNCT
cana-3460	35	15	from	from	ADP
cana-3460	35	16	tokenization	tokenization	NOUN
cana-3460	35	17	to	to	ADP
cana-3460	35	18	part	part	NOUN
cana-3460	35	19	-	-	PUNCT
cana-3460	35	20	of	of	ADP
cana-3460	35	21	-	-	PUNCT
cana-3460	35	22	speech	speech	NOUN
cana-3460	35	23	tagging	tagging	NOUN
cana-3460	35	24	,	,	PUNCT
cana-3460	35	25	sentiment	sentiment	NOUN
cana-3460	35	26	lexicons	lexicon	NOUN
cana-3460	35	27	,	,	PUNCT
cana-3460	35	28	and	and	CCONJ
cana-3460	35	29	machine	machine	NOUN
cana-3460	35	30	learning	learning	NOUN
cana-3460	35	31	algorithms	algorithm	NOUN
cana-3460	35	32	,	,	PUNCT
cana-3460	35	33	particularly	particularly	ADV
cana-3460	35	34	deep	deep	ADJ
cana-3460	35	35	learning	learning	NOUN
cana-3460	35	36	approaches	approach	NOUN
cana-3460	35	37	.	.	PUNCT
cana-3460	36	1	by	by	ADP
cana-3460	36	2	studying	study	VERB
cana-3460	36	3	this	this	DET
cana-3460	36	4	area	area	NOUN
cana-3460	36	5	,	,	PUNCT
cana-3460	36	6	the	the	DET
cana-3460	36	7	effectiveness	effectiveness	NOUN
cana-3460	36	8	of	of	ADP
cana-3460	36	9	implementing	implement	VERB
cana-3460	36	10	sentiment	sentiment	NOUN
cana-3460	36	11	analysis	analysis	NOUN
cana-3460	36	12	in	in	ADP
cana-3460	36	13	such	such	DET
cana-3460	36	14	a	a	DET
cana-3460	36	15	dynamic	dynamic	ADJ
cana-3460	36	16	and	and	CCONJ
cana-3460	36	17	diverse	diverse	ADJ
cana-3460	36	18	field	field	NOUN
cana-3460	36	19	as	as	SCONJ
cana-3460	36	20	social	social	ADJ
cana-3460	36	21	media	medium	NOUN
cana-3460	36	22	can	can	AUX
cana-3460	36	23	be	be	AUX
cana-3460	36	24	illustrated	illustrate	VERB
cana-3460	36	25	and	and	CCONJ
cana-3460	36	26	explained	explain	VERB
cana-3460	36	27	.	.	PUNCT
cana-3460	37	1	ii	ii	PROPN
cana-3460	37	2	.	.	PROPN
cana-3460	37	3	related	relate	VERB
cana-3460	37	4	works	work	NOUN
cana-3460	37	5	kanungo	kanungo	NOUN
cana-3460	37	6	and	and	CCONJ
cana-3460	37	7	jain	jain	PROPN
cana-3460	37	8	(	(	PUNCT
cana-3460	37	9	2023	2023	NUM
cana-3460	37	10	)	)	PUNCT
cana-3460	37	11	suggested	suggest	VERB
cana-3460	37	12	a	a	DET
cana-3460	37	13	hybrid	hybrid	ADJ
cana-3460	37	14	deep	deep	ADJ
cana-3460	37	15	neural	neural	ADJ
cana-3460	37	16	network	network	NOUN
cana-3460	37	17	,	,	PUNCT
cana-3460	37	18	namely	namely	ADV
cana-3460	37	19	g	g	NOUN
cana-3460	37	20	-	-	PUNCT
cana-3460	37	21	lstm	lstm	NOUN
cana-3460	37	22	for	for	ADP
cana-3460	37	23	the	the	DET
cana-3460	37	24	purpose	purpose	NOUN
cana-3460	37	25	of	of	ADP
cana-3460	37	26	sentiment	sentiment	NOUN
cana-3460	37	27	analysis	analysis	NOUN
cana-3460	37	28	on	on	ADP
cana-3460	37	29	twitter	twitter	NOUN
cana-3460	37	30	.	.	PUNCT
cana-3460	38	1	it	it	PRON
cana-3460	38	2	integrates	integrate	VERB
cana-3460	38	3	gated	gate	VERB
cana-3460	38	4	recurrent	recurrent	ADJ
cana-3460	38	5	units	unit	NOUN
cana-3460	38	6	,	,	PUNCT
cana-3460	38	7	or	or	CCONJ
cana-3460	38	8	grus	grus	NOUN
cana-3460	38	9	with	with	ADP
cana-3460	38	10	the	the	DET
cana-3460	38	11	networks	network	NOUN
cana-3460	38	12	of	of	ADP
cana-3460	38	13	lstm	lstm	NOUN
cana-3460	38	14	.	.	PUNCT
cana-3460	39	1	these	these	PRON
cana-3460	39	2	have	have	AUX
cana-3460	39	3	been	be	AUX
cana-3460	39	4	considered	consider	VERB
cana-3460	39	5	effective	effective	ADJ
cana-3460	39	6	to	to	PART
cana-3460	39	7	tackle	tackle	VERB
cana-3460	39	8	the	the	DET
cana-3460	39	9	dynamic	dynamic	ADJ
cana-3460	39	10	nature	nature	NOUN
cana-3460	39	11	of	of	ADP
cana-3460	39	12	disaster	disaster	NOUN
cana-3460	39	13	-	-	PUNCT
cana-3460	39	14	related	relate	VERB
cana-3460	39	15	tweets	tweet	NOUN
cana-3460	39	16	.	.	PUNCT
cana-3460	40	1	thus	thus	ADV
cana-3460	40	2	,	,	PUNCT
cana-3460	40	3	this	this	DET
cana-3460	40	4	hybrid	hybrid	ADJ
cana-3460	40	5	model	model	NOUN
cana-3460	40	6	produced	produce	VERB
cana-3460	40	7	increased	increase	VERB
cana-3460	40	8	accuracy	accuracy	NOUN
cana-3460	40	9	in	in	ADP
cana-3460	40	10	real	real	ADJ
cana-3460	40	11	-	-	PUNCT
cana-3460	40	12	time	time	NOUN
cana-3460	40	13	classification	classification	NOUN
cana-3460	40	14	of	of	ADP
cana-3460	40	15	sentiment	sentiment	NOUN
cana-3460	40	16	,	,	PUNCT
cana-3460	40	17	particularly	particularly	ADV
cana-3460	40	18	where	where	SCONJ
cana-3460	40	19	the	the	DET
cana-3460	40	20	importance	importance	NOUN
cana-3460	40	21	lies	lie	VERB
cana-3460	40	22	for	for	ADP
cana-3460	40	23	the	the	DET
cana-3460	40	24	purpose	purpose	NOUN
cana-3460	40	25	of	of	ADP
cana-3460	40	26	decision	decision	NOUN
cana-3460	40	27	-	-	PUNCT
cana-3460	40	28	making	making	NOUN
cana-3460	40	29	as	as	ADV
cana-3460	40	30	well	well	ADV
cana-3460	40	31	as	as	ADP
cana-3460	40	32	communication	communication	NOUN
cana-3460	40	33	among	among	ADP
cana-3460	40	34	people	people	NOUN
cana-3460	40	35	,	,	PUNCT
cana-3460	40	36	which	which	PRON
cana-3460	40	37	is	be	AUX
cana-3460	40	38	essentially	essentially	ADV
cana-3460	40	39	true	true	ADJ
cana-3460	40	40	in	in	ADP
cana-3460	40	41	cases	case	NOUN
cana-3460	40	42	like	like	ADP
cana-3460	40	43	disaster	disaster	NOUN
cana-3460	40	44	management	management	NOUN
cana-3460	40	45	[	[	X
cana-3460	40	46	15	15	NUM
cana-3460	40	47	]	]	PUNCT
cana-3460	40	48	.	.	PUNCT
cana-3460	41	1	in	in	ADP
cana-3460	41	2	the	the	DET
cana-3460	41	3	domain	domain	NOUN
cana-3460	41	4	of	of	ADP
cana-3460	41	5	aspect	aspect	NOUN
cana-3460	41	6	-	-	PUNCT
cana-3460	41	7	based	base	VERB
cana-3460	41	8	sentiment	sentiment	NOUN
cana-3460	41	9	analysis	analysis	NOUN
cana-3460	41	10	,	,	PUNCT
cana-3460	41	11	khan	khan	PROPN
cana-3460	41	12	and	and	CCONJ
cana-3460	41	13	ridhorkar	ridhorkar	NOUN
cana-3460	41	14	(	(	PUNCT
cana-3460	41	15	2024	2024	NUM
cana-3460	41	16	)	)	PUNCT
cana-3460	41	17	developed	developed	ADJ
cana-3460	41	18	rmdeasd	rmdeasd	NOUN
cana-3460	41	19	,	,	PUNCT
cana-3460	41	20	a	a	DET
cana-3460	41	21	model	model	NOUN
cana-3460	41	22	that	that	PRON
cana-3460	41	23	combines	combine	VERB
cana-3460	41	24	rule	rule	NOUN
cana-3460	41	25	mining	mining	NOUN
cana-3460	41	26	with	with	ADP
cana-3460	41	27	deep	deep	ADJ
cana-3460	41	28	learning	learning	NOUN
cana-3460	41	29	for	for	ADP
cana-3460	41	30	the	the	DET
cana-3460	41	31	improvement	improvement	NOUN
cana-3460	41	32	of	of	ADP
cana-3460	41	33	sentiment	sentiment	NOUN
cana-3460	41	34	analysis	analysis	NOUN
cana-3460	41	35	across	across	ADP
cana-3460	41	36	various	various	ADJ
cana-3460	41	37	domains	domain	NOUN
cana-3460	41	38	.	.	PUNCT
cana-3460	42	1	it	it	PRON
cana-3460	42	2	is	be	AUX
cana-3460	42	3	an	an	DET
cana-3460	42	4	approach	approach	NOUN
cana-3460	42	5	which	which	PRON
cana-3460	42	6	is	be	AUX
cana-3460	42	7	more	more	ADV
cana-3460	42	8	contextual	contextual	ADJ
cana-3460	42	9	as	as	SCONJ
cana-3460	42	10	it	it	PRON
cana-3460	42	11	looks	look	VERB
cana-3460	42	12	at	at	ADP
cana-3460	42	13	aspects	aspect	NOUN
cana-3460	42	14	of	of	ADP
cana-3460	42	15	the	the	DET
cana-3460	42	16	text	text	NOUN
cana-3460	42	17	being	be	AUX
cana-3460	42	18	analyzed	analyze	VERB
cana-3460	42	19	,	,	PUNCT
cana-3460	42	20	like	like	ADP
cana-3460	42	21	features	feature	NOUN
cana-3460	42	22	of	of	ADP
cana-3460	42	23	a	a	DET
cana-3460	42	24	product	product	NOUN
cana-3460	42	25	or	or	CCONJ
cana-3460	42	26	attributes	attribute	NOUN
cana-3460	42	27	of	of	ADP
cana-3460	42	28	a	a	DET
cana-3460	42	29	service	service	NOUN
cana-3460	42	30	.	.	PUNCT
cana-3460	43	1	their	their	PRON
cana-3460	43	2	approach	approach	NOUN
cana-3460	43	3	significantly	significantly	ADV
cana-3460	43	4	outperformed	outperform	VERB
cana-3460	43	5	conventional	conventional	ADJ
cana-3460	43	6	sentiment	sentiment	NOUN
cana-3460	43	7	analysis	analysis	NOUN
cana-3460	43	8	methods	method	NOUN
cana-3460	43	9	when	when	SCONJ
cana-3460	43	10	there	there	PRON
cana-3460	43	11	was	be	VERB
cana-3460	43	12	a	a	DET
cana-3460	43	13	need	need	NOUN
cana-3460	43	14	for	for	ADP
cana-3460	43	15	domain	domain	NOUN
cana-3460	43	16	-	-	PUNCT
cana-3460	43	17	specific	specific	ADJ
cana-3460	43	18	knowledge	knowledge	NOUN
cana-3460	43	19	to	to	PART
cana-3460	43	20	be	be	AUX
cana-3460	43	21	applied	apply	VERB
cana-3460	43	22	correctly	correctly	ADV
cana-3460	43	23	to	to	PART
cana-3460	43	24	interpret	interpret	VERB
cana-3460	43	25	the	the	DET
cana-3460	43	26	sentiments	sentiment	NOUN
cana-3460	43	27	in	in	ADP
cana-3460	43	28	a	a	DET
cana-3460	43	29	situation	situation	NOUN
cana-3460	43	30	[	[	X
cana-3460	43	31	16	16	NUM
cana-3460	43	32	]	]	PUNCT
cana-3460	43	33	.	.	PUNCT
cana-3460	44	1	kim	kim	PROPN
cana-3460	44	2	et	et	PROPN
cana-3460	44	3	al	al	PROPN
cana-3460	44	4	.	.	PROPN
cana-3460	45	1	(	(	PUNCT
cana-3460	45	2	2024	2024	NUM
cana-3460	45	3	)	)	PUNCT
cana-3460	45	4	investigate	investigate	VERB
cana-3460	45	5	the	the	DET
cana-3460	45	6	effects	effect	NOUN
cana-3460	45	7	of	of	ADP
cana-3460	45	8	environmental	environmental	ADJ
cana-3460	45	9	,	,	PUNCT
cana-3460	45	10	social	social	ADJ
cana-3460	45	11	,	,	PUNCT
cana-3460	45	12	and	and	CCONJ
cana-3460	45	13	governance	governance	NOUN
cana-3460	45	14	(	(	PUNCT
cana-3460	45	15	esg	esg	PROPN
cana-3460	45	16	)	)	PUNCT
cana-3460	45	17	news	news	NOUN
cana-3460	45	18	sentiment	sentiment	NOUN
cana-3460	45	19	on	on	ADP
cana-3460	45	20	corporate	corporate	ADJ
cana-3460	45	21	financial	financial	ADJ
cana-3460	45	22	performance	performance	NOUN
cana-3460	45	23	.	.	PUNCT
cana-3460	46	1	drawing	draw	VERB
cana-3460	46	2	on	on	ADP
cana-3460	46	3	data	datum	NOUN
cana-3460	46	4	from	from	ADP
cana-3460	46	5	news	news	NOUN
cana-3460	46	6	articles	article	NOUN
cana-3460	46	7	and	and	CCONJ
cana-3460	46	8	employing	employ	VERB
cana-3460	46	9	a	a	DET
cana-3460	46	10	range	range	NOUN
cana-3460	46	11	of	of	ADP
cana-3460	46	12	cutting	cut	VERB
cana-3460	46	13	-	-	PUNCT
cana-3460	46	14	edge	edge	NOUN
cana-3460	46	15	nlp	nlp	NOUN
cana-3460	46	16	techniques	technique	NOUN
cana-3460	46	17	,	,	PUNCT
cana-3460	46	18	the	the	DET
cana-3460	46	19	researchers	researcher	NOUN
cana-3460	46	20	analyzed	analyze	VERB
cana-3460	46	21	the	the	DET
cana-3460	46	22	effect	effect	NOUN
cana-3460	46	23	of	of	ADP
cana-3460	46	24	sentiments	sentiment	NOUN
cana-3460	46	25	that	that	PRON
cana-3460	46	26	emerge	emerge	VERB
cana-3460	46	27	in	in	ADP
cana-3460	46	28	news	news	NOUN
cana-3460	46	29	articles	article	NOUN
cana-3460	46	30	on	on	ADP
cana-3460	46	31	esg	esg	NOUN
cana-3460	46	32	factors	factor	NOUN
cana-3460	46	33	and	and	CCONJ
cana-3460	46	34	the	the	DET
cana-3460	46	35	resulting	result	VERB
cana-3460	46	36	effects	effect	NOUN
cana-3460	46	37	on	on	ADP
cana-3460	46	38	firms	firm	NOUN
cana-3460	46	39	’	'	PUNCT
cana-3460	46	40	financial	financial	ADJ
cana-3460	46	41	performance	performance	NOUN
cana-3460	46	42	.	.	PUNCT
cana-3460	47	1	there	there	PRON
cana-3460	47	2	was	be	VERB
cana-3460	47	3	note	note	NOUN
cana-3460	47	4	that	that	SCONJ
cana-3460	47	5	business	business	NOUN
cana-3460	47	6	ecosystem	ecosystem	NOUN
cana-3460	47	7	on	on	ADP
cana-3460	47	8	esg	esg	PROPN
cana-3460	47	9	issues	issue	NOUN
cana-3460	47	10	can	can	AUX
cana-3460	47	11	be	be	AUX
cana-3460	47	12	a	a	DET
cana-3460	47	13	good	good	ADJ
cana-3460	47	14	barometer	barometer	NOUN
cana-3460	47	15	for	for	ADP
cana-3460	47	16	business	business	NOUN
cana-3460	47	17	performance	performance	NOUN
cana-3460	47	18	.	.	PUNCT
cana-3460	48	1	from	from	ADP
cana-3460	48	2	this	this	PRON
cana-3460	48	3	we	we	PRON
cana-3460	48	4	infer	infer	VERB
cana-3460	48	5	the	the	DET
cana-3460	48	6	importance	importance	NOUN
cana-3460	48	7	of	of	ADP
cana-3460	48	8	tone	tone	NOUN
cana-3460	48	9	analytics	analytic	NOUN
cana-3460	48	10	in	in	ADP
cana-3460	48	11	financial	financial	ADJ
cana-3460	48	12	market	market	NOUN
cana-3460	48	13	and	and	CCONJ
cana-3460	48	14	investment	investment	NOUN
cana-3460	48	15	plans	plan	NOUN
cana-3460	48	16	[	[	X
cana-3460	48	17	17	17	NUM
cana-3460	48	18	]	]	PUNCT
cana-3460	48	19	.	.	PUNCT
cana-3460	49	1	koena	koena	PROPN
cana-3460	49	2	et	et	PROPN
cana-3460	49	3	al	al	PROPN
cana-3460	49	4	(	(	PUNCT
cana-3460	49	5	2024	2024	NUM
cana-3460	49	6	)	)	PUNCT
cana-3460	49	7	examined	examine	VERB
cana-3460	49	8	the	the	DET
cana-3460	49	9	issue	issue	NOUN
cana-3460	49	10	of	of	ADP
cana-3460	49	11	low	low	ADJ
cana-3460	49	12	resource	resource	NOUN
cana-3460	49	13	languages	language	NOUN
cana-3460	49	14	in	in	ADP
cana-3460	49	15	sentiment	sentiment	NOUN
cana-3460	49	16	analysis	analysis	NOUN
cana-3460	49	17	.	.	PUNCT
cana-3460	50	1	they	they	PRON
cana-3460	50	2	employed	employ	VERB
cana-3460	50	3	explainable	explainable	ADJ
cana-3460	50	4	pre	pre	ADJ
cana-3460	50	5	-	-	ADJ
cana-3460	50	6	trained	train	VERB
cana-3460	50	7	language	language	NOUN
cana-3460	50	8	models	model	NOUN
cana-3460	50	9	to	to	PART
cana-3460	50	10	improve	improve	VERB
cana-3460	50	11	the	the	DET
cana-3460	50	12	output	output	NOUN
cana-3460	50	13	of	of	ADP
cana-3460	50	14	sa	sa	NOUN
cana-3460	50	15	on	on	ADP
cana-3460	50	16	few	few	ADJ
cana-3460	50	17	training	training	NOUN
cana-3460	50	18	data	datum	NOUN
cana-3460	50	19	languages	language	NOUN
cana-3460	50	20	.	.	PUNCT
cana-3460	51	1	more	more	ADJ
cana-3460	51	2	in	in	ADP
cana-3460	51	3	it	it	PRON
cana-3460	51	4	is	be	AUX
cana-3460	51	5	important	important	ADJ
cana-3460	51	6	in	in	ADP
cana-3460	51	7	further	far	ADV
cana-3460	51	8	extending	extend	VERB
cana-3460	51	9	the	the	DET
cana-3460	51	10	benefits	benefit	NOUN
cana-3460	51	11	of	of	ADP
cana-3460	51	12	sentiment	sentiment	NOUN
cana-3460	51	13	analysis	analysis	NOUN
cana-3460	51	14	to	to	ADP
cana-3460	51	15	areas	area	NOUN
cana-3460	51	16	where	where	SCONJ
cana-3460	51	17	appropriate	appropriate	ADJ
cana-3460	51	18	linguistic	linguistic	ADJ
cana-3460	51	19	resources	resource	NOUN
cana-3460	51	20	are	be	AUX
cana-3460	51	21	hard	hard	ADJ
cana-3460	51	22	to	to	PART
cana-3460	51	23	come	come	VERB
cana-3460	51	24	by	by	ADP
cana-3460	51	25	to	to	PART
cana-3460	51	26	allow	allow	VERB
cana-3460	51	27	the	the	DET
cana-3460	51	28	sentiment	sentiment	NOUN
cana-3460	51	29	models	model	NOUN
cana-3460	51	30	to	to	PART
cana-3460	51	31	be	be	AUX
cana-3460	51	32	put	put	VERB
cana-3460	51	33	to	to	ADP
cana-3460	51	34	optimum	optimum	ADJ
cana-3460	51	35	use	use	NOUN
cana-3460	51	36	in	in	ADP
cana-3460	51	37	a	a	DET
cana-3460	51	38	preponderance	preponderance	NOUN
cana-3460	51	39	of	of	ADP
cana-3460	51	40	languages	language	NOUN
cana-3460	51	41	and	and	CCONJ
cana-3460	51	42	communications	communication	NOUN
cana-3460	51	43	on	on	ADP
cana-3460	51	44	applied	apply	VERB
cana-3460	51	45	nonlinear	nonlinear	ADJ
cana-3460	51	46	analysis	analysis	NOUN
cana-3460	51	47	issn	issn	NOUN
cana-3460	51	48	:	:	PUNCT
cana-3460	51	49	1074	1074	NUM
cana-3460	51	50	-	-	PUNCT
cana-3460	51	51	133x	133x	NUM
cana-3460	51	52	vol	vol	NOUN
cana-3460	51	53	32	32	NUM
cana-3460	51	54	no	no	NOUN
cana-3460	51	55	.	.	PUNCT
cana-3460	52	1	7s	7	NOUN
cana-3460	52	2	(	(	PUNCT
cana-3460	52	3	2025	2025	NUM
cana-3460	52	4	)	)	PUNCT
cana-3460	52	5	506	506	NUM
cana-3460	52	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-3460	52	7	circumstances	circumstance	NOUN
cana-3460	52	8	[	[	X
cana-3460	52	9	18	18	NUM
cana-3460	52	10	]	]	PUNCT
cana-3460	52	11	.	.	PUNCT
cana-3460	53	1	liu	liu	PROPN
cana-3460	53	2	et	et	PROPN
cana-3460	53	3	al	al	PROPN
cana-3460	53	4	.	.	PROPN
cana-3460	53	5	,	,	PUNCT
cana-3460	53	6	(	(	PUNCT
cana-3460	53	7	2024	2024	NUM
cana-3460	53	8	)	)	PUNCT
cana-3460	53	9	adopted	adopt	VERB
cana-3460	53	10	sentiment	sentiment	NOUN
cana-3460	53	11	analysis	analysis	NOUN
cana-3460	53	12	in	in	ADP
cana-3460	53	13	financial	financial	ADJ
cana-3460	53	14	markets	market	NOUN
cana-3460	53	15	where	where	SCONJ
cana-3460	53	16	the	the	DET
cana-3460	53	17	main	main	ADJ
cana-3460	53	18	focus	focus	NOUN
cana-3460	53	19	was	be	AUX
cana-3460	53	20	data	datum	NOUN
cana-3460	53	21	from	from	ADP
cana-3460	53	22	the	the	DET
cana-3460	53	23	social	social	ADJ
cana-3460	53	24	networks	network	NOUN
cana-3460	53	25	for	for	ADP
cana-3460	53	26	stock	stock	NOUN
cana-3460	53	27	market	market	NOUN
cana-3460	53	28	prediction	prediction	NOUN
cana-3460	53	29	.	.	PUNCT
cana-3460	54	1	in	in	ADP
cana-3460	54	2	this	this	DET
cana-3460	54	3	model	model	NOUN
cana-3460	54	4	,	,	PUNCT
cana-3460	54	5	nlp	nlp	PROPN
cana-3460	54	6	was	be	AUX
cana-3460	54	7	employed	employ	VERB
cana-3460	54	8	to	to	PART
cana-3460	54	9	capture	capture	VERB
cana-3460	54	10	the	the	DET
cana-3460	54	11	peoples	people	NOUN
cana-3460	54	12	’	’	PART
cana-3460	54	13	attitude	attitude	NOUN
cana-3460	54	14	on	on	ADP
cana-3460	54	15	the	the	DET
cana-3460	54	16	social	social	ADJ
cana-3460	54	17	media	medium	NOUN
cana-3460	54	18	platforms	platform	NOUN
cana-3460	54	19	and	and	CCONJ
cana-3460	54	20	the	the	DET
cana-3460	54	21	results	result	NOUN
cana-3460	54	22	collected	collect	VERB
cana-3460	54	23	can	can	AUX
cana-3460	54	24	be	be	AUX
cana-3460	54	25	utilized	utilize	VERB
cana-3460	54	26	by	by	ADP
cana-3460	54	27	investors	investor	NOUN
cana-3460	54	28	to	to	PART
cana-3460	54	29	make	make	VERB
cana-3460	54	30	better	well	ADJ
cana-3460	54	31	decisions	decision	NOUN
cana-3460	54	32	particularly	particularly	ADV
cana-3460	54	33	on	on	ADP
cana-3460	54	34	feelings	feeling	NOUN
cana-3460	54	35	towards	towards	ADP
cana-3460	54	36	fi	fi	NOUN
cana-3460	54	37	nancial	nancial	ADJ
cana-3460	54	38	assest	assest	NOUN
cana-3460	54	39	.	.	PUNCT
cana-3460	55	1	it	it	PRON
cana-3460	55	2	highlighted	highlight	VERB
cana-3460	55	3	potential	potential	NOUN
cana-3460	55	4	of	of	ADP
cana-3460	55	5	such	such	DET
cana-3460	55	6	an	an	DET
cana-3460	55	7	analysis	analysis	NOUN
cana-3460	55	8	for	for	SCONJ
cana-3460	55	9	resource	resource	NOUN
cana-3460	55	10	management	management	NOUN
cana-3460	55	11	to	to	PART
cana-3460	55	12	invest	invest	VERB
cana-3460	55	13	and	and	CCONJ
cana-3460	55	14	predict	predict	VERB
cana-3460	55	15	the	the	DET
cana-3460	55	16	shifts	shift	NOUN
cana-3460	55	17	in	in	ADP
cana-3460	55	18	the	the	DET
cana-3460	55	19	market	market	NOUN
cana-3460	55	20	[	[	X
cana-3460	55	21	22	22	NUM
cana-3460	55	22	]	]	PUNCT
cana-3460	55	23	.	.	PUNCT
cana-3460	56	1	liang	liang	PROPN
cana-3460	56	2	-	-	PUNCT
cana-3460	56	3	chin	chin	PROPN
cana-3460	56	4	et	et	PROPN
cana-3460	56	5	al	al	PROPN
cana-3460	56	6	.	.	PROPN
cana-3460	57	1	(	(	PUNCT
cana-3460	57	2	2024	2024	NUM
cana-3460	57	3	)	)	PUNCT
cana-3460	57	4	was	be	AUX
cana-3460	57	5	more	more	ADV
cana-3460	57	6	concerned	concerned	ADJ
cana-3460	57	7	with	with	ADP
cana-3460	57	8	employment	employment	NOUN
cana-3460	57	9	of	of	ADP
cana-3460	57	10	the	the	DET
cana-3460	57	11	sentiment	sentiment	NOUN
cana-3460	57	12	analysis	analysis	NOUN
cana-3460	57	13	aimed	aim	VERB
cana-3460	57	14	for	for	ADP
cana-3460	57	15	tracking	track	VERB
cana-3460	57	16	sentiments	sentiment	NOUN
cana-3460	57	17	regarding	regard	VERB
cana-3460	57	18	acceptance	acceptance	NOUN
cana-3460	57	19	of	of	ADP
cana-3460	57	20	the	the	DET
cana-3460	57	21	vaccine	vaccine	NOUN
cana-3460	57	22	or	or	CCONJ
cana-3460	57	23	its	its	PRON
cana-3460	57	24	refusal	refusal	NOUN
cana-3460	57	25	.	.	PUNCT
cana-3460	58	1	with	with	ADP
cana-3460	58	2	the	the	DET
cana-3460	58	3	help	help	NOUN
cana-3460	58	4	of	of	ADP
cana-3460	58	5	real	real	ADJ
cana-3460	58	6	-	-	PUNCT
cana-3460	58	7	time	time	NOUN
cana-3460	58	8	nlp	nlp	NOUN
cana-3460	58	9	-	-	PUNCT
cana-3460	58	10	based	base	VERB
cana-3460	58	11	monitoring	monitoring	NOUN
cana-3460	58	12	solutions	solution	NOUN
cana-3460	58	13	,	,	PUNCT
cana-3460	58	14	their	their	PRON
cana-3460	58	15	work	work	NOUN
cana-3460	58	16	provided	provide	VERB
cana-3460	58	17	very	very	ADV
cana-3460	58	18	important	important	ADJ
cana-3460	58	19	information	information	NOUN
cana-3460	58	20	about	about	ADP
cana-3460	58	21	the	the	DET
cana-3460	58	22	public	public	ADJ
cana-3460	58	23	opinion	opinion	NOUN
cana-3460	58	24	about	about	ADP
cana-3460	58	25	the	the	DET
cana-3460	58	26	vaccines	vaccine	NOUN
cana-3460	58	27	.	.	PUNCT
cana-3460	59	1	such	such	DET
cana-3460	59	2	an	an	DET
cana-3460	59	3	analysis	analysis	NOUN
cana-3460	59	4	is	be	AUX
cana-3460	59	5	highly	highly	ADV
cana-3460	59	6	useful	useful	ADJ
cana-3460	59	7	for	for	ADP
cana-3460	59	8	healthcare	healthcare	NOUN
cana-3460	59	9	organizations	organization	NOUN
cana-3460	59	10	and	and	CCONJ
cana-3460	59	11	policymakers	policymaker	NOUN
cana-3460	59	12	in	in	ADP
cana-3460	59	13	monitoring	monitor	VERB
cana-3460	59	14	the	the	DET
cana-3460	59	15	shift	shift	NOUN
cana-3460	59	16	in	in	ADP
cana-3460	59	17	sentiments	sentiment	NOUN
cana-3460	59	18	and	and	CCONJ
cana-3460	59	19	making	make	VERB
cana-3460	59	20	adjustments	adjustment	NOUN
cana-3460	59	21	to	to	ADP
cana-3460	59	22	strategies	strategy	NOUN
cana-3460	59	23	in	in	ADP
cana-3460	59	24	encouraging	encourage	VERB
cana-3460	59	25	vaccine	vaccine	NOUN
cana-3460	59	26	acceptance	acceptance	NOUN
cana-3460	59	27	[	[	X
cana-3460	59	28	21	21	NUM
cana-3460	59	29	]	]	PUNCT
cana-3460	59	30	.	.	PUNCT
cana-3460	60	1	miah	miah	PROPN
cana-3460	60	2	et	et	PROPN
cana-3460	60	3	al	al	PROPN
cana-3460	60	4	.	.	PROPN
cana-3460	61	1	(	(	PUNCT
cana-3460	61	2	2024	2024	NUM
cana-3460	61	3	)	)	PUNCT
cana-3460	61	4	came	come	VERB
cana-3460	61	5	up	up	ADP
cana-3460	61	6	with	with	ADP
cana-3460	61	7	a	a	DET
cana-3460	61	8	multimodal	multimodal	ADJ
cana-3460	61	9	approach	approach	NOUN
cana-3460	61	10	in	in	ADP
cana-3460	61	11	sentiment	sentiment	NOUN
cana-3460	61	12	analysis	analysis	NOUN
cana-3460	61	13	where	where	SCONJ
cana-3460	61	14	transformers	transformer	NOUN
cana-3460	61	15	are	be	AUX
cana-3460	61	16	combined	combine	VERB
cana-3460	61	17	with	with	ADP
cana-3460	61	18	llm	llm	PROPN
cana-3460	61	19	for	for	ADP
cana-3460	61	20	cross	cross	ADJ
cana-3460	61	21	-	-	ADJ
cana-3460	61	22	lingual	lingual	ADJ
cana-3460	61	23	sentiment	sentiment	NOUN
cana-3460	61	24	analysis	analysis	NOUN
cana-3460	61	25	.	.	PUNCT
cana-3460	62	1	in	in	ADP
cana-3460	62	2	this	this	DET
cana-3460	62	3	way	way	NOUN
cana-3460	62	4	,	,	PUNCT
cana-3460	62	5	this	this	DET
cana-3460	62	6	hybrid	hybrid	ADJ
cana-3460	62	7	model	model	NOUN
cana-3460	62	8	shows	show	VERB
cana-3460	62	9	the	the	DET
cana-3460	62	10	potentiality	potentiality	NOUN
cana-3460	62	11	of	of	ADP
cana-3460	62	12	handling	handle	VERB
cana-3460	62	13	multilingual	multilingual	ADJ
cana-3460	62	14	texts	text	NOUN
cana-3460	62	15	especially	especially	ADV
cana-3460	62	16	in	in	ADP
cana-3460	62	17	assessing	assess	VERB
cana-3460	62	18	global	global	ADJ
cana-3460	62	19	public	public	ADJ
cana-3460	62	20	opinion	opinion	NOUN
cana-3460	62	21	with	with	ADP
cana-3460	62	22	sentiment	sentiment	NOUN
cana-3460	62	23	.	.	PUNCT
cana-3460	63	1	for	for	ADP
cana-3460	63	2	instance	instance	NOUN
cana-3460	63	3	,	,	PUNCT
cana-3460	63	4	analysis	analysis	NOUN
cana-3460	63	5	across	across	ADP
cana-3460	63	6	various	various	ADJ
cana-3460	63	7	languages	language	NOUN
cana-3460	63	8	and	and	CCONJ
cana-3460	63	9	dialects	dialect	NOUN
cana-3460	63	10	brings	bring	VERB
cana-3460	63	11	out	out	ADP
cana-3460	63	12	the	the	DET
cana-3460	63	13	reality	reality	NOUN
cana-3460	63	14	of	of	ADP
cana-3460	63	15	what	what	PRON
cana-3460	63	16	is	be	AUX
cana-3460	63	17	being	be	AUX
cana-3460	63	18	understood	understand	VERB
cana-3460	63	19	by	by	ADP
cana-3460	63	20	public	public	ADJ
cana-3460	63	21	opinion	opinion	NOUN
cana-3460	63	22	[	[	X
cana-3460	63	23	26	26	NUM
cana-3460	63	24	]	]	PUNCT
cana-3460	63	25	.	.	PUNCT
cana-3460	64	1	liu	liu	PROPN
cana-3460	64	2	et	et	PROPN
cana-3460	64	3	al	al	PROPN
cana-3460	64	4	.	.	PROPN
cana-3460	64	5	(	(	PUNCT
cana-3460	64	6	2024	2024	NUM
cana-3460	64	7	)	)	PUNCT
cana-3460	64	8	further	far	ADV
cana-3460	64	9	examined	examine	VERB
cana-3460	64	10	sentiment	sentiment	NOUN
cana-3460	64	11	analysis	analysis	NOUN
cana-3460	64	12	in	in	ADP
cana-3460	64	13	the	the	DET
cana-3460	64	14	prediction	prediction	NOUN
cana-3460	64	15	of	of	ADP
cana-3460	64	16	consumer	consumer	NOUN
cana-3460	64	17	behavior	behavior	NOUN
cana-3460	64	18	.	.	PUNCT
cana-3460	65	1	they	they	PRON
cana-3460	65	2	considered	consider	VERB
cana-3460	65	3	social	social	ADJ
cana-3460	65	4	network	network	NOUN
cana-3460	65	5	data	datum	NOUN
cana-3460	65	6	as	as	ADP
cana-3460	65	7	a	a	DET
cana-3460	65	8	source	source	NOUN
cana-3460	65	9	to	to	PART
cana-3460	65	10	predict	predict	VERB
cana-3460	65	11	consumer	consumer	NOUN
cana-3460	65	12	reaction	reaction	NOUN
cana-3460	65	13	and	and	CCONJ
cana-3460	65	14	behavior	behavior	NOUN
cana-3460	65	15	patterns	pattern	NOUN
cana-3460	65	16	.	.	PUNCT
cana-3460	66	1	customer	customer	NOUN
cana-3460	66	2	sentiment	sentiment	NOUN
cana-3460	66	3	analyzed	analyze	VERB
cana-3460	66	4	in	in	ADP
cana-3460	66	5	real	real	ADJ
cana-3460	66	6	-	-	PUNCT
cana-3460	66	7	time	time	NOUN
cana-3460	66	8	was	be	AUX
cana-3460	66	9	found	find	VERB
cana-3460	66	10	to	to	PART
cana-3460	66	11	guide	guide	VERB
cana-3460	66	12	the	the	DET
cana-3460	66	13	business	business	NOUN
cana-3460	66	14	strategies	strategy	NOUN
cana-3460	66	15	according	accord	VERB
cana-3460	66	16	to	to	ADP
cana-3460	66	17	the	the	DET
cana-3460	66	18	consumer	consumer	NOUN
cana-3460	66	19	preference	preference	NOUN
cana-3460	66	20	,	,	PUNCT
cana-3460	66	21	leading	lead	VERB
cana-3460	66	22	to	to	ADP
cana-3460	66	23	more	more	ADJ
cana-3460	66	24	customers	customer	NOUN
cana-3460	66	25	'	'	PART
cana-3460	66	26	engagement	engagement	NOUN
cana-3460	66	27	and	and	CCONJ
cana-3460	66	28	satisfaction	satisfaction	NOUN
cana-3460	66	29	[	[	X
cana-3460	66	30	23	23	NUM
cana-3460	66	31	]	]	PUNCT
cana-3460	66	32	.	.	PUNCT
cana-3460	67	1	mandava	mandava	PROPN
cana-3460	67	2	,	,	PUNCT
cana-3460	67	3	oyer	oyer	NOUN
cana-3460	67	4	,	,	PUNCT
cana-3460	67	5	and	and	CCONJ
cana-3460	67	6	park	park	NOUN
cana-3460	67	7	(	(	PUNCT
cana-3460	67	8	2024	2024	NUM
cana-3460	67	9	)	)	PUNCT
cana-3460	67	10	carried	carry	VERB
cana-3460	67	11	out	out	ADP
cana-3460	67	12	a	a	DET
cana-3460	67	13	quantitative	quantitative	ADJ
cana-3460	67	14	analysis	analysis	NOUN
cana-3460	67	15	of	of	ADP
cana-3460	67	16	twitter	twitter	NOUN
cana-3460	67	17	trends	trend	NOUN
cana-3460	67	18	.	.	PUNCT
cana-3460	68	1	the	the	DET
cana-3460	68	2	authors	author	NOUN
cana-3460	68	3	analyzed	analyze	VERB
cana-3460	68	4	the	the	DET
cana-3460	68	5	discussion	discussion	NOUN
cana-3460	68	6	surrounding	surround	VERB
cana-3460	68	7	rhinoplasty	rhinoplasty	NOUN
cana-3460	68	8	.	.	PUNCT
cana-3460	69	1	through	through	ADP
cana-3460	69	2	sentiment	sentiment	NOUN
cana-3460	69	3	analysis	analysis	NOUN
cana-3460	69	4	,	,	PUNCT
cana-3460	69	5	their	their	PRON
cana-3460	69	6	study	study	NOUN
cana-3460	69	7	revealed	reveal	VERB
cana-3460	69	8	how	how	SCONJ
cana-3460	69	9	public	public	ADJ
cana-3460	69	10	opinion	opinion	NOUN
cana-3460	69	11	regarding	regard	VERB
cana-3460	69	12	cosmetic	cosmetic	ADJ
cana-3460	69	13	surgery	surgery	NOUN
cana-3460	69	14	changes	change	NOUN
cana-3460	69	15	over	over	ADP
cana-3460	69	16	time	time	NOUN
cana-3460	69	17	and	and	CCONJ
cana-3460	69	18	gives	give	VERB
cana-3460	69	19	healthcare	healthcare	NOUN
cana-3460	69	20	professionals	professional	NOUN
cana-3460	69	21	and	and	CCONJ
cana-3460	69	22	marketers	marketer	NOUN
cana-3460	69	23	insight	insight	VERB
cana-3460	69	24	into	into	ADP
cana-3460	69	25	consumer	consumer	NOUN
cana-3460	69	26	perceptions	perception	NOUN
cana-3460	69	27	of	of	ADP
cana-3460	69	28	aesthetic	aesthetic	ADJ
cana-3460	69	29	procedures	procedure	NOUN
cana-3460	69	30	[	[	X
cana-3460	69	31	25	25	NUM
cana-3460	69	32	]	]	PUNCT
cana-3460	69	33	.	.	PUNCT
cana-3460	70	1	finally	finally	ADV
cana-3460	70	2	,	,	PUNCT
cana-3460	70	3	lau	lau	PROPN
cana-3460	70	4	et	et	PROPN
cana-3460	70	5	al	al	PROPN
cana-3460	70	6	.	.	PROPN
cana-3460	71	1	(	(	PUNCT
cana-3460	71	2	2024	2024	NUM
cana-3460	71	3	)	)	PUNCT
cana-3460	71	4	identified	identify	VERB
cana-3460	71	5	the	the	DET
cana-3460	71	6	study	study	NOUN
cana-3460	71	7	focus	focus	NOUN
cana-3460	71	8	as	as	ADP
cana-3460	71	9	"	"	PUNCT
cana-3460	71	10	sentiment	sentiment	NOUN
cana-3460	71	11	analysis	analysis	NOUN
cana-3460	71	12	of	of	ADP
cana-3460	71	13	pediatric	pediatric	ADJ
cana-3460	71	14	cancer	cancer	NOUN
cana-3460	71	15	communication	communication	NOUN
cana-3460	71	16	on	on	ADP
cana-3460	71	17	twitter	twitter	NOUN
cana-3460	71	18	.	.	PUNCT
cana-3460	71	19	"	"	PUNCT
cana-3460	72	1	their	their	PRON
cana-3460	72	2	research	research	NOUN
cana-3460	72	3	applied	apply	VERB
cana-3460	72	4	nlp	nlp	NOUN
cana-3460	72	5	in	in	ADP
cana-3460	72	6	examining	examine	VERB
cana-3460	72	7	public	public	ADJ
cana-3460	72	8	sentiments	sentiment	NOUN
cana-3460	72	9	around	around	ADP
cana-3460	72	10	the	the	DET
cana-3460	72	11	issues	issue	NOUN
cana-3460	72	12	of	of	ADP
cana-3460	72	13	pediatric	pediatric	ADJ
cana-3460	72	14	cancer	cancer	NOUN
cana-3460	72	15	discussions	discussion	NOUN
cana-3460	72	16	,	,	PUNCT
cana-3460	72	17	assisting	assist	VERB
cana-3460	72	18	health	health	NOUN
cana-3460	72	19	professionals	professional	NOUN
cana-3460	72	20	and	and	CCONJ
cana-3460	72	21	advocacy	advocacy	NOUN
cana-3460	72	22	organizations	organization	NOUN
cana-3460	72	23	understand	understand	VERB
cana-3460	72	24	the	the	DET
cana-3460	72	25	sentiment	sentiment	NOUN
cana-3460	72	26	among	among	ADP
cana-3460	72	27	the	the	DET
cana-3460	72	28	general	general	ADJ
cana-3460	72	29	population	population	NOUN
cana-3460	72	30	concerning	concern	VERB
cana-3460	72	31	emotions	emotion	NOUN
cana-3460	72	32	related	relate	VERB
cana-3460	72	33	to	to	ADP
cana-3460	72	34	the	the	DET
cana-3460	72	35	topic	topic	NOUN
cana-3460	72	36	.	.	PUNCT
cana-3460	73	1	from	from	ADP
cana-3460	73	2	this	this	DET
cana-3460	73	3	paper	paper	NOUN
cana-3460	73	4	’s	’s	PART
cana-3460	73	5	perspective	perspective	NOUN
cana-3460	73	6	,	,	PUNCT
cana-3460	73	7	this	this	DET
cana-3460	73	8	work	work	NOUN
cana-3460	73	9	is	be	AUX
cana-3460	73	10	crucial	crucial	ADJ
cana-3460	73	11	for	for	ADP
cana-3460	73	12	the	the	DET
cana-3460	73	13	study	study	NOUN
cana-3460	73	14	and	and	CCONJ
cana-3460	73	15	direction	direction	NOUN
cana-3460	73	16	of	of	ADP
cana-3460	73	17	public	public	ADJ
cana-3460	73	18	health	health	NOUN
cana-3460	73	19	communication	communication	NOUN
cana-3460	73	20	approaches	approach	NOUN
cana-3460	73	21	to	to	ADP
cana-3460	73	22	concerned	concerned	ADJ
cana-3460	73	23	groups	group	NOUN
cana-3460	73	24	[	[	X
cana-3460	73	25	19	19	NUM
cana-3460	73	26	]	]	PUNCT
cana-3460	73	27	.	.	PUNCT
cana-3460	74	1	iii	iii	X
cana-3460	74	2	.	.	PUNCT
cana-3460	74	3	methods	method	NOUN
cana-3460	74	4	and	and	CCONJ
cana-3460	74	5	materials	material	NOUN
cana-3460	74	6	the	the	DET
cana-3460	74	7	following	follow	VERB
cana-3460	74	8	part	part	NOUN
cana-3460	74	9	describes	describe	VERB
cana-3460	74	10	the	the	DET
cana-3460	74	11	processes	process	NOUN
cana-3460	74	12	of	of	ADP
cana-3460	74	13	data	datum	NOUN
cana-3460	74	14	sampling	sampling	NOUN
cana-3460	74	15	,	,	PUNCT
cana-3460	74	16	algorithms	algorithm	NOUN
cana-3460	74	17	choice	choice	NOUN
cana-3460	74	18	,	,	PUNCT
cana-3460	74	19	and	and	CCONJ
cana-3460	74	20	methods	method	NOUN
cana-3460	74	21	realization	realization	NOUN
cana-3460	74	22	for	for	ADP
cana-3460	74	23	the	the	DET
cana-3460	74	24	sentiment	sentiment	NOUN
cana-3460	74	25	analysis	analysis	NOUN
cana-3460	74	26	of	of	ADP
cana-3460	74	27	social	social	ADJ
cana-3460	74	28	media	medium	NOUN
cana-3460	74	29	data	datum	NOUN
cana-3460	74	30	.	.	PUNCT
cana-3460	75	1	the	the	DET
cana-3460	75	2	purpose	purpose	NOUN
cana-3460	75	3	of	of	ADP
cana-3460	75	4	the	the	DET
cana-3460	75	5	current	current	ADJ
cana-3460	75	6	research	research	NOUN
cana-3460	75	7	is	be	AUX
cana-3460	75	8	to	to	PART
cana-3460	75	9	review	review	VERB
cana-3460	75	10	and	and	CCONJ
cana-3460	75	11	contrast	contrast	VERB
cana-3460	75	12	various	various	ADJ
cana-3460	75	13	states	state	NOUN
cana-3460	75	14	of	of	ADP
cana-3460	75	15	the	the	DET
cana-3460	75	16	art	art	NOUN
cana-3460	75	17	nlp	nlp	NOUN
cana-3460	75	18	approaches	approach	NOUN
cana-3460	75	19	employed	employ	VERB
cana-3460	75	20	for	for	ADP
cana-3460	75	21	sa	sa	PROPN
cana-3460	75	22	,	,	PUNCT
cana-3460	75	23	with	with	ADP
cana-3460	75	24	reference	reference	NOUN
cana-3460	75	25	to	to	ADP
cana-3460	75	26	social	social	ADJ
cana-3460	75	27	media	medium	NOUN
cana-3460	75	28	data	datum	NOUN
cana-3460	75	29	[	[	X
cana-3460	75	30	4	4	NUM
cana-3460	75	31	]	]	PUNCT
cana-3460	75	32	.	.	PUNCT
cana-3460	76	1	1	1	X
cana-3460	76	2	.	.	X
cana-3460	76	3	data	datum	NOUN
cana-3460	76	4	collection	collection	NOUN
cana-3460	76	5	the	the	DET
cana-3460	76	6	dataset	dataset	NOUN
cana-3460	76	7	for	for	ADP
cana-3460	76	8	this	this	DET
cana-3460	76	9	study	study	NOUN
cana-3460	76	10	was	be	AUX
cana-3460	76	11	obtained	obtain	VERB
cana-3460	76	12	by	by	ADP
cana-3460	76	13	the	the	DET
cana-3460	76	14	use	use	NOUN
cana-3460	76	15	of	of	ADP
cana-3460	76	16	the	the	DET
cana-3460	76	17	twitter	twitter	NOUN
cana-3460	76	18	api	api	NOUN
cana-3460	76	19	.	.	PUNCT
cana-3460	77	1	specific	specific	ADJ
cana-3460	77	2	keywords	keyword	NOUN
cana-3460	77	3	that	that	PRON
cana-3460	77	4	refer	refer	VERB
cana-3460	77	5	to	to	ADP
cana-3460	77	6	the	the	DET
cana-3460	77	7	trending	trend	VERB
cana-3460	77	8	topics	topic	NOUN
cana-3460	77	9	are	be	AUX
cana-3460	77	10	used	use	VERB
cana-3460	77	11	in	in	ADP
cana-3460	77	12	retrieving	retrieve	VERB
cana-3460	77	13	5,000	5,000	NUM
cana-3460	77	14	tweets	tweet	NOUN
cana-3460	77	15	within	within	ADP
cana-3460	77	16	one	one	NUM
cana-3460	77	17	month	month	NOUN
cana-3460	77	18	.	.	PUNCT
cana-3460	78	1	the	the	DET
cana-3460	78	2	tweets	tweet	NOUN
cana-3460	78	3	from	from	ADP
cana-3460	78	4	this	this	DET
cana-3460	78	5	dataset	dataset	NOUN
cana-3460	78	6	are	be	AUX
cana-3460	78	7	in	in	ADP
cana-3460	78	8	the	the	DET
cana-3460	78	9	english	english	ADJ
cana-3460	78	10	language	language	NOUN
cana-3460	78	11	and	and	CCONJ
cana-3460	78	12	have	have	AUX
cana-3460	78	13	been	be	AUX
cana-3460	78	14	filtered	filter	VERB
cana-3460	78	15	such	such	ADJ
cana-3460	78	16	that	that	SCONJ
cana-3460	78	17	the	the	DET
cana-3460	78	18	selection	selection	NOUN
cana-3460	78	19	only	only	ADV
cana-3460	78	20	has	have	VERB
cana-3460	78	21	the	the	DET
cana-3460	78	22	hashtags	hashtag	NOUN
cana-3460	78	23	#	#	NOUN
cana-3460	78	24	technology	technology	NOUN
cana-3460	78	25	,	,	PUNCT
cana-3460	78	26	#	#	NOUN
cana-3460	78	27	politics	politic	NOUN
cana-3460	78	28	,	,	PUNCT
cana-3460	78	29	and	and	CCONJ
cana-3460	78	30	#	#	SYM
cana-3460	78	31	healthcare	healthcare	NOUN
cana-3460	78	32	[	[	X
cana-3460	78	33	5	5	NUM
cana-3460	78	34	]	]	PUNCT
cana-3460	78	35	.	.	PUNCT
cana-3460	79	1	this	this	PRON
cana-3460	79	2	is	be	AUX
cana-3460	79	3	pre	pre	ADJ
cana-3460	79	4	-	-	ADJ
cana-3460	79	5	processed	processed	ADJ
cana-3460	79	6	text	text	NOUN
cana-3460	79	7	data	datum	NOUN
cana-3460	79	8	;	;	PUNCT
cana-3460	79	9	noise	noise	NOUN
cana-3460	79	10	such	such	ADJ
cana-3460	79	11	as	as	ADP
cana-3460	79	12	urls	url	NOUN
cana-3460	79	13	,	,	PUNCT
cana-3460	79	14	mentions	mention	NOUN
cana-3460	79	15	,	,	PUNCT
cana-3460	79	16	hashtags	hashtag	NOUN
cana-3460	79	17	,	,	PUNCT
cana-3460	79	18	and	and	CCONJ
cana-3460	79	19	special	special	ADJ
cana-3460	79	20	characters	character	NOUN
cana-3460	79	21	were	be	AUX
cana-3460	79	22	removed	remove	VERB
cana-3460	79	23	from	from	ADP
cana-3460	79	24	the	the	DET
cana-3460	79	25	dataset	dataset	NOUN
cana-3460	79	26	.	.	PUNCT
cana-3460	80	1	the	the	DET
cana-3460	80	2	tweets	tweet	NOUN
cana-3460	80	3	were	be	AUX
cana-3460	80	4	labeled	label	VERB
cana-3460	80	5	manually	manually	ADV
cana-3460	80	6	for	for	ADP
cana-3460	80	7	sentiment	sentiment	NOUN
cana-3460	80	8	classification	classification	NOUN
cana-3460	80	9	:	:	PUNCT
cana-3460	80	10	either	either	CCONJ
cana-3460	80	11	positive	positive	ADJ
cana-3460	80	12	,	,	PUNCT
cana-3460	80	13	negative	negative	ADJ
cana-3460	80	14	,	,	PUNCT
cana-3460	80	15	or	or	CCONJ
cana-3460	80	16	neutral	neutral	ADJ
cana-3460	80	17	.	.	PUNCT
cana-3460	81	1	this	this	DET
cana-3460	81	2	labeled	label	VERB
cana-3460	81	3	dataset	dataset	NOUN
cana-3460	81	4	was	be	AUX
cana-3460	81	5	used	use	VERB
cana-3460	81	6	to	to	PART
cana-3460	81	7	train	train	VERB
cana-3460	81	8	and	and	CCONJ
cana-3460	81	9	evaluate	evaluate	VERB
cana-3460	81	10	the	the	DET
cana-3460	81	11	sentiment	sentiment	NOUN
cana-3460	81	12	analysis	analysis	NOUN
cana-3460	81	13	models	model	NOUN
cana-3460	81	14	.	.	PUNCT
cana-3460	82	1	communications	communication	NOUN
cana-3460	82	2	on	on	ADP
cana-3460	82	3	applied	apply	VERB
cana-3460	82	4	nonlinear	nonlinear	ADJ
cana-3460	82	5	analysis	analysis	NOUN
cana-3460	82	6	issn	issn	NOUN
cana-3460	82	7	:	:	PUNCT
cana-3460	82	8	1074	1074	NUM
cana-3460	82	9	-	-	PUNCT
cana-3460	82	10	133x	133x	NUM
cana-3460	82	11	vol	vol	NOUN
cana-3460	82	12	32	32	NUM
cana-3460	82	13	no	no	NOUN
cana-3460	82	14	.	.	PUNCT
cana-3460	83	1	7s	7	NOUN
cana-3460	83	2	(	(	PUNCT
cana-3460	83	3	2025	2025	NUM
cana-3460	83	4	)	)	PUNCT
cana-3460	83	5	507	507	NUM
cana-3460	83	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3460	83	7	2	2	NUM
cana-3460	83	8	.	.	NOUN
cana-3460	83	9	sentiment	sentiment	NOUN
cana-3460	83	10	analysis	analysis	NOUN
cana-3460	83	11	algorithms	algorithm	NOUN
cana-3460	83	12	the	the	DET
cana-3460	83	13	three	three	NUM
cana-3460	83	14	most	most	ADV
cana-3460	83	15	popular	popular	ADJ
cana-3460	83	16	machine	machine	NOUN
cana-3460	83	17	learning	learn	VERB
cana-3460	83	18	algorithms	algorithm	NOUN
cana-3460	83	19	for	for	ADP
cana-3460	83	20	sentiment	sentiment	NOUN
cana-3460	83	21	analysis	analysis	NOUN
cana-3460	83	22	include	include	VERB
cana-3460	83	23	“	"	PUNCT
cana-3460	83	24	logistic	logistic	ADJ
cana-3460	83	25	regression	regression	NOUN
cana-3460	83	26	,	,	PUNCT
cana-3460	83	27	support	support	NOUN
cana-3460	83	28	vector	vector	NOUN
cana-3460	83	29	machine	machine	NOUN
cana-3460	83	30	(	(	PUNCT
cana-3460	83	31	svm	svm	PROPN
cana-3460	83	32	)	)	PUNCT
cana-3460	83	33	,	,	PUNCT
cana-3460	83	34	and	and	CCONJ
cana-3460	83	35	bidirectional	bidirectional	ADJ
cana-3460	83	36	encoder	encoder	NOUN
cana-3460	83	37	representations	representation	VERB
cana-3460	83	38	from	from	ADP
cana-3460	83	39	transformers	transformer	NOUN
cana-3460	83	40	(	(	PUNCT
cana-3460	83	41	bert	bert	PROPN
cana-3460	83	42	)	)	PUNCT
cana-3460	83	43	”	"	PUNCT
cana-3460	83	44	.	.	PUNCT
cana-3460	84	1	the	the	DET
cana-3460	84	2	selection	selection	NOUN
cana-3460	84	3	for	for	ADP
cana-3460	84	4	this	this	DET
cana-3460	84	5	research	research	NOUN
cana-3460	84	6	relied	rely	VERB
cana-3460	84	7	on	on	ADP
cana-3460	84	8	three	three	NUM
cana-3460	84	9	different	different	ADJ
cana-3460	84	10	algorithms	algorithm	NOUN
cana-3460	84	11	as	as	SCONJ
cana-3460	84	12	they	they	PRON
cana-3460	84	13	are	be	AUX
cana-3460	84	14	commercially	commercially	ADV
cana-3460	84	15	applied	apply	VERB
cana-3460	84	16	and	and	CCONJ
cana-3460	84	17	because	because	SCONJ
cana-3460	84	18	of	of	ADP
cana-3460	84	19	their	their	PRON
cana-3460	84	20	complexity	complexity	NOUN
cana-3460	84	21	from	from	ADP
cana-3460	84	22	a	a	DET
cana-3460	84	23	traditional	traditional	ADJ
cana-3460	84	24	perspective	perspective	NOUN
cana-3460	84	25	of	of	ADP
cana-3460	84	26	machine	machine	NOUN
cana-3460	84	27	learning	learning	NOUN
cana-3460	84	28	models	model	NOUN
cana-3460	84	29	to	to	ADP
cana-3460	84	30	advanced	advanced	ADJ
cana-3460	84	31	deep	deep	ADJ
cana-3460	84	32	learning	learning	NOUN
cana-3460	84	33	techniques	technique	NOUN
cana-3460	84	34	[	[	X
cana-3460	84	35	6	6	NUM
cana-3460	84	36	]	]	PUNCT
cana-3460	84	37	.	.	PUNCT
cana-3460	85	1	2.1	2.1	NUM
cana-3460	85	2	logistic	logistic	ADJ
cana-3460	85	3	regression	regression	NOUN
cana-3460	85	4	(	(	PUNCT
cana-3460	85	5	lr	lr	NOUN
cana-3460	85	6	)	)	PUNCT
cana-3460	85	7	logistic	logistic	ADJ
cana-3460	85	8	regression	regression	NOUN
cana-3460	85	9	is	be	AUX
cana-3460	85	10	a	a	DET
cana-3460	85	11	base	base	ADJ
cana-3460	85	12	machine	machine	NOUN
cana-3460	85	13	learning	learn	VERB
cana-3460	85	14	algorithm	algorithm	NOUN
cana-3460	85	15	for	for	ADP
cana-3460	85	16	binary	binary	ADJ
cana-3460	85	17	classification	classification	NOUN
cana-3460	85	18	.	.	PUNCT
cana-3460	86	1	for	for	ADP
cana-3460	86	2	sentiment	sentiment	NOUN
cana-3460	86	3	analysis	analysis	NOUN
cana-3460	86	4	,	,	PUNCT
cana-3460	86	5	this	this	DET
cana-3460	86	6	algorithm	algorithm	NOUN
cana-3460	86	7	is	be	AUX
cana-3460	86	8	used	use	VERB
cana-3460	86	9	to	to	PART
cana-3460	86	10	classify	classify	VERB
cana-3460	86	11	whether	whether	SCONJ
cana-3460	86	12	a	a	DET
cana-3460	86	13	given	give	VERB
cana-3460	86	14	text	text	NOUN
cana-3460	86	15	(	(	PUNCT
cana-3460	86	16	or	or	CCONJ
cana-3460	86	17	tweet	tweet	NOUN
cana-3460	86	18	)	)	PUNCT
cana-3460	86	19	conveys	convey	VERB
cana-3460	86	20	a	a	DET
cana-3460	86	21	positive	positive	ADJ
cana-3460	86	22	or	or	CCONJ
cana-3460	86	23	negative	negative	ADJ
cana-3460	86	24	sentiment	sentiment	NOUN
cana-3460	86	25	.	.	PUNCT
cana-3460	87	1	it	it	PRON
cana-3460	87	2	learns	learn	VERB
cana-3460	87	3	the	the	DET
cana-3460	87	4	relationship	relationship	NOUN
cana-3460	87	5	between	between	ADP
cana-3460	87	6	the	the	DET
cana-3460	87	7	features	feature	NOUN
cana-3460	87	8	that	that	PRON
cana-3460	87	9	have	have	AUX
cana-3460	87	10	been	be	AUX
cana-3460	87	11	derived	derive	VERB
cana-3460	87	12	from	from	ADP
cana-3460	87	13	the	the	DET
cana-3460	87	14	text	text	NOUN
cana-3460	87	15	,	,	PUNCT
cana-3460	87	16	including	include	VERB
cana-3460	87	17	word	word	NOUN
cana-3460	87	18	counts	count	NOUN
cana-3460	87	19	or	or	CCONJ
cana-3460	87	20	tf	tf	ADJ
cana-3460	87	21	-	-	PUNCT
cana-3460	87	22	idf	idf	PROPN
cana-3460	87	23	values	value	NOUN
cana-3460	87	24	,	,	PUNCT
cana-3460	87	25	and	and	CCONJ
cana-3460	87	26	the	the	DET
cana-3460	87	27	target	target	NOUN
cana-3460	87	28	label	label	NOUN
cana-3460	87	29	of	of	ADP
cana-3460	87	30	the	the	DET
cana-3460	87	31	sentiment	sentiment	NOUN
cana-3460	87	32	being	be	AUX
cana-3460	87	33	positive	positive	ADJ
cana-3460	87	34	or	or	CCONJ
cana-3460	87	35	negative	negative	ADJ
cana-3460	87	36	.	.	PUNCT
cana-3460	88	1	the	the	DET
cana-3460	88	2	logistic	logistic	ADJ
cana-3460	88	3	function	function	NOUN
cana-3460	88	4	maps	map	VERB
cana-3460	88	5	the	the	DET
cana-3460	88	6	predicted	predict	VERB
cana-3460	88	7	values	value	NOUN
cana-3460	88	8	to	to	ADP
cana-3460	88	9	probabilities	probability	NOUN
cana-3460	88	10	.	.	PUNCT
cana-3460	89	1	outputs	output	NOUN
cana-3460	89	2	close	close	ADV
cana-3460	89	3	to	to	ADP
cana-3460	89	4	0	0	NUM
cana-3460	89	5	indicate	indicate	VERB
cana-3460	89	6	negative	negative	ADJ
cana-3460	89	7	sentiment	sentiment	NOUN
cana-3460	89	8	,	,	PUNCT
cana-3460	89	9	and	and	CCONJ
cana-3460	89	10	outputs	output	NOUN
cana-3460	89	11	close	close	ADJ
cana-3460	89	12	to	to	PART
cana-3460	89	13	1	1	NUM
cana-3460	89	14	indicate	indicate	VERB
cana-3460	89	15	positive	positive	ADJ
cana-3460	89	16	sentiment	sentiment	NOUN
cana-3460	89	17	[	[	X
cana-3460	89	18	7	7	NUM
cana-3460	89	19	]	]	PUNCT
cana-3460	89	20	.	.	PUNCT
cana-3460	90	1	the	the	DET
cana-3460	90	2	algorithm	algorithm	NOUN
cana-3460	90	3	is	be	AUX
cana-3460	90	4	simple	simple	ADJ
cana-3460	90	5	,	,	PUNCT
cana-3460	90	6	interpretable	interpretable	ADJ
cana-3460	90	7	,	,	PUNCT
cana-3460	90	8	and	and	CCONJ
cana-3460	90	9	efficient	efficient	ADJ
cana-3460	90	10	in	in	ADP
cana-3460	90	11	terms	term	NOUN
cana-3460	90	12	of	of	ADP
cana-3460	90	13	computational	computational	ADJ
cana-3460	90	14	resources	resource	NOUN
cana-3460	90	15	.	.	PUNCT
cana-3460	91	1	however	however	ADV
cana-3460	91	2	,	,	PUNCT
cana-3460	91	3	it	it	PRON
cana-3460	91	4	may	may	AUX
cana-3460	91	5	face	face	VERB
cana-3460	91	6	challenges	challenge	NOUN
cana-3460	91	7	with	with	ADP
cana-3460	91	8	complex	complex	ADJ
cana-3460	91	9	datasets	dataset	NOUN
cana-3460	91	10	or	or	CCONJ
cana-3460	91	11	those	those	PRON
cana-3460	91	12	that	that	PRON
cana-3460	91	13	contain	contain	VERB
cana-3460	91	14	non	non	ADJ
cana-3460	91	15	-	-	ADJ
cana-3460	91	16	linear	linear	ADJ
cana-3460	91	17	relationships	relationship	NOUN
cana-3460	91	18	.	.	PUNCT
cana-3460	92	1	in	in	ADP
cana-3460	92	2	this	this	DET
cana-3460	92	3	study	study	NOUN
cana-3460	92	4	,	,	PUNCT
cana-3460	92	5	logistic	logistic	ADJ
cana-3460	92	6	regression	regression	NOUN
cana-3460	92	7	is	be	AUX
cana-3460	92	8	implemented	implement	VERB
cana-3460	92	9	using	use	VERB
cana-3460	92	10	features	feature	NOUN
cana-3460	92	11	like	like	ADP
cana-3460	92	12	term	term	NOUN
cana-3460	92	13	frequency	frequency	NOUN
cana-3460	92	14	-	-	PUNCT
cana-3460	92	15	inverse	inverse	NOUN
cana-3460	92	16	document	document	NOUN
cana-3460	92	17	frequency	frequency	NOUN
cana-3460	92	18	(	(	PUNCT
cana-3460	92	19	tf	tf	PROPN
cana-3460	92	20	-	-	PUNCT
cana-3460	92	21	idf	idf	PROPN
cana-3460	92	22	)	)	PUNCT
cana-3460	92	23	for	for	ADP
cana-3460	92	24	transforming	transform	VERB
cana-3460	92	25	textual	textual	ADJ
cana-3460	92	26	data	datum	NOUN
cana-3460	92	27	into	into	ADP
cana-3460	92	28	a	a	DET
cana-3460	92	29	numerical	numerical	ADJ
cana-3460	92	30	format	format	NOUN
cana-3460	92	31	.	.	PUNCT
cana-3460	93	1	algorithm	algorithm	PROPN
cana-3460	93	2	pseudocode	pseudocode	PROPN
cana-3460	93	3	for	for	ADP
cana-3460	93	4	logistic	logistic	ADJ
cana-3460	93	5	regression	regression	NOUN
cana-3460	93	6	:	:	PUNCT
cana-3460	93	7	“	"	PUNCT
cana-3460	93	8	1	1	X
cana-3460	93	9	.	.	X
cana-3460	93	10	initialize	initialize	VERB
cana-3460	93	11	logistic	logistic	ADJ
cana-3460	93	12	regression	regression	NOUN
cana-3460	93	13	model	model	NOUN
cana-3460	93	14	2	2	NUM
cana-3460	93	15	.	.	PUNCT
cana-3460	93	16	preprocess	preprocess	NOUN
cana-3460	93	17	data	datum	NOUN
cana-3460	93	18	(	(	PUNCT
cana-3460	93	19	remove	remove	VERB
cana-3460	93	20	noise	noise	NOUN
cana-3460	93	21	,	,	PUNCT
cana-3460	93	22	tokenize	tokenize	NOUN
cana-3460	93	23	)	)	PUNCT
cana-3460	93	24	3	3	NUM
cana-3460	93	25	.	.	X
cana-3460	93	26	convert	convert	VERB
cana-3460	93	27	text	text	NOUN
cana-3460	93	28	into	into	ADP
cana-3460	93	29	numerical	numerical	ADJ
cana-3460	93	30	features	feature	NOUN
cana-3460	93	31	(	(	PUNCT
cana-3460	93	32	tf	tf	NOUN
cana-3460	93	33	-	-	PUNCT
cana-3460	93	34	idf	idf	NOUN
cana-3460	93	35	)	)	PUNCT
cana-3460	93	36	4	4	NUM
cana-3460	93	37	.	.	X
cana-3460	93	38	split	split	NOUN
cana-3460	93	39	dataset	dataset	VERB
cana-3460	93	40	into	into	ADP
cana-3460	93	41	training	training	NOUN
cana-3460	93	42	and	and	CCONJ
cana-3460	93	43	testing	testing	NOUN
cana-3460	93	44	sets	set	NOUN
cana-3460	93	45	5	5	NUM
cana-3460	93	46	.	.	PUNCT
cana-3460	93	47	train	train	VERB
cana-3460	93	48	the	the	DET
cana-3460	93	49	model	model	NOUN
cana-3460	93	50	on	on	ADP
cana-3460	93	51	the	the	DET
cana-3460	93	52	training	training	NOUN
cana-3460	93	53	data	datum	NOUN
cana-3460	93	54	6	6	NUM
cana-3460	93	55	.	.	PUNCT
cana-3460	93	56	predict	predict	VERB
cana-3460	93	57	sentiment	sentiment	NOUN
cana-3460	93	58	on	on	ADP
cana-3460	93	59	the	the	DET
cana-3460	93	60	test	test	NOUN
cana-3460	93	61	data	datum	NOUN
cana-3460	93	62	7	7	NUM
cana-3460	93	63	.	.	PUNCT
cana-3460	93	64	evaluate	evaluate	VERB
cana-3460	93	65	model	model	NOUN
cana-3460	93	66	performance	performance	NOUN
cana-3460	93	67	using	use	VERB
cana-3460	93	68	accuracy	accuracy	NOUN
cana-3460	93	69	,	,	PUNCT
cana-3460	93	70	precision	precision	NOUN
cana-3460	93	71	,	,	PUNCT
cana-3460	93	72	recall	recall	NOUN
cana-3460	93	73	,	,	PUNCT
cana-3460	93	74	f1	f1	ADJ
cana-3460	93	75	-	-	PUNCT
cana-3460	93	76	score	score	NOUN
cana-3460	93	77	”	"	PUNCT
cana-3460	93	78	key	key	ADJ
cana-3460	93	79	hyperparameters	hyperparameter	NOUN
cana-3460	93	80	:	:	PUNCT
cana-3460	93	81	●	●	PUNCT
cana-3460	93	82	c	c	NOUN
cana-3460	93	83	(	(	PUNCT
cana-3460	93	84	regularization	regularization	NOUN
cana-3460	93	85	strength	strength	NOUN
cana-3460	93	86	):	):	PUNCT
cana-3460	93	87	1.0	1.0	NUM
cana-3460	93	88	●	●	NUM
cana-3460	93	89	solver	solver	NOUN
cana-3460	93	90	:	:	PUNCT
cana-3460	93	91	'	'	PUNCT
cana-3460	93	92	liblinear	liblinear	ADJ
cana-3460	93	93	'	'	PUNCT
cana-3460	93	94	●	●	NUM
cana-3460	93	95	max	max	PROPN
cana-3460	93	96	iterations	iteration	NOUN
cana-3460	93	97	:	:	PUNCT
cana-3460	93	98	100	100	NUM
cana-3460	93	99	communications	communication	NOUN
cana-3460	93	100	on	on	ADP
cana-3460	93	101	applied	apply	VERB
cana-3460	93	102	nonlinear	nonlinear	ADJ
cana-3460	93	103	analysis	analysis	NOUN
cana-3460	93	104	issn	issn	NOUN
cana-3460	93	105	:	:	PUNCT
cana-3460	93	106	1074	1074	NUM
cana-3460	93	107	-	-	PUNCT
cana-3460	93	108	133x	133x	NUM
cana-3460	93	109	vol	vol	NOUN
cana-3460	93	110	32	32	NUM
cana-3460	93	111	no	no	NOUN
cana-3460	93	112	.	.	PUNCT
cana-3460	94	1	7s	7	NOUN
cana-3460	94	2	(	(	PUNCT
cana-3460	94	3	2025	2025	NUM
cana-3460	94	4	)	)	PUNCT
cana-3460	94	5	508	508	NUM
cana-3460	94	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3460	94	7	logistic	logistic	ADJ
cana-3460	94	8	regression	regression	NOUN
cana-3460	94	9	hyperparameter	hyperparameter	NOUN
cana-3460	94	10	table	table	NOUN
cana-3460	94	11	:	:	PUNCT
cana-3460	94	12	hyperparameter	hyperparameter	NOUN
cana-3460	94	13	value	value	NOUN
cana-3460	94	14	regularization	regularization	NOUN
cana-3460	94	15	c	c	PROPN
cana-3460	94	16	1.0	1.0	NUM
cana-3460	94	17	solver	solver	ADV
cana-3460	94	18	liblinear	liblinear	PROPN
cana-3460	94	19	max	max	PROPN
cana-3460	94	20	iterations	iteration	NOUN
cana-3460	94	21	100	100	NUM
cana-3460	94	22	penalty	penalty	NOUN
cana-3460	94	23	l2	l2	NOUN
cana-3460	94	24	2.2	2.2	NUM
cana-3460	94	25	“	"	PUNCT
cana-3460	94	26	support	support	NOUN
cana-3460	94	27	vector	vector	NOUN
cana-3460	94	28	machine	machine	NOUN
cana-3460	94	29	(	(	PUNCT
cana-3460	94	30	svm	svm	PROPN
cana-3460	94	31	)	)	PUNCT
cana-3460	94	32	”	"	PUNCT
cana-3460	94	33	svm	svm	PROPN
cana-3460	94	34	is	be	AUX
cana-3460	94	35	one	one	NUM
cana-3460	94	36	of	of	ADP
cana-3460	94	37	the	the	DET
cana-3460	94	38	most	most	ADV
cana-3460	94	39	commonly	commonly	ADV
cana-3460	94	40	used	use	VERB
cana-3460	94	41	algorithms	algorithm	NOUN
cana-3460	94	42	in	in	ADP
cana-3460	94	43	supervised	supervised	ADJ
cana-3460	94	44	machine	machine	NOUN
cana-3460	94	45	learning	learning	NOUN
cana-3460	94	46	algorithms	algorithm	NOUN
cana-3460	94	47	used	use	VERB
cana-3460	94	48	for	for	ADP
cana-3460	94	49	classification	classification	NOUN
cana-3460	94	50	purposes	purpose	NOUN
cana-3460	94	51	.	.	PUNCT
cana-3460	95	1	its	its	PRON
cana-3460	95	2	core	core	ADJ
cana-3460	95	3	idea	idea	NOUN
cana-3460	95	4	is	be	AUX
cana-3460	95	5	based	base	VERB
cana-3460	95	6	on	on	ADP
cana-3460	95	7	identifying	identify	VERB
cana-3460	95	8	a	a	DET
cana-3460	95	9	hyperplane	hyperplane	NOUN
cana-3460	95	10	which	which	PRON
cana-3460	95	11	should	should	AUX
cana-3460	95	12	better	well	ADV
cana-3460	95	13	separate	separate	VERB
cana-3460	95	14	the	the	DET
cana-3460	95	15	points	point	NOUN
cana-3460	95	16	in	in	ADP
cana-3460	95	17	other	other	ADJ
cana-3460	95	18	classes	class	NOUN
cana-3460	95	19	.	.	PUNCT
cana-3460	96	1	for	for	ADP
cana-3460	96	2	instance	instance	NOUN
cana-3460	96	3	,	,	PUNCT
cana-3460	96	4	while	while	SCONJ
cana-3460	96	5	trying	try	VERB
cana-3460	96	6	to	to	PART
cana-3460	96	7	identify	identify	VERB
cana-3460	96	8	sentiment	sentiment	NOUN
cana-3460	96	9	words	word	NOUN
cana-3460	96	10	or	or	CCONJ
cana-3460	96	11	phrases	phrase	NOUN
cana-3460	96	12	,	,	PUNCT
cana-3460	96	13	this	this	PRON
cana-3460	96	14	works	work	VERB
cana-3460	96	15	quite	quite	ADV
cana-3460	96	16	well	well	ADV
cana-3460	96	17	with	with	ADP
cana-3460	96	18	a	a	DET
cana-3460	96	19	higher	high	ADJ
cana-3460	96	20	dimensionality	dimensionality	NOUN
cana-3460	96	21	of	of	ADP
cana-3460	96	22	spaces	space	NOUN
cana-3460	96	23	and	and	CCONJ
cana-3460	96	24	using	use	VERB
cana-3460	96	25	textual	textual	ADJ
cana-3460	96	26	features	feature	NOUN
cana-3460	96	27	,	,	PUNCT
cana-3460	96	28	tf	tf	PROPN
cana-3460	96	29	-	-	PUNCT
cana-3460	96	30	idf	idf	PROPN
cana-3460	96	31	,	,	PUNCT
cana-3460	96	32	it	it	PRON
cana-3460	96	33	performed	perform	VERB
cana-3460	96	34	really	really	ADV
cana-3460	96	35	well	well	ADV
cana-3460	97	1	[	[	X
cana-3460	97	2	8	8	NUM
cana-3460	97	3	]	]	PUNCT
cana-3460	97	4	.	.	PUNCT
cana-3460	98	1	using	use	VERB
cana-3460	98	2	a	a	DET
cana-3460	98	3	kernel	kernel	NOUN
cana-3460	98	4	trick	trick	NOUN
cana-3460	98	5	,	,	PUNCT
cana-3460	98	6	the	the	DET
cana-3460	98	7	non	non	ADJ
cana-3460	98	8	-	-	ADJ
cana-3460	98	9	linear	linear	ADJ
cana-3460	98	10	svm	svm	NOUN
cana-3460	98	11	allows	allow	VERB
cana-3460	98	12	classification	classification	NOUN
cana-3460	98	13	by	by	ADP
cana-3460	98	14	transforming	transform	VERB
cana-3460	98	15	input	input	NOUN
cana-3460	98	16	features	feature	NOUN
cana-3460	98	17	to	to	ADP
cana-3460	98	18	higher	higher	ADV
cana-3460	98	19	-	-	PUNCT
cana-3460	98	20	dimensional	dimensional	ADJ
cana-3460	98	21	spaces	space	NOUN
cana-3460	98	22	.	.	PUNCT
cana-3460	99	1	svm	svm	PROPN
cana-3460	99	2	has	have	AUX
cana-3460	99	3	been	be	AUX
cana-3460	99	4	highly	highly	ADV
cana-3460	99	5	effective	effective	ADJ
cana-3460	99	6	in	in	ADP
cana-3460	99	7	sentiment	sentiment	NOUN
cana-3460	99	8	analysis	analysis	NOUN
cana-3460	99	9	,	,	PUNCT
cana-3460	99	10	as	as	SCONJ
cana-3460	99	11	its	its	PRON
cana-3460	99	12	goal	goal	NOUN
cana-3460	99	13	is	be	AUX
cana-3460	99	14	maximizing	maximize	VERB
cana-3460	99	15	the	the	DET
cana-3460	99	16	margins	margin	NOUN
cana-3460	99	17	between	between	ADP
cana-3460	99	18	classes	class	NOUN
cana-3460	99	19	for	for	ADP
cana-3460	99	20	enhanced	enhanced	ADJ
cana-3460	99	21	generalization	generalization	NOUN
cana-3460	99	22	.	.	PUNCT
cana-3460	100	1	in	in	ADP
cana-3460	100	2	this	this	DET
cana-3460	100	3	work	work	NOUN
cana-3460	100	4	,	,	PUNCT
cana-3460	100	5	a	a	DET
cana-3460	100	6	linear	linear	ADJ
cana-3460	100	7	kernel	kernel	NOUN
cana-3460	100	8	svm	svm	PROPN
cana-3460	100	9	was	be	AUX
cana-3460	100	10	adopted	adopt	VERB
cana-3460	100	11	to	to	PART
cana-3460	100	12	categorize	categorize	VERB
cana-3460	100	13	the	the	DET
cana-3460	100	14	three	three	NUM
cana-3460	100	15	classes	class	NOUN
cana-3460	100	16	:	:	PUNCT
cana-3460	100	17	positive	positive	ADJ
cana-3460	100	18	,	,	PUNCT
cana-3460	100	19	negative	negative	ADJ
cana-3460	100	20	,	,	PUNCT
cana-3460	100	21	and	and	CCONJ
cana-3460	100	22	neutral	neutral	ADJ
cana-3460	100	23	sentiments	sentiment	NOUN
cana-3460	100	24	within	within	ADP
cana-3460	100	25	the	the	DET
cana-3460	100	26	tweets	tweet	NOUN
cana-3460	100	27	.	.	PUNCT
cana-3460	101	1	hyper	hyper	NOUN
cana-3460	101	2	-	-	NOUN
cana-3460	101	3	parameters	parameter	NOUN
cana-3460	101	4	including	include	VERB
cana-3460	101	5	c	c	PROPN
cana-3460	101	6	,	,	PUNCT
cana-3460	101	7	a	a	DET
cana-3460	101	8	penalty	penalty	NOUN
cana-3460	101	9	factor	factor	NOUN
cana-3460	101	10	,	,	PUNCT
cana-3460	101	11	and	and	CCONJ
cana-3460	101	12	gamma	gamma	NOUN
cana-3460	101	13	were	be	AUX
cana-3460	101	14	found	find	VERB
cana-3460	101	15	using	use	VERB
cana-3460	101	16	grid	grid	NOUN
cana-3460	101	17	search	search	NOUN
cana-3460	101	18	to	to	PART
cana-3460	101	19	attain	attain	VERB
cana-3460	101	20	optimal	optimal	ADJ
cana-3460	101	21	performance	performance	NOUN
cana-3460	101	22	.	.	PUNCT
cana-3460	102	1	“	"	PUNCT
cana-3460	102	2	key	key	ADJ
cana-3460	102	3	hyperparameters	hyperparameter	NOUN
cana-3460	102	4	:	:	PUNCT
cana-3460	102	5	●	●	PUNCT
cana-3460	102	6	c	c	NOUN
cana-3460	102	7	(	(	PUNCT
cana-3460	102	8	regularization	regularization	NOUN
cana-3460	102	9	):	):	PUNCT
cana-3460	102	10	10	10	NUM
cana-3460	102	11	●	●	NUM
cana-3460	102	12	kernel	kernel	NOUN
cana-3460	102	13	:	:	PUNCT
cana-3460	102	14	'	'	PUNCT
cana-3460	102	15	linear	linear	ADJ
cana-3460	102	16	'	'	PUNCT
cana-3460	102	17	●	●	NOUN
cana-3460	102	18	gamma	gamma	NOUN
cana-3460	102	19	:	:	PUNCT
cana-3460	102	20	'	'	PUNCT
cana-3460	102	21	scale	scale	NOUN
cana-3460	102	22	'	'	PUNCT
cana-3460	102	23	”	"	PUNCT
cana-3460	102	24	support	support	NOUN
cana-3460	102	25	vector	vector	NOUN
cana-3460	102	26	machine	machine	NOUN
cana-3460	102	27	hyperparameter	hyperparameter	NOUN
cana-3460	102	28	table	table	NOUN
cana-3460	102	29	:	:	PUNCT
cana-3460	102	30	hyperparameter	hyperparameter	NOUN
cana-3460	102	31	value	value	NOUN
cana-3460	102	32	regularization	regularization	NOUN
cana-3460	102	33	c	c	PROPN
cana-3460	102	34	10	10	NUM
cana-3460	102	35	kernel	kernel	PROPN
cana-3460	102	36	linear	linear	PROPN
cana-3460	102	37	gamma	gamma	PROPN
cana-3460	102	38	scale	scale	NOUN
cana-3460	102	39	decision	decision	NOUN
cana-3460	102	40	function	function	VERB
cana-3460	102	41	true	true	ADJ
cana-3460	102	42	“	"	PUNCT
cana-3460	102	43	1	1	NUM
cana-3460	102	44	.	.	PUNCT
cana-3460	102	45	initialize	initialize	VERB
cana-3460	102	46	svm	svm	ADJ
cana-3460	102	47	model	model	NOUN
cana-3460	102	48	with	with	ADP
cana-3460	102	49	a	a	DET
cana-3460	102	50	linear	linear	ADJ
cana-3460	102	51	kernel	kernel	NOUN
cana-3460	102	52	2	2	X
cana-3460	102	53	.	.	PUNCT
cana-3460	102	54	preprocess	preprocess	NOUN
cana-3460	102	55	data	datum	NOUN
cana-3460	102	56	(	(	PUNCT
cana-3460	102	57	remove	remove	VERB
cana-3460	102	58	noise	noise	NOUN
cana-3460	102	59	,	,	PUNCT
cana-3460	102	60	tokenize	tokenize	NOUN
cana-3460	102	61	)	)	PUNCT
cana-3460	102	62	3	3	NUM
cana-3460	102	63	.	.	X
cana-3460	102	64	convert	convert	VERB
cana-3460	102	65	text	text	NOUN
cana-3460	102	66	into	into	ADP
cana-3460	102	67	numerical	numerical	ADJ
cana-3460	102	68	features	feature	NOUN
cana-3460	102	69	(	(	PUNCT
cana-3460	102	70	tf	tf	NOUN
cana-3460	102	71	-	-	PUNCT
cana-3460	102	72	idf	idf	NOUN
cana-3460	102	73	)	)	PUNCT
cana-3460	102	74	4	4	NUM
cana-3460	102	75	.	.	X
cana-3460	102	76	split	split	NOUN
cana-3460	102	77	dataset	dataset	VERB
cana-3460	102	78	into	into	ADP
cana-3460	102	79	training	training	NOUN
cana-3460	102	80	and	and	CCONJ
cana-3460	102	81	testing	testing	NOUN
cana-3460	102	82	sets	set	NOUN
cana-3460	102	83	5	5	NUM
cana-3460	102	84	.	.	PUNCT
cana-3460	103	1	train	train	VERB
cana-3460	103	2	the	the	DET
cana-3460	103	3	model	model	NOUN
cana-3460	103	4	on	on	ADP
cana-3460	103	5	the	the	DET
cana-3460	103	6	training	training	NOUN
cana-3460	103	7	data	data	NOUN
cana-3460	103	8	communications	communication	NOUN
cana-3460	103	9	on	on	ADP
cana-3460	103	10	applied	apply	VERB
cana-3460	103	11	nonlinear	nonlinear	ADJ
cana-3460	103	12	analysis	analysis	NOUN
cana-3460	103	13	issn	issn	NOUN
cana-3460	103	14	:	:	PUNCT
cana-3460	103	15	1074	1074	NUM
cana-3460	103	16	-	-	PUNCT
cana-3460	103	17	133x	133x	NUM
cana-3460	103	18	vol	vol	NOUN
cana-3460	103	19	32	32	NUM
cana-3460	103	20	no	no	NOUN
cana-3460	103	21	.	.	PUNCT
cana-3460	104	1	7s	7	NOUN
cana-3460	104	2	(	(	PUNCT
cana-3460	104	3	2025	2025	NUM
cana-3460	104	4	)	)	PUNCT
cana-3460	104	5	509	509	NUM
cana-3460	104	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3460	104	7	6	6	NUM
cana-3460	104	8	.	.	PUNCT
cana-3460	105	1	tune	tune	NOUN
cana-3460	105	2	hyperparameters	hyperparameter	NOUN
cana-3460	105	3	using	use	VERB
cana-3460	105	4	grid	grid	NOUN
cana-3460	105	5	search	search	NOUN
cana-3460	105	6	(	(	PUNCT
cana-3460	105	7	c	c	NOUN
cana-3460	105	8	,	,	PUNCT
cana-3460	105	9	gamma	gamma	NOUN
cana-3460	105	10	)	)	PUNCT
cana-3460	105	11	7	7	NUM
cana-3460	105	12	.	.	NOUN
cana-3460	105	13	predict	predict	VERB
cana-3460	105	14	sentiment	sentiment	NOUN
cana-3460	105	15	on	on	ADP
cana-3460	105	16	the	the	DET
cana-3460	105	17	test	test	NOUN
cana-3460	105	18	data	datum	NOUN
cana-3460	105	19	8	8	NUM
cana-3460	105	20	.	.	PUNCT
cana-3460	105	21	evaluate	evaluate	VERB
cana-3460	105	22	model	model	NOUN
cana-3460	105	23	performance	performance	NOUN
cana-3460	105	24	using	use	VERB
cana-3460	105	25	accuracy	accuracy	NOUN
cana-3460	105	26	,	,	PUNCT
cana-3460	105	27	precision	precision	NOUN
cana-3460	105	28	,	,	PUNCT
cana-3460	105	29	recall	recall	NOUN
cana-3460	105	30	,	,	PUNCT
cana-3460	105	31	f1	f1	NOUN
cana-3460	105	32	-	-	PUNCT
cana-3460	105	33	score	score	NOUN
cana-3460	105	34	”	"	PUNCT
cana-3460	105	35	2.3	2.3	NUM
cana-3460	105	36	“	"	PUNCT
cana-3460	105	37	bidirectional	bidirectional	ADJ
cana-3460	105	38	encoder	encoder	NOUN
cana-3460	105	39	representations	representation	VERB
cana-3460	105	40	from	from	ADP
cana-3460	105	41	transformers	transformer	NOUN
cana-3460	105	42	(	(	PUNCT
cana-3460	105	43	bert	bert	PROPN
cana-3460	105	44	)	)	PUNCT
cana-3460	105	45	”	"	PUNCT
cana-3460	105	46	bert	bert	PROPN
cana-3460	105	47	(	(	PUNCT
cana-3460	105	48	bidirectional	bidirectional	ADJ
cana-3460	105	49	encoder	encoder	NOUN
cana-3460	105	50	representations	representation	VERB
cana-3460	105	51	from	from	ADP
cana-3460	105	52	transformers	transformer	NOUN
cana-3460	105	53	)	)	PUNCT
cana-3460	105	54	is	be	AUX
cana-3460	105	55	one	one	NUM
cana-3460	105	56	of	of	ADP
cana-3460	105	57	the	the	DET
cana-3460	105	58	leading	lead	VERB
cana-3460	105	59	deep	deep	ADJ
cana-3460	105	60	learning	learning	NOUN
cana-3460	105	61	models	model	NOUN
cana-3460	105	62	to	to	PART
cana-3460	105	63	perform	perform	VERB
cana-3460	105	64	a	a	DET
cana-3460	105	65	broad	broad	ADJ
cana-3460	105	66	set	set	NOUN
cana-3460	105	67	of	of	ADP
cana-3460	105	68	nlp	nlp	NOUN
cana-3460	105	69	tasks	task	NOUN
cana-3460	105	70	.	.	PUNCT
cana-3460	106	1	unlike	unlike	ADP
cana-3460	106	2	earlier	early	ADJ
cana-3460	106	3	models	model	NOUN
cana-3460	106	4	,	,	PUNCT
cana-3460	106	5	words	word	NOUN
cana-3460	106	6	are	be	AUX
cana-3460	106	7	taken	take	VERB
cana-3460	106	8	into	into	ADP
cana-3460	106	9	consideration	consideration	NOUN
cana-3460	106	10	with	with	ADP
cana-3460	106	11	the	the	DET
cana-3460	106	12	presence	presence	NOUN
cana-3460	106	13	of	of	ADP
cana-3460	106	14	their	their	PRON
cana-3460	106	15	previous	previous	ADJ
cana-3460	106	16	and	and	CCONJ
cana-3460	106	17	following	follow	VERB
cana-3460	106	18	words	word	NOUN
cana-3460	106	19	for	for	ADP
cana-3460	106	20	processing	processing	NOUN
cana-3460	106	21	in	in	ADP
cana-3460	106	22	the	the	DET
cana-3460	106	23	context	context	NOUN
cana-3460	106	24	of	of	ADP
cana-3460	106	25	bidirectional	bidirectional	ADJ
cana-3460	106	26	information	information	NOUN
cana-3460	106	27	capture	capture	NOUN
cana-3460	106	28	[	[	X
cana-3460	106	29	9	9	NUM
cana-3460	106	30	]	]	PUNCT
cana-3460	106	31	.	.	PUNCT
cana-3460	107	1	for	for	ADP
cana-3460	107	2	sentiment	sentiment	NOUN
cana-3460	107	3	analysis	analysis	NOUN
cana-3460	107	4	,	,	PUNCT
cana-3460	107	5	the	the	DET
cana-3460	107	6	large	large	ADJ
cana-3460	107	7	corpus	corpus	NOUN
cana-3460	107	8	of	of	ADP
cana-3460	107	9	text	text	NOUN
cana-3460	107	10	is	be	AUX
cana-3460	107	11	first	first	ADV
cana-3460	107	12	pre	pre	ADJ
cana-3460	107	13	-	-	VERB
cana-3460	107	14	trained	train	VERB
cana-3460	107	15	using	use	VERB
cana-3460	107	16	bert	bert	NOUN
cana-3460	107	17	,	,	PUNCT
cana-3460	107	18	and	and	CCONJ
cana-3460	107	19	then	then	ADV
cana-3460	107	20	it	it	PRON
cana-3460	107	21	's	be	AUX
cana-3460	107	22	fine	fine	ADV
cana-3460	107	23	-	-	PUNCT
cana-3460	107	24	tuned	tune	VERB
cana-3460	107	25	on	on	ADP
cana-3460	107	26	the	the	DET
cana-3460	107	27	dataset	dataset	NOUN
cana-3460	107	28	of	of	ADP
cana-3460	107	29	labeled	label	VERB
cana-3460	107	30	sentiment	sentiment	NOUN
cana-3460	107	31	.	.	PUNCT
cana-3460	108	1	bert	bert	PROPN
cana-3460	108	2	is	be	AUX
cana-3460	108	3	one	one	NUM
cana-3460	108	4	of	of	ADP
cana-3460	108	5	the	the	DET
cana-3460	108	6	most	most	ADV
cana-3460	108	7	influential	influential	ADJ
cana-3460	108	8	models	model	NOUN
cana-3460	108	9	for	for	ADP
cana-3460	108	10	sentiment	sentiment	NOUN
cana-3460	108	11	analysis	analysis	NOUN
cana-3460	108	12	and	and	CCONJ
cana-3460	108	13	can	can	AUX
cana-3460	108	14	handle	handle	VERB
cana-3460	108	15	contextual	contextual	ADJ
cana-3460	108	16	relationships	relationship	NOUN
cana-3460	108	17	due	due	ADP
cana-3460	108	18	to	to	ADP
cana-3460	108	19	its	its	PRON
cana-3460	108	20	large	large	ADJ
cana-3460	108	21	capacity	capacity	NOUN
cana-3460	108	22	.	.	PUNCT
cana-3460	109	1	in	in	ADP
cana-3460	109	2	this	this	DET
cana-3460	109	3	research	research	NOUN
cana-3460	109	4	,	,	PUNCT
cana-3460	109	5	bert	bert	PROPN
cana-3460	109	6	is	be	AUX
cana-3460	109	7	fine	fine	ADV
cana-3460	109	8	-	-	PUNCT
cana-3460	109	9	tuned	tune	VERB
cana-3460	109	10	on	on	ADP
cana-3460	109	11	the	the	DET
cana-3460	109	12	sentiment	sentiment	NOUN
cana-3460	109	13	-	-	PUNCT
cana-3460	109	14	labeled	label	VERB
cana-3460	109	15	twitter	twitter	NOUN
cana-3460	109	16	dataset	dataset	VERB
cana-3460	109	17	where	where	SCONJ
cana-3460	109	18	the	the	DET
cana-3460	109	19	tweets	tweet	NOUN
cana-3460	109	20	are	be	AUX
cana-3460	109	21	classified	classify	VERB
cana-3460	109	22	as	as	ADP
cana-3460	109	23	three	three	NUM
cana-3460	109	24	categories	category	NOUN
cana-3460	109	25	[	[	X
cana-3460	109	26	10	10	NUM
cana-3460	109	27	]	]	PUNCT
cana-3460	109	28	.	.	PUNCT
cana-3460	110	1	because	because	SCONJ
cana-3460	110	2	the	the	DET
cana-3460	110	3	architecture	architecture	NOUN
cana-3460	110	4	of	of	ADP
cana-3460	110	5	bert	bert	PROPN
cana-3460	110	6	is	be	AUX
cana-3460	110	7	complex	complex	ADJ
cana-3460	110	8	,	,	PUNCT
cana-3460	110	9	it	it	PRON
cana-3460	110	10	needs	need	VERB
cana-3460	110	11	strong	strong	ADJ
cana-3460	110	12	computational	computational	ADJ
cana-3460	110	13	resources	resource	NOUN
cana-3460	110	14	and	and	CCONJ
cana-3460	110	15	much	much	ADV
cana-3460	110	16	more	more	ADJ
cana-3460	110	17	time	time	NOUN
cana-3460	110	18	for	for	ADP
cana-3460	110	19	training	training	NOUN
cana-3460	110	20	,	,	PUNCT
cana-3460	110	21	however	however	ADV
cana-3460	110	22	,	,	PUNCT
cana-3460	110	23	it	it	PRON
cana-3460	110	24	has	have	VERB
cana-3460	110	25	a	a	DET
cana-3460	110	26	much	much	ADV
cana-3460	110	27	higher	high	ADJ
cana-3460	110	28	accuracy	accuracy	NOUN
cana-3460	110	29	in	in	ADP
cana-3460	110	30	predicting	predict	VERB
cana-3460	110	31	sentiments	sentiment	NOUN
cana-3460	110	32	.	.	PUNCT
cana-3460	111	1	key	key	ADJ
cana-3460	111	2	hyperparameters	hyperparameter	NOUN
cana-3460	111	3	:	:	PUNCT
cana-3460	111	4	●	●	NUM
cana-3460	111	5	batch	batch	NOUN
cana-3460	111	6	size	size	NOUN
cana-3460	111	7	:	:	PUNCT
cana-3460	111	8	32	32	NUM
cana-3460	111	9	●	●	NUM
cana-3460	111	10	learning	learning	NOUN
cana-3460	111	11	rate	rate	NOUN
cana-3460	111	12	:	:	PUNCT
cana-3460	111	13	2e-5	2e-5	NUM
cana-3460	111	14	●	●	NUM
cana-3460	111	15	epochs	epoch	NOUN
cana-3460	111	16	:	:	PUNCT
cana-3460	111	17	3	3	NUM
cana-3460	111	18	●	●	NUM
cana-3460	111	19	max	max	NOUN
cana-3460	111	20	sequence	sequence	NOUN
cana-3460	111	21	length	length	NOUN
cana-3460	111	22	:	:	PUNCT
cana-3460	111	23	128	128	NUM
cana-3460	111	24	bert	bert	PROPN
cana-3460	111	25	hyperparameter	hyperparameter	NOUN
cana-3460	111	26	table	table	NOUN
cana-3460	111	27	:	:	PUNCT
cana-3460	111	28	hyperparameter	hyperparameter	NOUN
cana-3460	111	29	value	value	NOUN
cana-3460	111	30	batch	batch	NOUN
cana-3460	111	31	size	size	NOUN
cana-3460	111	32	32	32	NUM
cana-3460	111	33	learning	learning	NOUN
cana-3460	111	34	rate	rate	NOUN
cana-3460	111	35	2e-5	2e-5	NUM
cana-3460	111	36	epochs	epoch	NOUN
cana-3460	111	37	3	3	NUM
cana-3460	111	38	max	max	PROPN
cana-3460	111	39	sequence	sequence	NOUN
cana-3460	111	40	length	length	NOUN
cana-3460	111	41	128	128	NUM
cana-3460	111	42	“	"	PUNCT
cana-3460	111	43	1	1	NUM
cana-3460	111	44	.	.	X
cana-3460	111	45	initialize	initialize	VERB
cana-3460	111	46	pre	pre	ADJ
cana-3460	111	47	-	-	ADJ
cana-3460	111	48	trained	train	VERB
cana-3460	111	49	bert	bert	NOUN
cana-3460	111	50	model	model	NOUN
cana-3460	111	51	2	2	NUM
cana-3460	111	52	.	.	PUNCT
cana-3460	111	53	preprocess	preprocess	NOUN
cana-3460	111	54	data	datum	NOUN
cana-3460	111	55	(	(	PUNCT
cana-3460	111	56	tokenization	tokenization	NOUN
cana-3460	111	57	,	,	PUNCT
cana-3460	111	58	padding	padding	NOUN
cana-3460	111	59	)	)	PUNCT
cana-3460	111	60	3	3	NUM
cana-3460	111	61	.	.	X
cana-3460	111	62	fine	fine	ADJ
cana-3460	111	63	-	-	PUNCT
cana-3460	111	64	tune	tune	NOUN
cana-3460	111	65	bert	bert	NOUN
cana-3460	111	66	on	on	ADP
cana-3460	111	67	sentimentlabeled	sentimentlabeled	ADJ
cana-3460	111	68	dataset	dataset	ADJ
cana-3460	111	69	4	4	NUM
cana-3460	111	70	.	.	NOUN
cana-3460	111	71	split	split	NOUN
cana-3460	111	72	dataset	dataset	VERB
cana-3460	111	73	into	into	ADP
cana-3460	111	74	training	training	NOUN
cana-3460	111	75	and	and	CCONJ
cana-3460	111	76	testing	testing	NOUN
cana-3460	111	77	sets	set	VERB
cana-3460	111	78	communications	communication	NOUN
cana-3460	111	79	on	on	ADP
cana-3460	111	80	applied	apply	VERB
cana-3460	111	81	nonlinear	nonlinear	ADJ
cana-3460	111	82	analysis	analysis	NOUN
cana-3460	111	83	issn	issn	NOUN
cana-3460	111	84	:	:	PUNCT
cana-3460	111	85	1074	1074	NUM
cana-3460	111	86	-	-	PUNCT
cana-3460	111	87	133x	133x	NUM
cana-3460	111	88	vol	vol	NOUN
cana-3460	111	89	32	32	NUM
cana-3460	111	90	no	no	NOUN
cana-3460	111	91	.	.	PUNCT
cana-3460	112	1	7s	7	NOUN
cana-3460	112	2	(	(	PUNCT
cana-3460	112	3	2025	2025	NUM
cana-3460	112	4	)	)	PUNCT
cana-3460	112	5	510	510	NUM
cana-3460	112	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3460	112	7	5	5	NUM
cana-3460	112	8	.	.	PUNCT
cana-3460	112	9	train	train	VERB
cana-3460	112	10	the	the	DET
cana-3460	112	11	model	model	NOUN
cana-3460	112	12	on	on	ADP
cana-3460	112	13	the	the	DET
cana-3460	112	14	training	training	NOUN
cana-3460	112	15	data	datum	NOUN
cana-3460	112	16	6	6	NUM
cana-3460	112	17	.	.	PUNCT
cana-3460	113	1	predict	predict	VERB
cana-3460	113	2	sentiment	sentiment	NOUN
cana-3460	113	3	on	on	ADP
cana-3460	113	4	the	the	DET
cana-3460	113	5	test	test	NOUN
cana-3460	113	6	data	datum	NOUN
cana-3460	113	7	7	7	NUM
cana-3460	113	8	.	.	PUNCT
cana-3460	113	9	evaluate	evaluate	VERB
cana-3460	113	10	model	model	NOUN
cana-3460	113	11	performance	performance	NOUN
cana-3460	113	12	using	use	VERB
cana-3460	113	13	accuracy	accuracy	NOUN
cana-3460	113	14	,	,	PUNCT
cana-3460	113	15	precision	precision	NOUN
cana-3460	113	16	,	,	PUNCT
cana-3460	113	17	recall	recall	NOUN
cana-3460	113	18	,	,	PUNCT
cana-3460	113	19	f1	f1	NOUN
cana-3460	113	20	-	-	PUNCT
cana-3460	113	21	score	score	NOUN
cana-3460	113	22	”	"	PUNCT
cana-3460	113	23	3	3	NUM
cana-3460	113	24	.	.	PUNCT
cana-3460	113	25	confusion	confusion	NOUN
cana-3460	113	26	matrix	matrix	NOUN
cana-3460	113	27	an	an	DET
cana-3460	113	28	essential	essential	ADJ
cana-3460	113	29	tool	tool	NOUN
cana-3460	113	30	for	for	ADP
cana-3460	113	31	the	the	DET
cana-3460	113	32	evaluation	evaluation	NOUN
cana-3460	113	33	of	of	ADP
cana-3460	113	34	classification	classification	NOUN
cana-3460	113	35	models	model	NOUN
cana-3460	113	36	is	be	AUX
cana-3460	113	37	the	the	DET
cana-3460	113	38	confusion	confusion	NOUN
cana-3460	113	39	matrix	matrix	NOUN
cana-3460	113	40	.	.	PUNCT
cana-3460	114	1	it	it	PRON
cana-3460	114	2	summarizes	summarize	VERB
cana-3460	114	3	counts	count	NOUN
cana-3460	114	4	for	for	ADP
cana-3460	114	5	true	true	ADJ
cana-3460	114	6	positives	positive	NOUN
cana-3460	114	7	,	,	PUNCT
cana-3460	114	8	false	false	ADJ
cana-3460	114	9	positives	positive	NOUN
cana-3460	114	10	,	,	PUNCT
cana-3460	114	11	true	true	ADJ
cana-3460	114	12	negatives	negative	NOUN
cana-3460	114	13	,	,	PUNCT
cana-3460	114	14	and	and	CCONJ
cana-3460	114	15	false	false	ADJ
cana-3460	114	16	negatives	negative	NOUN
cana-3460	114	17	.	.	PUNCT
cana-3460	115	1	for	for	ADP
cana-3460	115	2	this	this	DET
cana-3460	115	3	research	research	NOUN
cana-3460	115	4	,	,	PUNCT
cana-3460	115	5	it	it	PRON
cana-3460	115	6	is	be	AUX
cana-3460	115	7	computed	compute	VERB
cana-3460	115	8	for	for	SCONJ
cana-3460	115	9	each	each	PRON
cana-3460	115	10	of	of	ADP
cana-3460	115	11	the	the	DET
cana-3460	115	12	three	three	NUM
cana-3460	115	13	models	model	NOUN
cana-3460	115	14	to	to	PART
cana-3460	115	15	better	well	ADV
cana-3460	115	16	understand	understand	VERB
cana-3460	115	17	how	how	SCONJ
cana-3460	115	18	well	well	ADV
cana-3460	115	19	they	they	PRON
cana-3460	115	20	performed	perform	VERB
cana-3460	115	21	with	with	ADP
cana-3460	115	22	regard	regard	NOUN
cana-3460	115	23	to	to	ADP
cana-3460	115	24	sentiment	sentiment	NOUN
cana-3460	115	25	classification	classification	NOUN
cana-3460	116	1	[	[	X
cana-3460	116	2	11	11	NUM
cana-3460	116	3	]	]	PUNCT
cana-3460	116	4	.	.	PUNCT
cana-3460	117	1	confusion	confusion	NOUN
cana-3460	117	2	matrix	matrix	NOUN
cana-3460	117	3	table	table	NOUN
cana-3460	117	4	(	(	PUNCT
cana-3460	117	5	logistic	logistic	ADJ
cana-3460	117	6	regression	regression	NOUN
cana-3460	117	7	):	):	PUNCT
cana-3460	117	8	actual	actual	ADJ
cana-3460	117	9	\	\	NOUN
cana-3460	117	10	predicted	predict	VERB
cana-3460	117	11	positive	positive	ADJ
cana-3460	117	12	negative	negative	ADJ
cana-3460	117	13	neutral	neutral	ADJ
cana-3460	117	14	positive	positive	ADJ
cana-3460	117	15	350	350	NUM
cana-3460	117	16	50	50	NUM
cana-3460	117	17	30	30	NUM
cana-3460	117	18	negative	negative	ADJ
cana-3460	117	19	40	40	NUM
cana-3460	117	20	400	400	NUM
cana-3460	117	21	60	60	NUM
cana-3460	117	22	neutral	neutral	ADJ
cana-3460	117	23	20	20	NUM
cana-3460	117	24	30	30	NUM
cana-3460	117	25	400	400	NUM
cana-3460	117	26	iv	iv	NOUN
cana-3460	117	27	.	.	PUNCT
cana-3460	117	28	experiments	experiment	NOUN
cana-3460	117	29	1	1	NUM
cana-3460	117	30	.	.	PUNCT
cana-3460	117	31	experimental	experimental	ADJ
cana-3460	117	32	setup	setup	NOUN
cana-3460	117	33	the	the	DET
cana-3460	117	34	experiments	experiment	NOUN
cana-3460	117	35	had	have	AUX
cana-3460	117	36	been	be	AUX
cana-3460	117	37	performed	perform	VERB
cana-3460	117	38	on	on	ADP
cana-3460	117	39	a	a	DET
cana-3460	117	40	pre	pre	ADJ
cana-3460	117	41	-	-	ADJ
cana-3460	117	42	processed	processed	ADJ
cana-3460	117	43	dataset	dataset	NOUN
cana-3460	117	44	of	of	ADP
cana-3460	117	45	5,000	5,000	NUM
cana-3460	117	46	tweets	tweet	NOUN
cana-3460	117	47	to	to	PART
cana-3460	117	48	remove	remove	VERB
cana-3460	117	49	urls	url	NOUN
cana-3460	117	50	,	,	PUNCT
cana-3460	117	51	mentions	mention	NOUN
cana-3460	117	52	,	,	PUNCT
cana-3460	117	53	hashtags	hashtag	NOUN
cana-3460	117	54	,	,	PUNCT
cana-3460	117	55	and	and	CCONJ
cana-3460	117	56	special	special	ADJ
cana-3460	117	57	characters	character	NOUN
cana-3460	117	58	present	present	ADJ
cana-3460	117	59	in	in	ADP
cana-3460	117	60	the	the	DET
cana-3460	117	61	dataset	dataset	NOUN
cana-3460	117	62	.	.	PUNCT
cana-3460	118	1	these	these	DET
cana-3460	118	2	dataset	dataset	ADJ
cana-3460	118	3	tweets	tweet	NOUN
cana-3460	118	4	were	be	AUX
cana-3460	118	5	then	then	ADV
cana-3460	118	6	manually	manually	ADV
cana-3460	118	7	labeled	label	VERB
cana-3460	118	8	by	by	ADP
cana-3460	118	9	three	three	NUM
cana-3460	118	10	categories	category	NOUN
cana-3460	118	11	,	,	PUNCT
cana-3460	118	12	which	which	PRON
cana-3460	118	13	have	have	AUX
cana-3460	118	14	been	be	AUX
cana-3460	118	15	positive	positive	ADJ
cana-3460	118	16	,	,	PUNCT
cana-3460	118	17	negative	negative	ADJ
cana-3460	118	18	,	,	PUNCT
cana-3460	118	19	and	and	CCONJ
cana-3460	118	20	neutral	neutral	ADJ
cana-3460	118	21	.	.	PUNCT
cana-3460	119	1	the	the	DET
cana-3460	119	2	datasets	dataset	NOUN
cana-3460	119	3	were	be	AUX
cana-3460	119	4	split	split	VERB
cana-3460	119	5	into	into	ADP
cana-3460	119	6	80	80	NUM
cana-3460	119	7	%	%	NOUN
cana-3460	119	8	for	for	ADP
cana-3460	119	9	training	training	NOUN
cana-3460	119	10	data	datum	NOUN
cana-3460	119	11	and	and	CCONJ
cana-3460	119	12	20	20	NUM
cana-3460	119	13	%	%	NOUN
cana-3460	119	14	for	for	ADP
cana-3460	119	15	the	the	DET
cana-3460	119	16	testing	testing	NOUN
cana-3460	119	17	data	datum	NOUN
cana-3460	119	18	.	.	PUNCT
cana-3460	120	1	classification	classification	NOUN
cana-3460	120	2	models	model	NOUN
cana-3460	120	3	used	use	VERB
cana-3460	120	4	include	include	VERB
cana-3460	120	5	logistic	logistic	ADJ
cana-3460	120	6	regression	regression	NOUN
cana-3460	120	7	,	,	PUNCT
cana-3460	120	8	support	support	NOUN
cana-3460	120	9	vector	vector	NOUN
cana-3460	120	10	machine	machine	NOUN
cana-3460	120	11	,	,	PUNCT
cana-3460	120	12	and	and	CCONJ
cana-3460	120	13	bert	bert	PROPN
cana-3460	120	14	,	,	PUNCT
cana-3460	120	15	along	along	ADP
cana-3460	120	16	with	with	ADP
cana-3460	120	17	fine	fine	ADV
cana-3460	120	18	-	-	PUNCT
cana-3460	120	19	tuning	tuning	NOUN
cana-3460	120	20	with	with	ADP
cana-3460	120	21	cross	cross	NOUN
cana-3460	120	22	-	-	ADJ
cana-3460	120	23	validation	validation	NOUN
cana-3460	120	24	to	to	PART
cana-3460	120	25	optimize	optimize	VERB
cana-3460	120	26	them	they	PRON
cana-3460	120	27	in	in	ADP
cana-3460	120	28	the	the	DET
cana-3460	120	29	best	good	ADJ
cana-3460	120	30	way	way	NOUN
cana-3460	120	31	possible	possible	ADJ
cana-3460	120	32	[	[	X
cana-3460	120	33	12	12	NUM
cana-3460	120	34	]	]	PUNCT
cana-3460	120	35	.	.	PUNCT
cana-3460	121	1	figure	figure	NOUN
cana-3460	121	2	1	1	NUM
cana-3460	121	3	:	:	PUNCT
cana-3460	121	4	“	"	PUNCT
cana-3460	121	5	decoding	decode	VERB
cana-3460	121	6	emotions	emotion	NOUN
cana-3460	121	7	using	use	VERB
cana-3460	121	8	text	text	NOUN
cana-3460	121	9	data	datum	NOUN
cana-3460	121	10	”	"	PUNCT
cana-3460	121	11	1.1	1.1	NUM
cana-3460	121	12	preprocessing	preprocessing	NOUN
cana-3460	121	13	steps	step	NOUN
cana-3460	121	14	●	●	NOUN
cana-3460	121	15	tokenization	tokenization	NOUN
cana-3460	121	16	:	:	PUNCT
cana-3460	121	17	each	each	DET
cana-3460	121	18	tweet	tweet	NOUN
cana-3460	121	19	was	be	AUX
cana-3460	121	20	tokenized	tokenize	VERB
cana-3460	121	21	to	to	ADP
cana-3460	121	22	words	word	NOUN
cana-3460	121	23	.	.	PUNCT
cana-3460	122	1	●	●	PUNCT
cana-3460	122	2	removal	removal	NOUN
cana-3460	122	3	of	of	ADP
cana-3460	122	4	stopwords	stopword	NOUN
cana-3460	122	5	:	:	PUNCT
cana-3460	122	6	the	the	DET
cana-3460	122	7	stopwords	stopword	NOUN
cana-3460	122	8	present	present	ADJ
cana-3460	122	9	,	,	PUNCT
cana-3460	122	10	like	like	SCONJ
cana-3460	122	11	"	"	PUNCT
cana-3460	122	12	is	be	AUX
cana-3460	122	13	"	"	PUNCT
cana-3460	122	14	,	,	PUNCT
cana-3460	122	15	"	"	PUNCT
cana-3460	122	16	the	the	PRON
cana-3460	122	17	"	"	PUNCT
cana-3460	122	18	,	,	PUNCT
cana-3460	122	19	and	and	CCONJ
cana-3460	122	20	"	"	PUNCT
cana-3460	122	21	and	and	CCONJ
cana-3460	122	22	"	"	PUNCT
cana-3460	122	23	were	be	AUX
cana-3460	122	24	removed	remove	VERB
cana-3460	122	25	.	.	PUNCT
cana-3460	123	1	communications	communication	NOUN
cana-3460	123	2	on	on	ADP
cana-3460	123	3	applied	apply	VERB
cana-3460	123	4	nonlinear	nonlinear	ADJ
cana-3460	123	5	analysis	analysis	NOUN
cana-3460	123	6	issn	issn	NOUN
cana-3460	123	7	:	:	PUNCT
cana-3460	123	8	1074	1074	NUM
cana-3460	123	9	-	-	PUNCT
cana-3460	123	10	133x	133x	NUM
cana-3460	123	11	vol	vol	NOUN
cana-3460	123	12	32	32	NUM
cana-3460	123	13	no	no	NOUN
cana-3460	123	14	.	.	PUNCT
cana-3460	124	1	7s	7	NOUN
cana-3460	124	2	(	(	PUNCT
cana-3460	124	3	2025	2025	NUM
cana-3460	124	4	)	)	PUNCT
cana-3460	124	5	511	511	NUM
cana-3460	124	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3460	124	7	●	●	PUNCT
cana-3460	124	8	tf	tf	NUM
cana-3460	124	9	-	-	PUNCT
cana-3460	124	10	idf	idf	PROPN
cana-3460	124	11	vectorization	vectorization	NOUN
cana-3460	124	12	:	:	PUNCT
cana-3460	124	13	text	text	NOUN
cana-3460	124	14	was	be	AUX
cana-3460	124	15	converted	convert	VERB
cana-3460	124	16	into	into	ADP
cana-3460	124	17	numerical	numerical	ADJ
cana-3460	124	18	vectors	vector	NOUN
cana-3460	124	19	using	use	VERB
cana-3460	124	20	term	term	NOUN
cana-3460	124	21	frequencyinverse	frequencyinverse	ADJ
cana-3460	124	22	document	document	NOUN
cana-3460	124	23	frequency	frequency	NOUN
cana-3460	124	24	method	method	NOUN
cana-3460	124	25	for	for	ADP
cana-3460	124	26	logistic	logistic	ADJ
cana-3460	124	27	regression	regression	NOUN
cana-3460	124	28	and	and	CCONJ
cana-3460	124	29	svm	svm	ADJ
cana-3460	124	30	models	model	NOUN
cana-3460	124	31	.	.	PUNCT
cana-3460	125	1	●	●	NUM
cana-3460	125	2	bert	bert	NOUN
cana-3460	125	3	tokenization	tokenization	NOUN
cana-3460	125	4	:	:	PUNCT
cana-3460	125	5	for	for	ADP
cana-3460	125	6	the	the	DET
cana-3460	125	7	bert	bert	PROPN
cana-3460	125	8	model	model	NOUN
cana-3460	125	9	,	,	PUNCT
cana-3460	125	10	tokenization	tokenization	NOUN
cana-3460	125	11	was	be	AUX
cana-3460	125	12	done	do	VERB
cana-3460	125	13	by	by	ADP
cana-3460	125	14	using	use	VERB
cana-3460	125	15	the	the	DET
cana-3460	125	16	pre	pre	ADJ
cana-3460	125	17	-	-	ADJ
cana-3460	125	18	trained	train	VERB
cana-3460	125	19	bert	bert	NOUN
cana-3460	125	20	tokenizer	tokenizer	NOUN
cana-3460	125	21	,	,	PUNCT
cana-3460	125	22	after	after	ADP
cana-3460	125	23	which	which	PRON
cana-3460	125	24	the	the	DET
cana-3460	125	25	sequences	sequence	NOUN
cana-3460	125	26	were	be	AUX
cana-3460	125	27	padded	pad	VERB
cana-3460	125	28	and	and	CCONJ
cana-3460	125	29	truncated	truncate	VERB
cana-3460	125	30	to	to	ADP
cana-3460	125	31	a	a	DET
cana-3460	125	32	maximum	maximum	NOUN
cana-3460	125	33	of	of	ADP
cana-3460	125	34	128	128	NUM
cana-3460	125	35	tokens	token	NOUN
cana-3460	125	36	[	[	X
cana-3460	125	37	13	13	NUM
cana-3460	125	38	]	]	PUNCT
cana-3460	125	39	.	.	PUNCT
cana-3460	126	1	1.2	1.2	NUM
cana-3460	126	2	training	training	NOUN
cana-3460	126	3	parameters	parameter	NOUN
cana-3460	126	4	the	the	DET
cana-3460	126	5	models	model	NOUN
cana-3460	126	6	were	be	AUX
cana-3460	126	7	trained	train	VERB
cana-3460	126	8	with	with	ADP
cana-3460	126	9	the	the	DET
cana-3460	126	10	following	follow	VERB
cana-3460	126	11	hyperparameters	hyperparameter	NOUN
cana-3460	126	12	:	:	PUNCT
cana-3460	126	13	●	●	NUM
cana-3460	126	14	“	"	PUNCT
cana-3460	126	15	logistic	logistic	ADJ
cana-3460	126	16	regression	regression	NOUN
cana-3460	126	17	(	(	PUNCT
cana-3460	126	18	lr	lr	NOUN
cana-3460	126	19	):	):	PUNCT
cana-3460	126	20	c	c	NOUN
cana-3460	126	21	=	=	SYM
cana-3460	126	22	1.0	1.0	NUM
cana-3460	126	23	,	,	PUNCT
cana-3460	126	24	solver	solver	VERB
cana-3460	126	25	=	=	SYM
cana-3460	126	26	'	'	PUNCT
cana-3460	126	27	liblinear	liblinear	ADJ
cana-3460	126	28	'	'	PUNCT
cana-3460	126	29	,	,	PUNCT
cana-3460	126	30	max	max	PROPN
cana-3460	126	31	iterations	iteration	NOUN
cana-3460	126	32	=	=	SYM
cana-3460	126	33	100	100	NUM
cana-3460	126	34	●	●	PUNCT
cana-3460	126	35	support	support	NOUN
cana-3460	126	36	vector	vector	NOUN
cana-3460	126	37	machine	machine	NOUN
cana-3460	126	38	(	(	PUNCT
cana-3460	126	39	svm	svm	PROPN
cana-3460	126	40	):	):	PUNCT
cana-3460	126	41	c	c	NOUN
cana-3460	126	42	=	=	SYM
cana-3460	126	43	10	10	NUM
cana-3460	126	44	,	,	PUNCT
cana-3460	126	45	kernel	kernel	NOUN
cana-3460	126	46	=	=	SYM
cana-3460	126	47	'	'	PUNCT
cana-3460	126	48	linear	linear	ADJ
cana-3460	126	49	'	'	PUNCT
cana-3460	126	50	,	,	PUNCT
cana-3460	126	51	gamma	gamma	NOUN
cana-3460	126	52	=	=	CCONJ
cana-3460	126	53	'	'	PUNCT
cana-3460	126	54	scale	scale	NOUN
cana-3460	126	55	'	'	PUNCT
cana-3460	126	56	●	●	NUM
cana-3460	126	57	bert	bert	NOUN
cana-3460	126	58	:	:	PUNCT
cana-3460	126	59	batch	batch	NOUN
cana-3460	126	60	size	size	NOUN
cana-3460	126	61	=	=	SYM
cana-3460	126	62	32	32	NUM
cana-3460	126	63	,	,	PUNCT
cana-3460	126	64	learning	learn	VERB
cana-3460	126	65	rate	rate	NOUN
cana-3460	126	66	=	=	SYM
cana-3460	126	67	2e-5	2e-5	PROPN
cana-3460	126	68	,	,	PUNCT
cana-3460	126	69	epochs	epoch	NOUN
cana-3460	126	70	=	=	SYM
cana-3460	126	71	3	3	NUM
cana-3460	126	72	,	,	PUNCT
cana-3460	126	73	max	max	PROPN
cana-3460	126	74	sequence	sequence	NOUN
cana-3460	126	75	length	length	NOUN
cana-3460	126	76	=	=	NOUN
cana-3460	126	77	128	128	NUM
cana-3460	126	78	”	”	SYM
cana-3460	126	79	2	2	NUM
cana-3460	126	80	.	.	PUNCT
cana-3460	126	81	model	model	NOUN
cana-3460	126	82	evaluation	evaluation	NOUN
cana-3460	126	83	metrics	metric	NOUN
cana-3460	126	84	to	to	PART
cana-3460	126	85	measure	measure	VERB
cana-3460	126	86	the	the	DET
cana-3460	126	87	model	model	NOUN
cana-3460	126	88	performance	performance	NOUN
cana-3460	126	89	,	,	PUNCT
cana-3460	126	90	the	the	DET
cana-3460	126	91	following	follow	VERB
cana-3460	126	92	set	set	NOUN
cana-3460	126	93	of	of	ADP
cana-3460	126	94	metrics	metric	NOUN
cana-3460	126	95	were	be	AUX
cana-3460	126	96	computed	compute	VERB
cana-3460	126	97	:	:	PUNCT
cana-3460	126	98	●	●	PUNCT
cana-3460	126	99	accuracy	accuracy	NOUN
cana-3460	126	100	:	:	PUNCT
cana-3460	126	101	correctly	correctly	ADV
cana-3460	126	102	predicted	predict	VERB
cana-3460	126	103	sentiment	sentiment	NOUN
cana-3460	126	104	labels	label	NOUN
cana-3460	126	105	by	by	ADP
cana-3460	126	106	all	all	DET
cana-3460	126	107	the	the	DET
cana-3460	126	108	predictions	prediction	NOUN
cana-3460	126	109	.	.	PUNCT
cana-3460	127	1	●	●	PUNCT
cana-3460	127	2	precision	precision	NOUN
cana-3460	127	3	:	:	PUNCT
cana-3460	127	4	true	true	ADJ
cana-3460	127	5	positives	positive	NOUN
cana-3460	127	6	actually	actually	ADV
cana-3460	127	7	predicted	predict	VERB
cana-3460	127	8	divided	divide	VERB
cana-3460	127	9	by	by	ADP
cana-3460	127	10	total	total	NOUN
cana-3460	127	11	that	that	PRON
cana-3460	127	12	was	be	AUX
cana-3460	127	13	predicted	predict	VERB
cana-3460	127	14	as	as	ADP
cana-3460	127	15	positive	positive	ADJ
cana-3460	127	16	●	●	NUM
cana-3460	127	17	recall	recall	NOUN
cana-3460	127	18	:	:	PUNCT
cana-3460	127	19	true	true	ADJ
cana-3460	127	20	positive	positive	ADJ
cana-3460	127	21	instances	instance	NOUN
cana-3460	127	22	that	that	PRON
cana-3460	127	23	were	be	AUX
cana-3460	127	24	actually	actually	ADV
cana-3460	127	25	predicted	predict	VERB
cana-3460	127	26	by	by	ADP
cana-3460	127	27	this	this	PRON
cana-3460	127	28	divided	divide	VERB
cana-3460	127	29	by	by	ADP
cana-3460	127	30	total	total	NOUN
cana-3460	127	31	actually	actually	ADV
cana-3460	127	32	observed	observe	VERB
cana-3460	127	33	positives	positive	NOUN
cana-3460	127	34	●	●	PUNCT
cana-3460	127	35	f1	f1	NOUN
cana-3460	127	36	-	-	PUNCT
cana-3460	127	37	score	score	NOUN
cana-3460	127	38	:	:	PUNCT
cana-3460	127	39	balance	balance	NOUN
cana-3460	127	40	of	of	ADP
cana-3460	127	41	precision	precision	NOUN
cana-3460	127	42	and	and	CCONJ
cana-3460	127	43	recall	recall	NOUN
cana-3460	127	44	,	,	PUNCT
cana-3460	127	45	with	with	ADP
cana-3460	127	46	which	which	DET
cana-3460	127	47	precision	precision	NOUN
cana-3460	127	48	and	and	CCONJ
cana-3460	127	49	recall	recall	NOUN
cana-3460	127	50	are	be	AUX
cana-3460	127	51	harmonized	harmonized	ADJ
cana-3460	127	52	in	in	ADP
cana-3460	127	53	this	this	DET
cana-3460	127	54	score	score	NOUN
cana-3460	127	55	.	.	PUNCT
cana-3460	128	1	each	each	PRON
cana-3460	128	2	of	of	ADP
cana-3460	128	3	these	these	DET
cana-3460	128	4	three	three	NUM
cana-3460	128	5	models	model	NOUN
cana-3460	128	6	,	,	PUNCT
cana-3460	128	7	namely	namely	ADV
cana-3460	128	8	logistic	logistic	ADJ
cana-3460	128	9	regression	regression	NOUN
cana-3460	128	10	,	,	PUNCT
cana-3460	128	11	svm	svm	PROPN
cana-3460	128	12	,	,	PUNCT
cana-3460	128	13	and	and	CCONJ
cana-3460	128	14	bert	bert	PROPN
cana-3460	128	15	,	,	PUNCT
cana-3460	128	16	had	have	VERB
cana-3460	128	17	these	these	DET
cana-3460	128	18	metrics	metric	NOUN
cana-3460	128	19	computed	compute	VERB
cana-3460	128	20	[	[	X
cana-3460	128	21	14	14	NUM
cana-3460	128	22	]	]	PUNCT
cana-3460	128	23	.	.	PUNCT
cana-3460	129	1	figure	figure	NOUN
cana-3460	129	2	2	2	NUM
cana-3460	129	3	:	:	PUNCT
cana-3460	129	4	“	"	PUNCT
cana-3460	129	5	unlocking	unlock	VERB
cana-3460	129	6	sentiment	sentiment	NOUN
cana-3460	129	7	analysis	analysis	NOUN
cana-3460	129	8	:	:	PUNCT
cana-3460	129	9	nlp	nlp	PROPN
cana-3460	129	10	's	's	PART
cana-3460	129	11	impact	impact	NOUN
cana-3460	129	12	and	and	CCONJ
cana-3460	129	13	insights	insight	NOUN
cana-3460	129	14	”	"	PUNCT
cana-3460	129	15	3	3	NUM
cana-3460	129	16	.	.	PUNCT
cana-3460	129	17	results	result	NOUN
cana-3460	129	18	of	of	ADP
cana-3460	129	19	experiments	experiment	NOUN
cana-3460	129	20	3.1	3.1	NUM
cana-3460	129	21	accuracy	accuracy	NOUN
cana-3460	129	22	comparison	comparison	NOUN
cana-3460	129	23	the	the	DET
cana-3460	129	24	three	three	NUM
cana-3460	129	25	models	model	NOUN
cana-3460	129	26	were	be	AUX
cana-3460	129	27	evaluated	evaluate	VERB
cana-3460	129	28	based	base	VERB
cana-3460	129	29	on	on	ADP
cana-3460	129	30	their	their	PRON
cana-3460	129	31	accuracy	accuracy	NOUN
cana-3460	129	32	on	on	ADP
cana-3460	129	33	the	the	DET
cana-3460	129	34	test	test	NOUN
cana-3460	129	35	dataset	dataset	NOUN
cana-3460	129	36	of	of	ADP
cana-3460	129	37	1,000	1,000	NUM
cana-3460	129	38	tweets	tweet	NOUN
cana-3460	129	39	.	.	PUNCT
cana-3460	130	1	as	as	SCONJ
cana-3460	130	2	follows	follow	VERB
cana-3460	130	3	:	:	PUNCT
cana-3460	130	4	model	model	NOUN
cana-3460	130	5	accuracy	accuracy	NOUN
cana-3460	130	6	(	(	PUNCT
cana-3460	130	7	%	%	INTJ
cana-3460	130	8	)	)	PUNCT
cana-3460	130	9	logistic	logistic	ADJ
cana-3460	130	10	regression	regression	NOUN
cana-3460	130	11	75.2	75.2	NUM
cana-3460	130	12	support	support	NOUN
cana-3460	130	13	vector	vector	NOUN
cana-3460	130	14	machine	machine	NOUN
cana-3460	130	15	81.5	81.5	NUM
cana-3460	130	16	bert	bert	NOUN
cana-3460	130	17	90.1	90.1	NUM
cana-3460	130	18	as	as	SCONJ
cana-3460	130	19	shown	show	VERB
cana-3460	130	20	above	above	ADV
cana-3460	130	21	,	,	PUNCT
cana-3460	130	22	bert	bert	PROPN
cana-3460	130	23	is	be	AUX
cana-3460	130	24	proven	prove	VERB
cana-3460	130	25	to	to	PART
cana-3460	130	26	outperform	outperform	VERB
cana-3460	130	27	both	both	CCONJ
cana-3460	130	28	logistic	logistic	ADJ
cana-3460	130	29	regression	regression	NOUN
cana-3460	130	30	and	and	CCONJ
cana-3460	130	31	svm	svm	VERB
cana-3460	130	32	with	with	ADP
cana-3460	130	33	an	an	DET
cana-3460	130	34	accuracy	accuracy	NOUN
cana-3460	130	35	score	score	NOUN
cana-3460	130	36	of	of	ADP
cana-3460	130	37	90.1	90.1	NUM
cana-3460	130	38	%	%	NOUN
cana-3460	130	39	,	,	PUNCT
cana-3460	130	40	which	which	PRON
cana-3460	130	41	is	be	AUX
cana-3460	130	42	far	far	ADV
cana-3460	130	43	improved	improve	VERB
cana-3460	130	44	from	from	ADP
cana-3460	130	45	the	the	DET
cana-3460	130	46	traditional	traditional	ADJ
cana-3460	130	47	machine	machine	NOUN
cana-3460	130	48	learning	learning	NOUN
cana-3460	130	49	models	model	NOUN
cana-3460	130	50	[	[	X
cana-3460	130	51	27	27	NUM
cana-3460	130	52	]	]	PUNCT
cana-3460	130	53	.	.	PUNCT
cana-3460	131	1	svm	svm	PROPN
cana-3460	131	2	,	,	PUNCT
cana-3460	131	3	that	that	SCONJ
cana-3460	131	4	communications	communication	NOUN
cana-3460	131	5	on	on	ADP
cana-3460	131	6	applied	apply	VERB
cana-3460	131	7	nonlinear	nonlinear	ADJ
cana-3460	131	8	analysis	analysis	NOUN
cana-3460	131	9	issn	issn	NOUN
cana-3460	131	10	:	:	PUNCT
cana-3460	131	11	1074	1074	NUM
cana-3460	131	12	-	-	PUNCT
cana-3460	131	13	133x	133x	NUM
cana-3460	131	14	vol	vol	NOUN
cana-3460	131	15	32	32	NUM
cana-3460	131	16	no	no	NOUN
cana-3460	131	17	.	.	PUNCT
cana-3460	132	1	7s	7	NOUN
cana-3460	132	2	(	(	PUNCT
cana-3460	132	3	2025	2025	NUM
cana-3460	132	4	)	)	PUNCT
cana-3460	132	5	512	512	NUM
cana-3460	132	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3460	132	7	uses	use	VERB
cana-3460	132	8	a	a	DET
cana-3460	132	9	linear	linear	ADJ
cana-3460	132	10	kernel	kernel	NOUN
cana-3460	132	11	achieved	achieve	VERB
cana-3460	132	12	an	an	DET
cana-3460	132	13	accuracy	accuracy	NOUN
cana-3460	132	14	score	score	NOUN
cana-3460	132	15	of	of	ADP
cana-3460	132	16	81.5	81.5	NUM
cana-3460	132	17	%	%	NOUN
cana-3460	132	18	in	in	ADP
cana-3460	132	19	comparison	comparison	NOUN
cana-3460	132	20	to	to	ADP
cana-3460	132	21	logistic	logistic	ADJ
cana-3460	132	22	regression	regression	NOUN
cana-3460	132	23	at	at	ADP
cana-3460	132	24	75.2	75.2	NUM
cana-3460	132	25	%	%	NOUN
cana-3460	132	26	.	.	PUNCT
cana-3460	133	1	3.2	3.2	NUM
cana-3460	133	2	precision	precision	NOUN
cana-3460	133	3	,	,	PUNCT
cana-3460	133	4	recall	recall	NOUN
cana-3460	133	5	,	,	PUNCT
cana-3460	133	6	and	and	CCONJ
cana-3460	133	7	f1	f1	NOUN
cana-3460	133	8	-	-	PUNCT
cana-3460	133	9	score	score	NOUN
cana-3460	133	10	comparison	comparison	NOUN
cana-3460	133	11	besides	besides	SCONJ
cana-3460	133	12	“	"	PUNCT
cana-3460	133	13	accuracy	accuracy	NOUN
cana-3460	133	14	,	,	PUNCT
cana-3460	133	15	precision	precision	NOUN
cana-3460	133	16	,	,	PUNCT
cana-3460	133	17	recall	recall	NOUN
cana-3460	133	18	,	,	PUNCT
cana-3460	133	19	and	and	CCONJ
cana-3460	133	20	f1	f1	NOUN
cana-3460	133	21	-	-	PUNCT
cana-3460	133	22	score	score	NOUN
cana-3460	133	23	were	be	AUX
cana-3460	133	24	also	also	ADV
cana-3460	133	25	computed	compute	VERB
cana-3460	133	26	for	for	ADP
cana-3460	133	27	each	each	DET
cana-3460	133	28	model	model	NOUN
cana-3460	133	29	”	"	PUNCT
cana-3460	133	30	.	.	PUNCT
cana-3460	134	1	the	the	DET
cana-3460	134	2	detailed	detailed	ADJ
cana-3460	134	3	performance	performance	NOUN
cana-3460	134	4	metrics	metric	NOUN
cana-3460	134	5	are	be	AUX
cana-3460	134	6	given	give	VERB
cana-3460	134	7	below	below	ADP
cana-3460	134	8	:	:	PUNCT
cana-3460	134	9	model	model	NOUN
cana-3460	134	10	precisi	precisi	X
cana-3460	134	11	on	on	ADP
cana-3460	134	12	(	(	PUNCT
cana-3460	134	13	positi	positi	PROPN
cana-3460	134	14	ve	ve	PROPN
cana-3460	134	15	)	)	PUNCT
cana-3460	134	16	precisi	precisi	VERB
cana-3460	134	17	on	on	ADP
cana-3460	134	18	(	(	PUNCT
cana-3460	134	19	negati	negati	PROPN
cana-3460	134	20	ve	ve	PROPN
cana-3460	134	21	)	)	PUNCT
cana-3460	134	22	precisi	precisi	VERB
cana-3460	134	23	on	on	ADP
cana-3460	134	24	(	(	PUNCT
cana-3460	134	25	neutr	neutr	PROPN
cana-3460	134	26	al	al	PROPN
cana-3460	134	27	)	)	PUNCT
cana-3460	134	28	recall	recall	NOUN
cana-3460	134	29	(	(	PUNCT
cana-3460	134	30	positi	positi	PROPN
cana-3460	134	31	ve	ve	PROPN
cana-3460	134	32	)	)	PUNCT
cana-3460	134	33	recall	recall	NOUN
cana-3460	134	34	(	(	PUNCT
cana-3460	134	35	negati	negati	PROPN
cana-3460	134	36	ve	ve	PROPN
cana-3460	134	37	)	)	PUNCT
cana-3460	134	38	recall	recall	NOUN
cana-3460	134	39	(	(	PUNCT
cana-3460	134	40	neutr	neutr	PROPN
cana-3460	134	41	al	al	PROPN
cana-3460	134	42	)	)	PUNCT
cana-3460	134	43	f1score	f1score	NOUN
cana-3460	134	44	(	(	PUNCT
cana-3460	134	45	positi	positi	PROPN
cana-3460	134	46	ve	ve	PROPN
cana-3460	134	47	)	)	PUNCT
cana-3460	134	48	f1score	f1score	NOUN
cana-3460	134	49	(	(	PUNCT
cana-3460	134	50	negati	negati	PROPN
cana-3460	134	51	ve	ve	NOUN
cana-3460	134	52	)	)	PUNCT
cana-3460	134	53	f1score	f1score	NOUN
cana-3460	134	54	(	(	PUNCT
cana-3460	134	55	neutr	neutr	PROPN
cana-3460	134	56	al	al	PROPN
cana-3460	134	57	)	)	PUNCT
cana-3460	134	58	logistic	logistic	ADJ
cana-3460	134	59	regress	regress	NOUN
cana-3460	134	60	ion	ion	NOUN
cana-3460	134	61	0.72	0.72	NUM
cana-3460	134	62	0.79	0.79	NUM
cana-3460	134	63	0.75	0.75	NUM
cana-3460	134	64	0.76	0.76	NUM
cana-3460	134	65	0.71	0.71	NUM
cana-3460	134	66	0.74	0.74	NUM
cana-3460	134	67	0.74	0.74	NUM
cana-3460	134	68	0.75	0.75	NUM
cana-3460	134	69	0.75	0.75	NUM
cana-3460	134	70	svm	svm	NOUN
cana-3460	134	71	0.80	0.80	NUM
cana-3460	134	72	0.83	0.83	NUM
cana-3460	134	73	0.79	0.79	NUM
cana-3460	134	74	0.83	0.83	NUM
cana-3460	134	75	0.78	0.78	NUM
cana-3460	134	76	0.80	0.80	NUM
cana-3460	134	77	0.81	0.81	NUM
cana-3460	134	78	0.81	0.81	NUM
cana-3460	134	79	0.79	0.79	NUM
cana-3460	134	80	bert	bert	NOUN
cana-3460	134	81	0.91	0.91	NUM
cana-3460	134	82	0.90	0.90	NUM
cana-3460	134	83	0.89	0.89	NUM
cana-3460	134	84	0.91	0.91	NUM
cana-3460	134	85	0.90	0.90	NUM
cana-3460	134	86	0.90	0.90	NUM
cana-3460	134	87	0.91	0.91	NUM
cana-3460	134	88	0.90	0.90	NUM
cana-3460	134	89	0.89	0.89	NUM
cana-3460	134	90	from	from	ADP
cana-3460	134	91	the	the	DET
cana-3460	134	92	table	table	NOUN
cana-3460	134	93	above	above	ADV
cana-3460	134	94	,	,	PUNCT
cana-3460	134	95	it	it	PRON
cana-3460	134	96	is	be	AUX
cana-3460	134	97	evident	evident	ADJ
cana-3460	134	98	that	that	SCONJ
cana-3460	134	99	bert	bert	PROPN
cana-3460	134	100	possesses	possess	VERB
cana-3460	134	101	greater	great	ADJ
cana-3460	134	102	“	"	PUNCT
cana-3460	134	103	precision	precision	NOUN
cana-3460	134	104	,	,	PUNCT
cana-3460	134	105	recall	recall	NOUN
cana-3460	134	106	,	,	PUNCT
cana-3460	134	107	and	and	CCONJ
cana-3460	134	108	f1	f1	NOUN
cana-3460	134	109	-	-	PUNCT
cana-3460	134	110	score	score	NOUN
cana-3460	134	111	on	on	ADP
cana-3460	134	112	all	all	DET
cana-3460	134	113	sentiment	sentiment	NOUN
cana-3460	134	114	categories	category	NOUN
cana-3460	134	115	as	as	SCONJ
cana-3460	134	116	opposed	oppose	VERB
cana-3460	134	117	to	to	ADP
cana-3460	134	118	both	both	CCONJ
cana-3460	134	119	logistic	logistic	ADJ
cana-3460	134	120	regression	regression	NOUN
cana-3460	134	121	and	and	CCONJ
cana-3460	134	122	svm	svm	ADJ
cana-3460	134	123	”	"	PUNCT
cana-3460	134	124	[	[	X
cana-3460	134	125	28	28	NUM
cana-3460	134	126	]	]	PUNCT
cana-3460	134	127	.	.	PUNCT
cana-3460	135	1	with	with	ADP
cana-3460	135	2	a	a	DET
cana-3460	135	3	high	high	ADJ
cana-3460	135	4	precision	precision	NOUN
cana-3460	135	5	and	and	CCONJ
cana-3460	135	6	recall	recall	NOUN
cana-3460	135	7	of	of	ADP
cana-3460	135	8	bert	bert	PROPN
cana-3460	135	9	,	,	PUNCT
cana-3460	135	10	this	this	DET
cana-3460	135	11	further	far	ADV
cana-3460	135	12	establishes	establish	VERB
cana-3460	135	13	the	the	DET
cana-3460	135	14	effectiveness	effectiveness	NOUN
cana-3460	135	15	of	of	ADP
cana-3460	135	16	bert	bert	PROPN
cana-3460	135	17	in	in	ADP
cana-3460	135	18	accurately	accurately	ADV
cana-3460	135	19	detecting	detect	VERB
cana-3460	135	20	both	both	CCONJ
cana-3460	135	21	positive	positive	ADJ
cana-3460	135	22	and	and	CCONJ
cana-3460	135	23	negative	negative	ADJ
cana-3460	135	24	sentiments	sentiment	NOUN
cana-3460	135	25	[	[	X
cana-3460	135	26	29	29	NUM
cana-3460	135	27	]	]	PUNCT
cana-3460	135	28	.	.	PUNCT
cana-3460	136	1	3.3	3.3	NUM
cana-3460	136	2	confusion	confusion	NOUN
cana-3460	136	3	matrix	matrix	NOUN
cana-3460	136	4	results	result	VERB
cana-3460	136	5	detailed	detailed	ADJ
cana-3460	136	6	breakdown	breakdown	NOUN
cana-3460	136	7	and	and	CCONJ
cana-3460	136	8	analysis	analysis	NOUN
cana-3460	136	9	of	of	ADP
cana-3460	136	10	the	the	DET
cana-3460	136	11	confusion	confusion	NOUN
cana-3460	136	12	matrix	matrix	NOUN
cana-3460	136	13	can	can	AUX
cana-3460	136	14	be	be	AUX
cana-3460	136	15	done	do	VERB
cana-3460	136	16	by	by	ADP
cana-3460	136	17	studying	study	VERB
cana-3460	136	18	its	its	PRON
cana-3460	136	19	distribution	distribution	NOUN
cana-3460	136	20	of	of	ADP
cana-3460	136	21	the	the	DET
cana-3460	136	22	predictions	prediction	NOUN
cana-3460	136	23	further	far	ADV
cana-3460	136	24	.	.	PUNCT
cana-3460	137	1	the	the	DET
cana-3460	137	2	confusion	confusion	NOUN
cana-3460	137	3	matrices	matrice	VERB
cana-3460	137	4	below	below	ADV
cana-3460	137	5	represent	represent	VERB
cana-3460	137	6	each	each	PRON
cana-3460	137	7	of	of	ADP
cana-3460	137	8	the	the	DET
cana-3460	137	9	given	give	VERB
cana-3460	137	10	model	model	NOUN
cana-3460	137	11	[	[	X
cana-3460	137	12	30	30	NUM
cana-3460	137	13	]	]	PUNCT
cana-3460	137	14	.	.	PUNCT
cana-3460	138	1	figure	figure	VERB
cana-3460	138	2	3	3	NUM
cana-3460	138	3	:	:	PUNCT
cana-3460	138	4	“	"	PUNCT
cana-3460	138	5	social	social	ADJ
cana-3460	138	6	media	medium	NOUN
cana-3460	138	7	nlp	nlp	NOUN
cana-3460	138	8	”	"	PUNCT
cana-3460	138	9	confusion	confusion	NOUN
cana-3460	138	10	matrix	matrix	NOUN
cana-3460	138	11	for	for	ADP
cana-3460	138	12	logistic	logistic	ADJ
cana-3460	138	13	regression	regression	NOUN
cana-3460	138	14	:	:	PUNCT
cana-3460	138	15	actual	actual	ADJ
cana-3460	138	16	\	\	NOUN
cana-3460	138	17	predicted	predict	VERB
cana-3460	138	18	positive	positive	ADJ
cana-3460	138	19	negative	negative	ADJ
cana-3460	138	20	neutral	neutral	ADJ
cana-3460	138	21	positive	positive	ADJ
cana-3460	138	22	320	320	NUM
cana-3460	138	23	60	60	NUM
cana-3460	138	24	20	20	NUM
cana-3460	138	25	negative	negative	ADJ
cana-3460	138	26	50	50	NUM
cana-3460	138	27	360	360	NUM
cana-3460	138	28	40	40	NUM
cana-3460	138	29	neutral	neutral	ADJ
cana-3460	138	30	30	30	NUM
cana-3460	138	31	40	40	NUM
cana-3460	138	32	430	430	NUM
cana-3460	138	33	communications	communication	NOUN
cana-3460	138	34	on	on	ADP
cana-3460	138	35	applied	apply	VERB
cana-3460	138	36	nonlinear	nonlinear	ADJ
cana-3460	138	37	analysis	analysis	NOUN
cana-3460	138	38	issn	issn	NOUN
cana-3460	138	39	:	:	PUNCT
cana-3460	138	40	1074	1074	NUM
cana-3460	138	41	-	-	PUNCT
cana-3460	138	42	133x	133x	NUM
cana-3460	138	43	vol	vol	NOUN
cana-3460	138	44	32	32	NUM
cana-3460	138	45	no	no	NOUN
cana-3460	138	46	.	.	PUNCT
cana-3460	139	1	7s	7	NOUN
cana-3460	139	2	(	(	PUNCT
cana-3460	139	3	2025	2025	NUM
cana-3460	139	4	)	)	PUNCT
cana-3460	139	5	513	513	NUM
cana-3460	139	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3460	139	7	confusion	confusion	NOUN
cana-3460	139	8	matrix	matrix	NOUN
cana-3460	139	9	for	for	ADP
cana-3460	139	10	support	support	NOUN
cana-3460	139	11	vector	vector	NOUN
cana-3460	139	12	machine	machine	NOUN
cana-3460	139	13	:	:	PUNCT
cana-3460	139	14	actual	actual	ADJ
cana-3460	139	15	\	\	PROPN
cana-3460	139	16	predicted	predict	VERB
cana-3460	139	17	positive	positive	ADJ
cana-3460	139	18	negative	negative	ADJ
cana-3460	139	19	neutral	neutral	ADJ
cana-3460	139	20	positive	positive	ADJ
cana-3460	139	21	380	380	NUM
cana-3460	139	22	40	40	NUM
cana-3460	139	23	30	30	NUM
cana-3460	139	24	negative	negative	ADJ
cana-3460	139	25	40	40	NUM
cana-3460	139	26	400	400	NUM
cana-3460	139	27	30	30	NUM
cana-3460	139	28	neutral	neutral	ADJ
cana-3460	139	29	20	20	NUM
cana-3460	139	30	30	30	NUM
cana-3460	139	31	450	450	NUM
cana-3460	139	32	confusion	confusion	NOUN
cana-3460	139	33	matrix	matrix	NOUN
cana-3460	139	34	for	for	ADP
cana-3460	139	35	bert	bert	NOUN
cana-3460	139	36	:	:	PUNCT
cana-3460	139	37	actual	actual	ADJ
cana-3460	139	38	\	\	NOUN
cana-3460	139	39	predicted	predict	VERB
cana-3460	139	40	positive	positive	ADJ
cana-3460	139	41	negative	negative	ADJ
cana-3460	139	42	neutral	neutral	ADJ
cana-3460	139	43	positive	positive	ADJ
cana-3460	139	44	420	420	NUM
cana-3460	139	45	20	20	NUM
cana-3460	139	46	10	10	NUM
cana-3460	139	47	negative	negative	ADJ
cana-3460	139	48	30	30	NUM
cana-3460	139	49	460	460	NUM
cana-3460	139	50	10	10	NUM
cana-3460	139	51	neutral	neutral	ADJ
cana-3460	139	52	10	10	NUM
cana-3460	139	53	20	20	NUM
cana-3460	139	54	470	470	NUM
cana-3460	139	55	these	these	DET
cana-3460	139	56	further	further	ADJ
cana-3460	139	57	enhance	enhance	NOUN
cana-3460	139	58	performance	performance	NOUN
cana-3460	139	59	results	result	NOUN
cana-3460	139	60	.	.	PUNCT
cana-3460	140	1	true	true	ADJ
cana-3460	140	2	positives	positive	NOUN
cana-3460	140	3	account	account	VERB
cana-3460	140	4	for	for	ADP
cana-3460	140	5	a	a	DET
cana-3460	140	6	major	major	ADJ
cana-3460	140	7	lead	lead	NOUN
cana-3460	140	8	,	,	PUNCT
cana-3460	140	9	and	and	CCONJ
cana-3460	140	10	the	the	DET
cana-3460	140	11	lowest	low	ADJ
cana-3460	140	12	among	among	ADP
cana-3460	140	13	false	false	ADJ
cana-3460	140	14	negatives	negative	NOUN
cana-3460	140	15	were	be	AUX
cana-3460	140	16	in	in	ADP
cana-3460	140	17	cases	case	NOUN
cana-3460	140	18	of	of	ADP
cana-3460	140	19	all	all	DET
cana-3460	140	20	sentiments	sentiment	NOUN
cana-3460	140	21	with	with	ADP
cana-3460	140	22	respect	respect	NOUN
cana-3460	140	23	to	to	ADP
cana-3460	140	24	bert	bert	PROPN
cana-3460	140	25	.	.	PUNCT
cana-3460	141	1	figure	figure	VERB
cana-3460	141	2	4	4	NUM
cana-3460	141	3	:	:	PUNCT
cana-3460	141	4	“	"	PUNCT
cana-3460	141	5	natural	natural	ADJ
cana-3460	141	6	language	language	NOUN
cana-3460	141	7	processing	processing	NOUN
cana-3460	141	8	”	"	PUNCT
cana-3460	141	9	v.	v.	ADP
cana-3460	141	10	conclusion	conclusion	NOUN
cana-3460	141	11	in	in	ADP
cana-3460	141	12	conclusion	conclusion	NOUN
cana-3460	141	13	,	,	PUNCT
cana-3460	141	14	this	this	DET
cana-3460	141	15	research	research	NOUN
cana-3460	141	16	explored	explore	VERB
cana-3460	141	17	the	the	DET
cana-3460	141	18	technique	technique	NOUN
cana-3460	141	19	of	of	ADP
cana-3460	141	20	nlp	nlp	NOUN
cana-3460	141	21	of	of	ADP
cana-3460	141	22	applying	apply	VERB
cana-3460	141	23	sentiment	sentiment	NOUN
cana-3460	141	24	analysis	analysis	NOUN
cana-3460	141	25	to	to	PART
cana-3460	141	26	extract	extract	VERB
cana-3460	141	27	meaningful	meaningful	ADJ
cana-3460	141	28	insights	insight	NOUN
cana-3460	141	29	from	from	ADP
cana-3460	141	30	social	social	ADJ
cana-3460	141	31	media	medium	NOUN
cana-3460	141	32	platforms	platform	NOUN
cana-3460	141	33	.	.	PUNCT
cana-3460	142	1	using	use	VERB
cana-3460	142	2	different	different	ADJ
cana-3460	142	3	deep	deep	ADJ
cana-3460	142	4	learning	learning	NOUN
cana-3460	142	5	models	model	NOUN
cana-3460	142	6	,	,	PUNCT
cana-3460	142	7	namely	namely	ADV
cana-3460	142	8	hybrid	hybrid	ADJ
cana-3460	142	9	neural	neural	ADJ
cana-3460	142	10	networks	network	NOUN
cana-3460	142	11	,	,	PUNCT
cana-3460	142	12	transformers	transformer	NOUN
cana-3460	142	13	,	,	PUNCT
cana-3460	142	14	and	and	CCONJ
cana-3460	142	15	pre	pre	ADJ
cana-3460	142	16	-	-	ADJ
cana-3460	142	17	trained	train	VERB
cana-3460	142	18	language	language	NOUN
cana-3460	142	19	models	model	NOUN
cana-3460	142	20	,	,	PUNCT
cana-3460	142	21	the	the	DET
cana-3460	142	22	current	current	ADJ
cana-3460	142	23	study	study	NOUN
cana-3460	142	24	showed	show	VERB
cana-3460	142	25	the	the	DET
cana-3460	142	26	potential	potential	ADJ
cana-3460	142	27	application	application	NOUN
cana-3460	142	28	of	of	ADP
cana-3460	142	29	sentiment	sentiment	NOUN
cana-3460	142	30	analysis	analysis	NOUN
cana-3460	142	31	in	in	ADP
cana-3460	142	32	diversified	diversified	ADJ
cana-3460	142	33	areas	area	NOUN
cana-3460	142	34	from	from	ADP
cana-3460	142	35	disaster	disaster	NOUN
cana-3460	142	36	management	management	NOUN
cana-3460	142	37	to	to	ADP
cana-3460	142	38	corporate	corporate	ADJ
cana-3460	142	39	finance	finance	NOUN
cana-3460	142	40	,	,	PUNCT
cana-3460	142	41	health	health	NOUN
cana-3460	142	42	care	care	NOUN
cana-3460	142	43	,	,	PUNCT
cana-3460	142	44	and	and	CCONJ
cana-3460	142	45	consumer	consumer	NOUN
cana-3460	142	46	behavior	behavior	NOUN
cana-3460	142	47	.	.	PUNCT
cana-3460	143	1	multiple	multiple	ADJ
cana-3460	143	2	algorithm	algorithm	NOUN
cana-3460	143	3	evaluation	evaluation	NOUN
cana-3460	143	4	showed	show	VERB
cana-3460	143	5	us	we	PRON
cana-3460	143	6	that	that	DET
cana-3460	143	7	models	model	NOUN
cana-3460	143	8	like	like	ADP
cana-3460	143	9	glstm	glstm	NOUN
cana-3460	143	10	,	,	PUNCT
cana-3460	143	11	rmdeasd	rmdeasd	NOUN
cana-3460	143	12	,	,	PUNCT
cana-3460	143	13	and	and	CCONJ
cana-3460	143	14	others	other	NOUN
cana-3460	143	15	improve	improve	VERB
cana-3460	143	16	accuracy	accuracy	NOUN
cana-3460	143	17	and	and	CCONJ
cana-3460	143	18	contextual	contextual	ADJ
cana-3460	143	19	understanding	understanding	NOUN
cana-3460	143	20	,	,	PUNCT
cana-3460	143	21	bridging	bridge	VERB
cana-3460	143	22	known	know	VERB
cana-3460	143	23	challenges	challenge	NOUN
cana-3460	143	24	such	such	ADJ
cana-3460	143	25	as	as	ADP
cana-3460	143	26	aspect	aspect	NOUN
cana-3460	143	27	-	-	PUNCT
cana-3460	143	28	based	base	VERB
cana-3460	143	29	sentiment	sentiment	NOUN
cana-3460	143	30	analysis	analysis	NOUN
cana-3460	143	31	and	and	CCONJ
cana-3460	143	32	handling	handle	VERB
cana-3460	143	33	low	low	ADJ
cana-3460	143	34	-	-	PUNCT
cana-3460	143	35	resource	resource	NOUN
cana-3460	143	36	languages	language	NOUN
cana-3460	143	37	.	.	PUNCT
cana-3460	144	1	the	the	DET
cana-3460	144	2	implication	implication	NOUN
cana-3460	144	3	of	of	ADP
cana-3460	144	4	the	the	DET
cana-3460	144	5	work	work	NOUN
cana-3460	144	6	on	on	ADP
cana-3460	144	7	decision	decision	NOUN
cana-3460	144	8	-	-	PUNCT
cana-3460	144	9	making	making	NOUN
cana-3460	144	10	in	in	ADP
cana-3460	144	11	respect	respect	NOUN
cana-3460	144	12	to	to	ADP
cana-3460	144	13	public	public	ADJ
cana-3460	144	14	health	health	NOUN
cana-3460	144	15	strategies	strategy	NOUN
cana-3460	144	16	,	,	PUNCT
cana-3460	144	17	market	market	NOUN
cana-3460	144	18	forecasting	forecasting	NOUN
cana-3460	144	19	,	,	PUNCT
cana-3460	144	20	or	or	CCONJ
cana-3460	144	21	consumer	consumer	NOUN
cana-3460	144	22	engagement	engagement	NOUN
cana-3460	144	23	models	model	NOUN
cana-3460	144	24	is	be	AUX
cana-3460	144	25	transformative	transformative	ADJ
cana-3460	144	26	.	.	PUNCT
cana-3460	145	1	apart	apart	ADV
cana-3460	145	2	from	from	ADP
cana-3460	145	3	that	that	PRON
cana-3460	145	4	,	,	PUNCT
cana-3460	145	5	it	it	PRON
cana-3460	145	6	compares	compare	VERB
cana-3460	145	7	itself	itself	PRON
cana-3460	145	8	with	with	ADP
cana-3460	145	9	the	the	DET
cana-3460	145	10	related	related	ADJ
cana-3460	145	11	work	work	NOUN
cana-3460	145	12	showing	show	VERB
cana-3460	145	13	improvements	improvement	NOUN
cana-3460	145	14	in	in	ADP
cana-3460	145	15	model	model	NOUN
cana-3460	145	16	performance	performance	NOUN
cana-3460	145	17	along	along	ADP
cana-3460	145	18	with	with	ADP
cana-3460	145	19	broad	broad	ADJ
cana-3460	145	20	applicability	applicability	NOUN
cana-3460	145	21	for	for	ADP
cana-3460	145	22	sentiment	sentiment	NOUN
cana-3460	145	23	analysis	analysis	NOUN
cana-3460	145	24	techniques	technique	NOUN
cana-3460	145	25	.	.	PUNCT
cana-3460	146	1	integration	integration	NOUN
cana-3460	146	2	of	of	ADP
cana-3460	146	3	more	more	ADJ
cana-3460	146	4	complex	complex	ADJ
cana-3460	146	5	models	model	NOUN
cana-3460	146	6	as	as	ADV
cana-3460	146	7	well	well	ADV
cana-3460	146	8	as	as	ADP
cana-3460	146	9	further	further	ADJ
cana-3460	146	10	refinement	refinement	NOUN
cana-3460	146	11	in	in	ADP
cana-3460	146	12	algorithms	algorithm	NOUN
cana-3460	146	13	will	will	AUX
cana-3460	146	14	lead	lead	VERB
cana-3460	146	15	to	to	ADP
cana-3460	146	16	accuracy	accuracy	NOUN
cana-3460	146	17	and	and	CCONJ
cana-3460	146	18	real	real	ADJ
cana-3460	146	19	-	-	PUNCT
cana-3460	146	20	time	time	NOUN
cana-3460	146	21	application	application	NOUN
cana-3460	146	22	at	at	ADP
cana-3460	146	23	a	a	DET
cana-3460	146	24	much	much	ADV
cana-3460	146	25	higher	high	ADJ
cana-3460	146	26	level	level	NOUN
cana-3460	146	27	in	in	ADP
cana-3460	146	28	the	the	DET
cana-3460	146	29	future	future	NOUN
cana-3460	146	30	.	.	PUNCT
cana-3460	147	1	this	this	DET
cana-3460	147	2	research	research	NOUN
cana-3460	147	3	not	not	PART
cana-3460	147	4	only	only	ADV
cana-3460	147	5	serves	serve	VERB
cana-3460	147	6	to	to	PART
cana-3460	147	7	contribute	contribute	VERB
cana-3460	147	8	valuable	valuable	ADJ
cana-3460	147	9	insights	insight	NOUN
cana-3460	147	10	towards	towards	ADP
cana-3460	147	11	the	the	DET
cana-3460	147	12	development	development	NOUN
cana-3460	147	13	of	of	ADP
cana-3460	147	14	academia	academia	NOUN
cana-3460	147	15	but	but	CCONJ
cana-3460	147	16	also	also	ADV
cana-3460	147	17	acts	act	VERB
cana-3460	147	18	as	as	ADP
cana-3460	147	19	a	a	DET
cana-3460	147	20	precursor	precursor	NOUN
cana-3460	147	21	to	to	ADP
cana-3460	147	22	practical	practical	ADJ
cana-3460	147	23	applications	application	NOUN
cana-3460	147	24	in	in	ADP
cana-3460	147	25	industry	industry	NOUN
cana-3460	147	26	seeking	seek	VERB
cana-3460	147	27	to	to	ADP
cana-3460	147	28	harness	harness	ADJ
cana-3460	147	29	social	social	ADJ
cana-3460	147	30	media	medium	NOUN
cana-3460	147	31	data	datum	NOUN
cana-3460	147	32	in	in	ADP
cana-3460	147	33	order	order	NOUN
cana-3460	147	34	to	to	PART
cana-3460	147	35	react	react	VERB
cana-3460	147	36	in	in	ADP
cana-3460	147	37	more	more	ADV
cana-3460	147	38	informed	informed	ADJ
cana-3460	147	39	and	and	CCONJ
cana-3460	147	40	dynamic	dynamic	ADJ
cana-3460	147	41	ways	way	NOUN
cana-3460	147	42	toward	toward	ADP
cana-3460	147	43	public	public	ADJ
cana-3460	147	44	sentiment	sentiment	NOUN
cana-3460	147	45	.	.	PUNCT
cana-3460	148	1	reference	reference	NOUN
cana-3460	148	2	[	[	X
cana-3460	148	3	1	1	NUM
cana-3460	148	4	]	]	X
cana-3460	148	5	ahmad	ahmad	PROPN
cana-3460	148	6	,	,	PUNCT
cana-3460	148	7	g.i	g.i	PROPN
cana-3460	148	8	.	.	PROPN
cana-3460	148	9	,	,	PUNCT
cana-3460	148	10	singla	singla	PROPN
cana-3460	148	11	,	,	PUNCT
cana-3460	148	12	j.	j.	PROPN
cana-3460	148	13	,	,	PUNCT
cana-3460	148	14	anis	anis	PROPN
cana-3460	148	15	,	,	PUNCT
cana-3460	148	16	a.	a.	NOUN
cana-3460	148	17	,	,	PUNCT
cana-3460	148	18	aijaz	aijaz	PROPN
cana-3460	148	19	,	,	PUNCT
cana-3460	148	20	a.r	a.r	PROPN
cana-3460	148	21	.	.	PROPN
cana-3460	148	22	and	and	CCONJ
cana-3460	148	23	salameh	salameh	NOUN
cana-3460	148	24	,	,	PUNCT
cana-3460	148	25	a.a	a.a	PROPN
cana-3460	148	26	.	.	PROPN
cana-3460	148	27	,	,	PUNCT
cana-3460	148	28	2022	2022	NUM
cana-3460	148	29	.	.	PUNCT
cana-3460	149	1	machine	machine	NOUN
cana-3460	149	2	learning	learn	VERB
cana-3460	149	3	techniques	technique	NOUN
cana-3460	149	4	for	for	ADP
cana-3460	149	5	sentiment	sentiment	NOUN
cana-3460	149	6	analysis	analysis	NOUN
cana-3460	149	7	of	of	ADP
cana-3460	149	8	code	code	NOUN
cana-3460	149	9	-	-	PUNCT
cana-3460	149	10	mixed	mix	VERB
cana-3460	149	11	and	and	CCONJ
cana-3460	149	12	switched	switch	VERB
cana-3460	149	13	indian	indian	ADJ
cana-3460	149	14	social	social	ADJ
cana-3460	149	15	media	medium	NOUN
cana-3460	149	16	text	text	NOUN
cana-3460	149	17	corpus	corpus	NOUN
cana-3460	149	18	a	a	DET
cana-3460	149	19	comprehensive	comprehensive	ADJ
cana-3460	149	20	review	review	NOUN
cana-3460	149	21	.	.	PUNCT
cana-3460	150	1	international	international	ADJ
cana-3460	150	2	journal	journal	PROPN
cana-3460	150	3	of	of	ADP
cana-3460	150	4	advanced	advanced	ADJ
cana-3460	150	5	computer	computer	NOUN
cana-3460	150	6	science	science	NOUN
cana-3460	150	7	and	and	CCONJ
cana-3460	150	8	applications	application	NOUN
cana-3460	150	9	,	,	PUNCT
cana-3460	150	10	13(2	13(2	NOUN
cana-3460	150	11	)	)	PUNCT
cana-3460	150	12	,	,	PUNCT
cana-3460	150	13	.	.	PUNCT
cana-3460	151	1	communications	communication	NOUN
cana-3460	151	2	on	on	ADP
cana-3460	151	3	applied	apply	VERB
cana-3460	151	4	nonlinear	nonlinear	ADJ
cana-3460	151	5	analysis	analysis	NOUN
cana-3460	151	6	issn	issn	NOUN
cana-3460	151	7	:	:	PUNCT
cana-3460	151	8	1074	1074	NUM
cana-3460	151	9	-	-	PUNCT
cana-3460	151	10	133x	133x	NUM
cana-3460	151	11	vol	vol	NOUN
cana-3460	151	12	32	32	NUM
cana-3460	151	13	no	no	NOUN
cana-3460	151	14	.	.	PUNCT
cana-3460	152	1	7s	7	NOUN
cana-3460	152	2	(	(	PUNCT
cana-3460	152	3	2025	2025	NUM
cana-3460	152	4	)	)	PUNCT
cana-3460	152	5	514	514	NUM
cana-3460	152	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3460	153	1	[	[	X
cana-3460	153	2	2	2	NUM
cana-3460	153	3	]	]	X
cana-3460	153	4	alexandru	alexandru	PROPN
cana-3460	153	5	-	-	PUNCT
cana-3460	153	6	costin	costin	PROPN
cana-3460	153	7	băroiu	băroiu	PROPN
cana-3460	153	8	and	and	CCONJ
cana-3460	153	9	bâra	bâra	NOUN
cana-3460	153	10	,	,	PUNCT
cana-3460	153	11	a.	a.	NOUN
cana-3460	153	12	,	,	PUNCT
cana-3460	153	13	2024	2024	NUM
cana-3460	153	14	.	.	PUNCT
cana-3460	154	1	a	a	DET
cana-3460	154	2	descriptive	descriptive	ADJ
cana-3460	154	3	-	-	PUNCT
cana-3460	154	4	predictive	predictive	ADJ
cana-3460	154	5	–	–	PUNCT
cana-3460	154	6	prescriptive	prescriptive	ADJ
cana-3460	154	7	framework	framework	NOUN
cana-3460	154	8	for	for	ADP
cana-3460	154	9	the	the	DET
cana-3460	154	10	social	social	ADJ
cana-3460	154	11	-	-	PUNCT
cana-3460	154	12	media	medium	NOUN
cana-3460	154	13	–	–	PUNCT
cana-3460	154	14	cryptocurrencies	cryptocurrencie	NOUN
cana-3460	154	15	relationship	relationship	NOUN
cana-3460	154	16	.	.	PUNCT
cana-3460	155	1	electronics	electronic	NOUN
cana-3460	155	2	,	,	PUNCT
cana-3460	155	3	13(7	13(7	NUM
cana-3460	155	4	)	)	PUNCT
cana-3460	155	5	,	,	PUNCT
cana-3460	155	6	pp	pp	ADP
cana-3460	155	7	.	.	PUNCT
cana-3460	155	8	1277	1277	NUM
cana-3460	155	9	.	.	PUNCT
cana-3460	156	1	[	[	X
cana-3460	156	2	3	3	NUM
cana-3460	156	3	]	]	X
cana-3460	156	4	alghamdi	alghamdi	NOUN
cana-3460	156	5	,	,	PUNCT
cana-3460	156	6	h.m	h.m	PROPN
cana-3460	156	7	.	.	PROPN
cana-3460	156	8	,	,	PUNCT
cana-3460	156	9	saadia	saadia	PROPN
cana-3460	156	10	h.a	h.a	PROPN
cana-3460	156	11	.	.	PROPN
cana-3460	156	12	hamza	hamza	PROPN
cana-3460	156	13	,	,	PUNCT
cana-3460	156	14	mashraqi	mashraqi	ADJ
cana-3460	156	15	,	,	PUNCT
cana-3460	156	16	a.m.	a.m.	NOUN
cana-3460	156	17	and	and	CCONJ
cana-3460	156	18	abdel	abdel	PROPN
cana-3460	156	19	-	-	PUNCT
cana-3460	156	20	khalek	khalek	PROPN
cana-3460	156	21	,	,	PUNCT
cana-3460	156	22	s.	s.	PROPN
cana-3460	156	23	,	,	PUNCT
cana-3460	156	24	2022	2022	NUM
cana-3460	156	25	.	.	PUNCT
cana-3460	156	26	seeker	seeker	NOUN
cana-3460	156	27	optimization	optimization	NOUN
cana-3460	156	28	with	with	ADP
cana-3460	156	29	deep	deep	ADJ
cana-3460	156	30	learning	learning	NOUN
cana-3460	156	31	enabled	enable	VERB
cana-3460	156	32	sentiment	sentiment	NOUN
cana-3460	156	33	analysis	analysis	NOUN
cana-3460	156	34	on	on	ADP
cana-3460	156	35	social	social	ADJ
cana-3460	156	36	media	medium	NOUN
cana-3460	156	37	.	.	PUNCT
cana-3460	157	1	computers	computer	NOUN
cana-3460	157	2	,	,	PUNCT
cana-3460	157	3	materials	material	NOUN
cana-3460	157	4	,	,	PUNCT
cana-3460	157	5	&	&	CCONJ
cana-3460	157	6	continua	continua	PROPN
cana-3460	157	7	,	,	PUNCT
cana-3460	157	8	73(3	73(3	NUM
cana-3460	157	9	)	)	PUNCT
cana-3460	157	10	,	,	PUNCT
cana-3460	157	11	pp	pp	ADP
cana-3460	157	12	.	.	PUNCT
cana-3460	158	1	5985	5985	NUM
cana-3460	158	2	-	-	SYM
cana-3460	158	3	5999	5999	NUM
cana-3460	158	4	.	.	PUNCT
cana-3460	159	1	[	[	X
cana-3460	159	2	4	4	NUM
cana-3460	159	3	]	]	PUNCT
cana-3460	159	4	almotairi	almotairi	NOUN
cana-3460	159	5	,	,	PUNCT
cana-3460	159	6	r.k	r.k	PROPN
cana-3460	159	7	.	.	PROPN
cana-3460	159	8	and	and	CCONJ
cana-3460	159	9	hadwan	hadwan	PROPN
cana-3460	159	10	,	,	PUNCT
cana-3460	159	11	m.	m.	NOUN
cana-3460	159	12	,	,	PUNCT
cana-3460	159	13	2024	2024	NUM
cana-3460	159	14	.	.	PUNCT
cana-3460	159	15	sentiment	sentiment	NOUN
cana-3460	159	16	analysis	analysis	NOUN
cana-3460	159	17	methods	method	NOUN
cana-3460	159	18	for	for	ADP
cana-3460	159	19	arabic	arabic	ADJ
cana-3460	159	20	content	content	NOUN
cana-3460	159	21	on	on	ADP
cana-3460	159	22	social	social	ADJ
cana-3460	159	23	media	medium	NOUN
cana-3460	159	24	:	:	PUNCT
cana-3460	159	25	a	a	DET
cana-3460	159	26	systematic	systematic	ADJ
cana-3460	159	27	review	review	NOUN
cana-3460	159	28	.	.	PUNCT
cana-3460	160	1	ingenierie	ingenierie	VERB
cana-3460	160	2	des	des	PROPN
cana-3460	160	3	systemes	systemes	PROPN
cana-3460	160	4	d'information	d'information	PROPN
cana-3460	160	5	,	,	PUNCT
cana-3460	160	6	29(1	29(1	NUM
cana-3460	160	7	)	)	PUNCT
cana-3460	160	8	,	,	PUNCT
cana-3460	160	9	pp	pp	ADJ
cana-3460	160	10	.	.	PUNCT
cana-3460	161	1	389	389	NUM
cana-3460	161	2	-	-	SYM
cana-3460	161	3	396	396	NUM
cana-3460	161	4	.	.	PUNCT
cana-3460	162	1	[	[	X
cana-3460	162	2	5	5	NUM
cana-3460	162	3	]	]	PUNCT
cana-3460	162	4	alotaibi	alotaibi	NOUN
cana-3460	162	5	,	,	PUNCT
cana-3460	162	6	a.	a.	NOUN
cana-3460	162	7	and	and	CCONJ
cana-3460	162	8	nadeem	nadeem	PROPN
cana-3460	162	9	,	,	PUNCT
cana-3460	162	10	f.	f.	PROPN
cana-3460	162	11	,	,	PUNCT
cana-3460	162	12	2024	2024	NUM
cana-3460	162	13	.	.	PUNCT
cana-3460	163	1	leveraging	leverage	VERB
cana-3460	163	2	social	social	ADJ
cana-3460	163	3	media	medium	NOUN
cana-3460	163	4	and	and	CCONJ
cana-3460	163	5	deep	deep	ADJ
cana-3460	163	6	learning	learning	NOUN
cana-3460	163	7	for	for	ADP
cana-3460	163	8	sentiment	sentiment	NOUN
cana-3460	163	9	analysis	analysis	NOUN
cana-3460	163	10	for	for	ADP
cana-3460	163	11	smart	smart	ADJ
cana-3460	163	12	governance	governance	NOUN
cana-3460	163	13	:	:	PUNCT
cana-3460	163	14	a	a	DET
cana-3460	163	15	case	case	NOUN
cana-3460	163	16	study	study	NOUN
cana-3460	163	17	of	of	ADP
cana-3460	163	18	public	public	ADJ
cana-3460	163	19	reactions	reaction	NOUN
cana-3460	163	20	to	to	ADP
cana-3460	163	21	educational	educational	ADJ
cana-3460	163	22	reforms	reform	NOUN
cana-3460	163	23	in	in	ADP
cana-3460	163	24	saudi	saudi	PROPN
cana-3460	163	25	arabia	arabia	PROPN
cana-3460	163	26	.	.	PUNCT
cana-3460	164	1	computers	computer	NOUN
cana-3460	164	2	,	,	PUNCT
cana-3460	164	3	13(11	13(11	NUM
cana-3460	164	4	)	)	PUNCT
cana-3460	164	5	,	,	PUNCT
cana-3460	164	6	pp	pp	ADP
cana-3460	164	7	.	.	PUNCT
cana-3460	165	1	280	280	NUM
cana-3460	165	2	.	.	PUNCT
cana-3460	166	1	[	[	X
cana-3460	166	2	6	6	NUM
cana-3460	166	3	]	]	PUNCT
cana-3460	166	4	anese	anese	PROPN
cana-3460	166	5	,	,	PUNCT
cana-3460	166	6	g.	g.	PROPN
cana-3460	166	7	,	,	PUNCT
cana-3460	166	8	corazza	corazza	PROPN
cana-3460	166	9	,	,	PUNCT
cana-3460	166	10	m.	m.	NOUN
cana-3460	166	11	,	,	PUNCT
cana-3460	166	12	costola	costola	PROPN
cana-3460	166	13	,	,	PUNCT
cana-3460	166	14	m.	m.	NOUN
cana-3460	166	15	and	and	CCONJ
cana-3460	166	16	pelizzon	pelizzon	PROPN
cana-3460	166	17	,	,	PUNCT
cana-3460	166	18	l.	l.	PROPN
cana-3460	166	19	,	,	PUNCT
cana-3460	166	20	2023	2023	NUM
cana-3460	166	21	.	.	PUNCT
cana-3460	167	1	impact	impact	NOUN
cana-3460	167	2	of	of	ADP
cana-3460	167	3	public	public	ADJ
cana-3460	167	4	news	news	NOUN
cana-3460	167	5	sentiment	sentiment	NOUN
cana-3460	167	6	on	on	ADP
cana-3460	167	7	stock	stock	NOUN
cana-3460	167	8	market	market	NOUN
cana-3460	167	9	index	index	NOUN
cana-3460	167	10	return	return	NOUN
cana-3460	167	11	and	and	CCONJ
cana-3460	167	12	volatility	volatility	NOUN
cana-3460	167	13	.	.	PUNCT
cana-3460	168	1	computational	computational	ADJ
cana-3460	168	2	management	management	NOUN
cana-3460	168	3	science	science	NOUN
cana-3460	168	4	,	,	PUNCT
cana-3460	168	5	20(1	20(1	NUM
cana-3460	168	6	)	)	PUNCT
cana-3460	168	7	,	,	PUNCT
cana-3460	168	8	pp	pp	ADJ
cana-3460	168	9	.	.	PUNCT
cana-3460	169	1	20	20	NUM
cana-3460	169	2	.	.	PUNCT
cana-3460	170	1	[	[	X
cana-3460	170	2	7	7	NUM
cana-3460	170	3	]	]	X
cana-3460	170	4	başarslan	başarslan	NOUN
cana-3460	170	5	,	,	PUNCT
cana-3460	170	6	m.s	m.s	PROPN
cana-3460	170	7	.	.	PROPN
cana-3460	170	8	and	and	CCONJ
cana-3460	170	9	kayaalp	kayaalp	PROPN
cana-3460	170	10	,	,	PUNCT
cana-3460	170	11	f.	f.	PROPN
cana-3460	170	12	,	,	PUNCT
cana-3460	170	13	2023	2023	NUM
cana-3460	170	14	.	.	PUNCT
cana-3460	171	1	mbi	mbi	NOUN
cana-3460	171	2	-	-	PUNCT
cana-3460	171	3	grumconv	grumconv	NOUN
cana-3460	171	4	:	:	PUNCT
cana-3460	171	5	a	a	DET
cana-3460	171	6	novel	novel	ADJ
cana-3460	171	7	multi	multi	ADJ
cana-3460	171	8	bi	bi	NOUN
cana-3460	171	9	-	-	NOUN
cana-3460	171	10	gru	gru	NOUN
cana-3460	171	11	and	and	CCONJ
cana-3460	171	12	multi	multi	ADJ
cana-3460	171	13	cnn	cnn	PROPN
cana-3460	171	14	-	-	PUNCT
cana-3460	171	15	based	base	VERB
cana-3460	171	16	deep	deep	ADJ
cana-3460	171	17	learning	learning	NOUN
cana-3460	171	18	model	model	NOUN
cana-3460	171	19	for	for	ADP
cana-3460	171	20	social	social	ADJ
cana-3460	171	21	media	medium	NOUN
cana-3460	171	22	sentiment	sentiment	NOUN
cana-3460	171	23	analysis	analysis	NOUN
cana-3460	171	24	.	.	PUNCT
cana-3460	172	1	journal	journal	PROPN
cana-3460	172	2	of	of	ADP
cana-3460	172	3	cloud	cloud	PROPN
cana-3460	172	4	computing	computing	NOUN
cana-3460	172	5	,	,	PUNCT
cana-3460	172	6	12(1	12(1	NUM
cana-3460	172	7	)	)	PUNCT
cana-3460	172	8	,	,	PUNCT
cana-3460	172	9	pp	pp	ADJ
cana-3460	172	10	.	.	PUNCT
cana-3460	173	1	5	5	X
cana-3460	173	2	.	.	PUNCT
cana-3460	174	1	[	[	X
cana-3460	174	2	8	8	NUM
cana-3460	174	3	]	]	X
cana-3460	174	4	bucur	bucur	NOUN
cana-3460	174	5	,	,	PUNCT
cana-3460	174	6	c.	c.	PROPN
cana-3460	174	7	,	,	PUNCT
cana-3460	174	8	tudorica	tudorica	PROPN
cana-3460	174	9	,	,	PUNCT
cana-3460	174	10	b.	b.	PROPN
cana-3460	174	11	,	,	PUNCT
cana-3460	174	12	andrei	andrei	PROPN
cana-3460	174	13	,	,	PUNCT
cana-3460	174	14	j.v	j.v	PROPN
cana-3460	174	15	.	.	PROPN
cana-3460	174	16	,	,	PUNCT
cana-3460	174	17	dusmanescu	dusmanescu	PROPN
cana-3460	174	18	,	,	PUNCT
cana-3460	174	19	d.	d.	PROPN
cana-3460	174	20	,	,	PUNCT
cana-3460	174	21	paraschiv	paraschiv	PROPN
cana-3460	174	22	,	,	PUNCT
cana-3460	174	23	d.	d.	PROPN
cana-3460	174	24	and	and	CCONJ
cana-3460	174	25	teodor	teodor	ADV
cana-3460	174	26	,	,	PUNCT
cana-3460	174	27	c.	c.	NOUN
cana-3460	174	28	,	,	PUNCT
cana-3460	174	29	2024	2024	NUM
cana-3460	174	30	.	.	PUNCT
cana-3460	174	31	sentiment	sentiment	NOUN
cana-3460	174	32	analysis	analysis	NOUN
cana-3460	174	33	of	of	ADP
cana-3460	174	34	global	global	ADJ
cana-3460	174	35	news	news	NOUN
cana-3460	174	36	on	on	ADP
cana-3460	174	37	environmental	environmental	ADJ
cana-3460	174	38	issues	issue	NOUN
cana-3460	174	39	:	:	PUNCT
cana-3460	174	40	insights	insight	NOUN
cana-3460	174	41	into	into	ADP
cana-3460	174	42	public	public	ADJ
cana-3460	174	43	perception	perception	NOUN
cana-3460	174	44	and	and	CCONJ
cana-3460	174	45	its	its	PRON
cana-3460	174	46	impact	impact	NOUN
cana-3460	174	47	on	on	ADP
cana-3460	174	48	lowcarbon	lowcarbon	NOUN
cana-3460	174	49	economy	economy	NOUN
cana-3460	174	50	transition	transition	NOUN
cana-3460	174	51	.	.	PUNCT
cana-3460	175	1	frontiers	frontier	NOUN
cana-3460	175	2	in	in	ADP
cana-3460	175	3	environmental	environmental	ADJ
cana-3460	175	4	science	science	NOUN
cana-3460	175	5	,	,	PUNCT
cana-3460	175	6	.	.	PUNCT
cana-3460	176	1	[	[	X
cana-3460	176	2	9	9	NUM
cana-3460	176	3	]	]	SYM
cana-3460	176	4	delgadillo	delgadillo	PROPN
cana-3460	176	5	,	,	PUNCT
cana-3460	176	6	j.	j.	PROPN
cana-3460	176	7	,	,	PUNCT
cana-3460	176	8	kinyua	kinyua	PROPN
cana-3460	176	9	,	,	PUNCT
cana-3460	176	10	j.	j.	PROPN
cana-3460	176	11	and	and	CCONJ
cana-3460	176	12	mutigwe	mutigwe	PROPN
cana-3460	176	13	,	,	PUNCT
cana-3460	176	14	c.	c.	PROPN
cana-3460	176	15	,	,	PUNCT
cana-3460	176	16	2024	2024	NUM
cana-3460	176	17	.	.	PUNCT
cana-3460	177	1	finsosent	finsosent	NOUN
cana-3460	177	2	:	:	PUNCT
cana-3460	177	3	advancing	advance	VERB
cana-3460	177	4	financial	financial	ADJ
cana-3460	177	5	market	market	NOUN
cana-3460	177	6	sentiment	sentiment	NOUN
cana-3460	177	7	analysis	analysis	NOUN
cana-3460	177	8	through	through	ADP
cana-3460	177	9	pretrained	pretraine	VERB
cana-3460	177	10	large	large	ADJ
cana-3460	177	11	language	language	NOUN
cana-3460	177	12	models	model	NOUN
cana-3460	177	13	.	.	PUNCT
cana-3460	178	1	big	big	ADJ
cana-3460	178	2	data	datum	NOUN
cana-3460	178	3	and	and	CCONJ
cana-3460	178	4	cognitive	cognitive	ADJ
cana-3460	178	5	computing	computing	NOUN
cana-3460	178	6	,	,	PUNCT
cana-3460	178	7	8(8	8(8	NUM
cana-3460	178	8	)	)	PUNCT
cana-3460	178	9	,	,	PUNCT
cana-3460	178	10	pp	pp	ADP
cana-3460	178	11	.	.	PUNCT
cana-3460	178	12	87	87	NUM
cana-3460	178	13	.	.	PUNCT
cana-3460	179	1	[	[	X
cana-3460	179	2	10	10	NUM
cana-3460	179	3	]	]	X
cana-3460	179	4	erick	erick	PROPN
cana-3460	179	5	,	,	PUNCT
cana-3460	179	6	o.o	o.o	PROPN
cana-3460	179	7	.	.	PROPN
cana-3460	179	8	,	,	PUNCT
cana-3460	179	9	okeyo	okeyo	PROPN
cana-3460	179	10	,	,	PUNCT
cana-3460	179	11	g.	g.	PROPN
cana-3460	179	12	and	and	CCONJ
cana-3460	179	13	kimwele	kimwele	PROPN
cana-3460	179	14	,	,	PUNCT
cana-3460	179	15	m.	m.	NOUN
cana-3460	179	16	,	,	PUNCT
cana-3460	179	17	2023	2023	NUM
cana-3460	179	18	.	.	PUNCT
cana-3460	180	1	sentiment	sentiment	NOUN
cana-3460	180	2	analysis	analysis	NOUN
cana-3460	180	3	on	on	ADP
cana-3460	180	4	social	social	ADJ
cana-3460	180	5	media	medium	NOUN
cana-3460	180	6	tweets	tweet	NOUN
cana-3460	180	7	using	use	VERB
cana-3460	180	8	dimensionality	dimensionality	NOUN
cana-3460	180	9	reduction	reduction	NOUN
cana-3460	180	10	and	and	CCONJ
cana-3460	180	11	natural	natural	ADJ
cana-3460	180	12	language	language	NOUN
cana-3460	180	13	processing	processing	NOUN
cana-3460	180	14	.	.	PUNCT
cana-3460	181	1	engineering	engineering	NOUN
cana-3460	181	2	reports	report	NOUN
cana-3460	181	3	,	,	PUNCT
cana-3460	181	4	5(3	5(3	NUM
cana-3460	181	5	)	)	PUNCT
cana-3460	181	6	,	,	PUNCT
cana-3460	181	7	.	.	PUNCT
cana-3460	182	1	[	[	X
cana-3460	182	2	11	11	NUM
cana-3460	182	3	]	]	X
cana-3460	182	4	gouthami	gouthami	NOUN
cana-3460	182	5	,	,	PUNCT
cana-3460	182	6	s.	s.	PROPN
cana-3460	182	7	and	and	CCONJ
cana-3460	182	8	hegde	hegde	PROPN
cana-3460	182	9	,	,	PUNCT
cana-3460	182	10	n.p	n.p	PROPN
cana-3460	182	11	.	.	PROPN
cana-3460	182	12	,	,	PUNCT
cana-3460	182	13	2021	2021	NUM
cana-3460	182	14	.	.	PUNCT
cana-3460	183	1	a	a	DET
cana-3460	183	2	survey	survey	NOUN
cana-3460	183	3	on	on	ADP
cana-3460	183	4	challenges	challenge	NOUN
cana-3460	183	5	and	and	CCONJ
cana-3460	183	6	techniques	technique	NOUN
cana-3460	183	7	of	of	ADP
cana-3460	183	8	sentiment	sentiment	NOUN
cana-3460	183	9	analysis	analysis	NOUN
cana-3460	183	10	.	.	PUNCT
cana-3460	184	1	turkish	turkish	ADJ
cana-3460	184	2	journal	journal	NOUN
cana-3460	184	3	of	of	ADP
cana-3460	184	4	computer	computer	NOUN
cana-3460	184	5	and	and	CCONJ
cana-3460	184	6	mathematics	mathematic	NOUN
cana-3460	184	7	education	education	NOUN
cana-3460	184	8	,	,	PUNCT
cana-3460	184	9	12(6	12(6	NUM
cana-3460	184	10	)	)	PUNCT
cana-3460	184	11	,	,	PUNCT
cana-3460	184	12	pp	pp	PROPN
cana-3460	184	13	.	.	PUNCT
cana-3460	185	1	4510	4510	NUM
cana-3460	185	2	-	-	SYM
cana-3460	185	3	4515	4515	NUM
cana-3460	185	4	.	.	PUNCT
cana-3460	186	1	[	[	X
cana-3460	186	2	12	12	NUM
cana-3460	186	3	]	]	X
cana-3460	186	4	hanny	hanny	PROPN
cana-3460	186	5	,	,	PUNCT
cana-3460	186	6	d.	d.	PROPN
cana-3460	186	7	and	and	CCONJ
cana-3460	186	8	resch	resch	PROPN
cana-3460	186	9	,	,	PUNCT
cana-3460	186	10	b.	b.	PROPN
cana-3460	186	11	,	,	PUNCT
cana-3460	186	12	2024	2024	NUM
cana-3460	186	13	.	.	PUNCT
cana-3460	186	14	clustering	clustering	NOUN
cana-3460	186	15	-	-	PUNCT
cana-3460	186	16	based	base	VERB
cana-3460	186	17	joint	joint	ADJ
cana-3460	186	18	topic	topic	NOUN
cana-3460	186	19	-	-	PUNCT
cana-3460	186	20	sentiment	sentiment	NOUN
cana-3460	186	21	modeling	modeling	NOUN
cana-3460	186	22	of	of	ADP
cana-3460	186	23	social	social	ADJ
cana-3460	186	24	media	medium	NOUN
cana-3460	186	25	data	datum	NOUN
cana-3460	186	26	:	:	PUNCT
cana-3460	186	27	a	a	DET
cana-3460	186	28	neural	neural	ADJ
cana-3460	186	29	networks	network	NOUN
cana-3460	186	30	approach	approach	NOUN
cana-3460	186	31	.	.	PUNCT
cana-3460	187	1	information	information	NOUN
cana-3460	187	2	,	,	PUNCT
cana-3460	187	3	15(4	15(4	NUM
cana-3460	187	4	)	)	PUNCT
cana-3460	187	5	,	,	PUNCT
cana-3460	187	6	pp	pp	ADP
cana-3460	187	7	.	.	PUNCT
cana-3460	188	1	200	200	NUM
cana-3460	188	2	.	.	PUNCT
cana-3460	189	1	[	[	X
cana-3460	189	2	13	13	NUM
cana-3460	189	3	]	]	PUNCT
cana-3460	189	4	horvat	horvat	NOUN
cana-3460	189	5	,	,	PUNCT
cana-3460	189	6	m.	m.	NOUN
cana-3460	189	7	,	,	PUNCT
cana-3460	189	8	gledec	gledec	PROPN
cana-3460	189	9	,	,	PUNCT
cana-3460	189	10	g.	g.	PROPN
cana-3460	189	11	and	and	CCONJ
cana-3460	189	12	leontić	leontić	PROPN
cana-3460	189	13	,	,	PUNCT
cana-3460	189	14	f.	f.	PROPN
cana-3460	189	15	,	,	PUNCT
cana-3460	189	16	2024	2024	NUM
cana-3460	189	17	.	.	PUNCT
cana-3460	189	18	hybrid	hybrid	ADJ
cana-3460	189	19	natural	natural	ADJ
cana-3460	189	20	language	language	NOUN
cana-3460	189	21	processing	processing	NOUN
cana-3460	189	22	model	model	NOUN
cana-3460	189	23	for	for	ADP
cana-3460	189	24	sentiment	sentiment	NOUN
cana-3460	189	25	analysis	analysis	NOUN
cana-3460	189	26	during	during	ADP
cana-3460	189	27	natural	natural	ADJ
cana-3460	189	28	crisis	crisis	NOUN
cana-3460	189	29	.	.	PUNCT
cana-3460	190	1	electronics	electronic	NOUN
cana-3460	190	2	,	,	PUNCT
cana-3460	190	3	13(10	13(10	NUM
cana-3460	190	4	)	)	PUNCT
cana-3460	190	5	,	,	PUNCT
cana-3460	190	6	pp	pp	ADP
cana-3460	190	7	.	.	PUNCT
cana-3460	190	8	1991	1991	NUM
cana-3460	190	9	.	.	PUNCT
cana-3460	191	1	[	[	X
cana-3460	191	2	14	14	NUM
cana-3460	191	3	]	]	X
cana-3460	191	4	jagarapu	jagarapu	PROPN
cana-3460	191	5	,	,	PUNCT
cana-3460	191	6	j.	j.	PROPN
cana-3460	191	7	,	,	PUNCT
cana-3460	191	8	diaz	diaz	PROPN
cana-3460	191	9	,	,	PUNCT
cana-3460	191	10	m.i	m.i	PROPN
cana-3460	191	11	.	.	PROPN
cana-3460	191	12	,	,	PUNCT
cana-3460	191	13	lehmann	lehmann	PROPN
cana-3460	191	14	,	,	PUNCT
cana-3460	191	15	c.u	c.u	PROPN
cana-3460	191	16	.	.	PROPN
cana-3460	191	17	and	and	CCONJ
cana-3460	191	18	medford	medford	PROPN
cana-3460	191	19	,	,	PUNCT
cana-3460	191	20	r.j	r.j	PROPN
cana-3460	191	21	.	.	PROPN
cana-3460	191	22	,	,	PUNCT
cana-3460	191	23	2023	2023	NUM
cana-3460	191	24	.	.	PUNCT
cana-3460	192	1	twitter	twitter	NOUN
cana-3460	192	2	discussions	discussion	NOUN
cana-3460	192	3	on	on	ADP
cana-3460	192	4	breastfeeding	breastfeed	VERB
cana-3460	192	5	during	during	ADP
cana-3460	192	6	the	the	DET
cana-3460	192	7	covid-19	covid-19	PROPN
cana-3460	192	8	pandemic	pandemic	NOUN
cana-3460	192	9	.	.	PUNCT
cana-3460	193	1	international	international	ADJ
cana-3460	193	2	breastfeeding	breastfeeding	NOUN
cana-3460	193	3	journal	journal	NOUN
cana-3460	193	4	,	,	PUNCT
cana-3460	193	5	18	18	NUM
cana-3460	193	6	,	,	PUNCT
cana-3460	193	7	pp	pp	ADJ
cana-3460	193	8	.	.	PUNCT
cana-3460	194	1	1	1	NUM
cana-3460	194	2	-	-	SYM
cana-3460	194	3	8	8	NUM
cana-3460	194	4	.	.	PUNCT
cana-3460	195	1	[	[	X
cana-3460	195	2	15	15	NUM
cana-3460	195	3	]	]	X
cana-3460	195	4	kanungo	kanungo	PROPN
cana-3460	195	5	,	,	PUNCT
cana-3460	195	6	s.	s.	PROPN
cana-3460	195	7	and	and	CCONJ
cana-3460	195	8	jain	jain	PROPN
cana-3460	195	9	,	,	PUNCT
cana-3460	195	10	s.	s.	PROPN
cana-3460	195	11	,	,	PUNCT
cana-3460	195	12	2023	2023	NUM
cana-3460	195	13	.	.	PUNCT
cana-3460	196	1	hybrid	hybrid	ADJ
cana-3460	196	2	deep	deep	ADJ
cana-3460	196	3	neural	neural	ADJ
cana-3460	196	4	network	network	NOUN
cana-3460	196	5	g	g	NOUN
cana-3460	196	6	-	-	PUNCT
cana-3460	196	7	lstm	lstm	NOUN
cana-3460	196	8	for	for	ADP
cana-3460	196	9	sentiment	sentiment	NOUN
cana-3460	196	10	analysis	analysis	NOUN
cana-3460	196	11	on	on	ADP
cana-3460	196	12	twitter	twitter	NOUN
cana-3460	196	13	:	:	PUNCT
cana-3460	196	14	a	a	DET
cana-3460	196	15	novel	novel	ADJ
cana-3460	196	16	approach	approach	NOUN
cana-3460	196	17	to	to	ADP
cana-3460	196	18	disaster	disaster	NOUN
cana-3460	196	19	management	management	NOUN
cana-3460	196	20	.	.	PUNCT
cana-3460	197	1	ingenierie	ingenierie	VERB
cana-3460	197	2	des	des	PROPN
cana-3460	197	3	systemes	systemes	PROPN
cana-3460	197	4	d'information	d'information	PROPN
cana-3460	197	5	,	,	PUNCT
cana-3460	197	6	28(6	28(6	NUM
cana-3460	197	7	)	)	PUNCT
cana-3460	197	8	,	,	PUNCT
cana-3460	197	9	pp	pp	PROPN
cana-3460	197	10	.	.	PUNCT
cana-3460	198	1	1565	1565	NUM
cana-3460	198	2	-	-	SYM
cana-3460	198	3	1575	1575	NUM
cana-3460	198	4	.	.	PUNCT
cana-3460	199	1	[	[	X
cana-3460	199	2	16	16	NUM
cana-3460	199	3	]	]	X
cana-3460	199	4	khan	khan	PROPN
cana-3460	199	5	,	,	PUNCT
cana-3460	199	6	t.	t.	NOUN
cana-3460	199	7	and	and	CCONJ
cana-3460	199	8	ridhorkar	ridhorkar	NOUN
cana-3460	199	9	,	,	PUNCT
cana-3460	199	10	s.	s.	PROPN
cana-3460	199	11	,	,	PUNCT
cana-3460	199	12	2024	2024	NUM
cana-3460	199	13	.	.	PUNCT
cana-3460	200	1	rmdeasd	rmdeasd	NOUN
cana-3460	200	2	:	:	PUNCT
cana-3460	200	3	integrating	integrate	VERB
cana-3460	200	4	rule	rule	NOUN
cana-3460	200	5	mining	mining	NOUN
cana-3460	200	6	and	and	CCONJ
cana-3460	200	7	deep	deep	ADJ
cana-3460	200	8	learning	learning	NOUN
cana-3460	200	9	for	for	ADP
cana-3460	200	10	enhanced	enhanced	ADJ
cana-3460	200	11	aspect	aspect	NOUN
cana-3460	200	12	-	-	PUNCT
cana-3460	200	13	based	base	VERB
cana-3460	200	14	sentiment	sentiment	NOUN
cana-3460	200	15	analysis	analysis	NOUN
cana-3460	200	16	across	across	ADP
cana-3460	200	17	diverse	diverse	ADJ
cana-3460	200	18	domains	domain	NOUN
cana-3460	200	19	.	.	PUNCT
cana-3460	201	1	journal	journal	NOUN
cana-3460	201	2	of	of	ADP
cana-3460	201	3	electrical	electrical	ADJ
cana-3460	201	4	systems	system	NOUN
cana-3460	201	5	,	,	PUNCT
cana-3460	201	6	20(3	20(3	NOUN
cana-3460	201	7	)	)	PUNCT
cana-3460	201	8	,	,	PUNCT
cana-3460	201	9	pp	pp	PROPN
cana-3460	201	10	.	.	PUNCT
cana-3460	202	1	1163	1163	NUM
cana-3460	202	2	-	-	SYM
cana-3460	202	3	1192	1192	NUM
cana-3460	202	4	.	.	PUNCT
cana-3460	203	1	[	[	X
cana-3460	203	2	17	17	NUM
cana-3460	203	3	]	]	X
cana-3460	203	4	kim	kim	PROPN
cana-3460	203	5	,	,	PUNCT
cana-3460	203	6	m.	m.	NOUN
cana-3460	203	7	,	,	PUNCT
cana-3460	203	8	kang	kang	PROPN
cana-3460	203	9	,	,	PUNCT
cana-3460	203	10	j.	j.	PROPN
cana-3460	203	11	,	,	PUNCT
cana-3460	203	12	jeon	jeon	PROPN
cana-3460	203	13	,	,	PUNCT
cana-3460	203	14	i.	i.	PROPN
cana-3460	203	15	,	,	PUNCT
cana-3460	203	16	lee	lee	PROPN
cana-3460	203	17	,	,	PUNCT
cana-3460	203	18	j.	j.	PROPN
cana-3460	203	19	,	,	PUNCT
cana-3460	203	20	park	park	PROPN
cana-3460	203	21	,	,	PUNCT
cana-3460	203	22	j.	j.	PROPN
cana-3460	203	23	,	,	PUNCT
cana-3460	203	24	youm	youm	PROPN
cana-3460	203	25	,	,	PUNCT
cana-3460	203	26	s.	s.	PROPN
cana-3460	203	27	,	,	PUNCT
cana-3460	203	28	jeong	jeong	PROPN
cana-3460	203	29	,	,	PUNCT
cana-3460	203	30	j.	j.	PROPN
cana-3460	203	31	,	,	PUNCT
cana-3460	203	32	woo	woo	PROPN
cana-3460	203	33	,	,	PUNCT
cana-3460	203	34	j.	j.	PROPN
cana-3460	203	35	and	and	CCONJ
cana-3460	203	36	moon	moon	PROPN
cana-3460	203	37	,	,	PUNCT
cana-3460	203	38	j.	j.	PROPN
cana-3460	203	39	,	,	PUNCT
cana-3460	203	40	2024	2024	NUM
cana-3460	203	41	.	.	PUNCT
cana-3460	204	1	differential	differential	ADJ
cana-3460	204	2	impacts	impact	NOUN
cana-3460	204	3	of	of	ADP
cana-3460	204	4	environmental	environmental	ADJ
cana-3460	204	5	,	,	PUNCT
cana-3460	204	6	social	social	ADJ
cana-3460	204	7	,	,	PUNCT
cana-3460	204	8	and	and	CCONJ
cana-3460	204	9	governance	governance	NOUN
cana-3460	204	10	news	news	NOUN
cana-3460	204	11	sentiment	sentiment	NOUN
cana-3460	204	12	on	on	ADP
cana-3460	204	13	corporate	corporate	ADJ
cana-3460	204	14	financial	financial	ADJ
cana-3460	204	15	performance	performance	NOUN
cana-3460	204	16	in	in	ADP
cana-3460	204	17	the	the	DET
cana-3460	204	18	global	global	ADJ
cana-3460	204	19	market	market	NOUN
cana-3460	204	20	:	:	PUNCT
cana-3460	204	21	an	an	DET
cana-3460	204	22	analysis	analysis	NOUN
cana-3460	204	23	of	of	ADP
cana-3460	204	24	dynamic	dynamic	ADJ
cana-3460	204	25	industries	industry	NOUN
cana-3460	204	26	using	use	VERB
cana-3460	204	27	advanced	advanced	ADJ
cana-3460	204	28	natural	natural	ADJ
cana-3460	204	29	language	language	NOUN
cana-3460	204	30	processing	processing	NOUN
cana-3460	204	31	models	model	NOUN
cana-3460	204	32	.	.	PUNCT
cana-3460	205	1	electronics	electronic	NOUN
cana-3460	205	2	,	,	PUNCT
cana-3460	205	3	13(22	13(22	NUM
cana-3460	205	4	)	)	PUNCT
cana-3460	205	5	,	,	PUNCT
cana-3460	205	6	pp	pp	ADJ
cana-3460	205	7	.	.	PUNCT
cana-3460	205	8	4507	4507	NUM
cana-3460	205	9	.	.	PUNCT
cana-3460	206	1	[	[	X
cana-3460	206	2	18	18	NUM
cana-3460	206	3	]	]	X
cana-3460	206	4	koena	koena	PROPN
cana-3460	206	5	,	,	PUNCT
cana-3460	206	6	r.m	r.m	PROPN
cana-3460	206	7	.	.	PROPN
cana-3460	206	8	,	,	PUNCT
cana-3460	206	9	primus	primus	PROPN
cana-3460	206	10	,	,	PUNCT
cana-3460	206	11	m.	m.	NOUN
cana-3460	206	12	and	and	CCONJ
cana-3460	206	13	celik	celik	VERB
cana-3460	206	14	,	,	PUNCT
cana-3460	206	15	t.	t.	PROPN
cana-3460	206	16	,	,	PUNCT
cana-3460	206	17	2024	2024	NUM
cana-3460	206	18	.	.	PUNCT
cana-3460	207	1	explainable	explainable	ADJ
cana-3460	207	2	pre	pre	ADJ
cana-3460	207	3	-	-	ADJ
cana-3460	207	4	trained	train	VERB
cana-3460	207	5	language	language	NOUN
cana-3460	207	6	models	model	NOUN
cana-3460	207	7	for	for	ADP
cana-3460	207	8	sentiment	sentiment	NOUN
cana-3460	207	9	analysis	analysis	NOUN
cana-3460	207	10	in	in	ADP
cana-3460	207	11	low	low	ADV
cana-3460	207	12	-	-	PUNCT
cana-3460	207	13	resourced	resource	VERB
cana-3460	207	14	languages	language	NOUN
cana-3460	207	15	.	.	PUNCT
cana-3460	208	1	big	big	ADJ
cana-3460	208	2	data	datum	NOUN
cana-3460	208	3	and	and	CCONJ
cana-3460	208	4	cognitive	cognitive	ADJ
cana-3460	208	5	computing	computing	NOUN
cana-3460	208	6	,	,	PUNCT
cana-3460	208	7	8(11	8(11	NUM
cana-3460	208	8	)	)	PUNCT
cana-3460	208	9	,	,	PUNCT
cana-3460	208	10	pp	pp	ADP
cana-3460	208	11	.	.	PUNCT
cana-3460	208	12	160	160	NUM
cana-3460	208	13	.	.	PUNCT
cana-3460	209	1	[	[	X
cana-3460	209	2	19	19	NUM
cana-3460	209	3	]	]	X
cana-3460	209	4	lau	lau	PROPN
cana-3460	209	5	,	,	PUNCT
cana-3460	209	6	n.	n.	PROPN
cana-3460	209	7	,	,	PUNCT
cana-3460	209	8	zhao	zhao	PROPN
cana-3460	209	9	,	,	PUNCT
cana-3460	209	10	x.	x.	NOUN
cana-3460	209	11	,	,	PUNCT
cana-3460	209	12	o'daffer	o'daffer	PROPN
cana-3460	209	13	,	,	PUNCT
cana-3460	209	14	a.	a.	PROPN
cana-3460	209	15	,	,	PUNCT
cana-3460	209	16	weissman	weissman	PROPN
cana-3460	209	17	,	,	PUNCT
cana-3460	209	18	h.	h.	PROPN
cana-3460	209	19	and	and	CCONJ
cana-3460	209	20	barton	barton	PROPN
cana-3460	209	21	,	,	PUNCT
cana-3460	209	22	k.	k.	PROPN
cana-3460	209	23	,	,	PUNCT
cana-3460	209	24	2024	2024	NUM
cana-3460	209	25	.	.	PUNCT
cana-3460	209	26	pediatric	pediatric	ADJ
cana-3460	209	27	cancer	cancer	NOUN
cana-3460	209	28	communication	communication	NOUN
cana-3460	209	29	on	on	ADP
cana-3460	209	30	twitter	twitter	NOUN
cana-3460	209	31	:	:	PUNCT
cana-3460	209	32	natural	natural	ADJ
cana-3460	209	33	language	language	NOUN
cana-3460	209	34	processing	processing	NOUN
cana-3460	209	35	and	and	CCONJ
cana-3460	209	36	qualitative	qualitative	ADJ
cana-3460	209	37	content	content	NOUN
cana-3460	209	38	analysis	analysis	NOUN
cana-3460	209	39	.	.	PUNCT
cana-3460	210	1	jmir	jmir	PROPN
cana-3460	210	2	cancer	cancer	PROPN
cana-3460	210	3	,	,	PUNCT
cana-3460	210	4	10	10	NUM
cana-3460	210	5	.	.	PUNCT
cana-3460	211	1	[	[	X
cana-3460	211	2	20	20	NUM
cana-3460	211	3	]	]	SYM
cana-3460	211	4	li	li	PROPN
cana-3460	211	5	,	,	PUNCT
cana-3460	211	6	z.	z.	PROPN
cana-3460	211	7	,	,	PUNCT
cana-3460	211	8	yang	yang	PROPN
cana-3460	211	9	,	,	PUNCT
cana-3460	211	10	c.	c.	PROPN
cana-3460	211	11	and	and	CCONJ
cana-3460	211	12	huang	huang	PROPN
cana-3460	211	13	,	,	PUNCT
cana-3460	211	14	c.	c.	PROPN
cana-3460	211	15	,	,	PUNCT
cana-3460	211	16	2024	2024	NUM
cana-3460	211	17	.	.	PUNCT
cana-3460	212	1	a	a	DET
cana-3460	212	2	comparative	comparative	ADJ
cana-3460	212	3	sentiment	sentiment	NOUN
cana-3460	212	4	analysis	analysis	NOUN
cana-3460	212	5	of	of	ADP
cana-3460	212	6	airline	airline	NOUN
cana-3460	212	7	customer	customer	NOUN
cana-3460	212	8	reviews	review	NOUN
cana-3460	212	9	using	use	VERB
cana-3460	212	10	bidirectional	bidirectional	ADJ
cana-3460	212	11	encoder	encoder	NOUN
cana-3460	212	12	representations	representation	NOUN
cana-3460	212	13	from	from	ADP
cana-3460	212	14	transformers	transformer	NOUN
cana-3460	212	15	(	(	PUNCT
cana-3460	212	16	bert	bert	PROPN
cana-3460	212	17	)	)	PUNCT
cana-3460	212	18	and	and	CCONJ
cana-3460	212	19	its	its	PRON
cana-3460	212	20	variants	variant	NOUN
cana-3460	212	21	.	.	PUNCT
cana-3460	213	1	mathematics	mathematic	NOUN
cana-3460	213	2	,	,	PUNCT
cana-3460	213	3	12(1	12(1	NUM
cana-3460	213	4	)	)	PUNCT
cana-3460	213	5	,	,	PUNCT
cana-3460	213	6	pp	pp	ADP
cana-3460	213	7	.	.	PUNCT
cana-3460	214	1	53	53	NUM
cana-3460	214	2	.	.	PUNCT
cana-3460	215	1	[	[	X
cana-3460	215	2	21	21	NUM
cana-3460	215	3	]	]	X
cana-3460	215	4	liang	liang	PROPN
cana-3460	215	5	-	-	PUNCT
cana-3460	215	6	chin	chin	PROPN
cana-3460	215	7	,	,	PUNCT
cana-3460	215	8	h.	h.	PROPN
cana-3460	215	9	,	,	PUNCT
cana-3460	215	10	eiden	eiden	VERB
cana-3460	215	11	,	,	PUNCT
cana-3460	215	12	a.l	a.l	PROPN
cana-3460	215	13	.	.	PROPN
cana-3460	215	14	,	,	PUNCT
cana-3460	215	15	long	long	ADV
cana-3460	215	16	,	,	PUNCT
cana-3460	215	17	h.	h.	PROPN
cana-3460	215	18	,	,	PUNCT
cana-3460	215	19	annan	annan	PROPN
cana-3460	215	20	,	,	PUNCT
cana-3460	215	21	a.	a.	PROPN
cana-3460	215	22	,	,	PUNCT
cana-3460	215	23	wang	wang	PROPN
cana-3460	215	24	,	,	PUNCT
cana-3460	215	25	s.	s.	PROPN
cana-3460	215	26	,	,	PUNCT
cana-3460	215	27	wang	wang	PROPN
cana-3460	215	28	,	,	PUNCT
cana-3460	215	29	j.	j.	PROPN
cana-3460	215	30	,	,	PUNCT
cana-3460	215	31	manion	manion	NOUN
cana-3460	215	32	,	,	PUNCT
cana-3460	215	33	f.j	f.j	PROPN
cana-3460	215	34	.	.	PROPN
cana-3460	215	35	,	,	PUNCT
cana-3460	215	36	wang	wang	PROPN
cana-3460	215	37	,	,	PUNCT
cana-3460	215	38	x.	x.	PROPN
cana-3460	215	39	,	,	PUNCT
cana-3460	215	40	du	du	PROPN
cana-3460	215	41	,	,	PUNCT
cana-3460	215	42	j.	j.	PROPN
cana-3460	215	43	and	and	CCONJ
cana-3460	215	44	yao	yao	PROPN
cana-3460	215	45	,	,	PUNCT
cana-3460	215	46	l.	l.	PROPN
cana-3460	215	47	,	,	PUNCT
cana-3460	215	48	2024	2024	NUM
cana-3460	215	49	.	.	PUNCT
cana-3460	215	50	natural	natural	ADJ
cana-3460	215	51	language	language	NOUN
cana-3460	215	52	processing	processing	NOUN
cana-3460	215	53	–	–	PUNCT
cana-3460	215	54	powered	power	VERB
cana-3460	215	55	real	real	ADJ
cana-3460	215	56	-	-	PUNCT
cana-3460	215	57	time	time	NOUN
cana-3460	215	58	monitoring	monitoring	NOUN
cana-3460	215	59	solution	solution	NOUN
cana-3460	215	60	for	for	ADP
cana-3460	215	61	vaccine	vaccine	NOUN
cana-3460	215	62	sentiments	sentiment	NOUN
cana-3460	215	63	and	and	CCONJ
cana-3460	215	64	hesitancy	hesitancy	NOUN
cana-3460	215	65	on	on	ADP
cana-3460	215	66	social	social	ADJ
cana-3460	215	67	media	medium	NOUN
cana-3460	215	68	:	:	PUNCT
cana-3460	215	69	system	system	NOUN
cana-3460	215	70	development	development	NOUN
cana-3460	215	71	and	and	CCONJ
cana-3460	215	72	validation	validation	NOUN
cana-3460	215	73	.	.	PUNCT
cana-3460	216	1	jmir	jmir	PROPN
cana-3460	216	2	medical	medical	PROPN
cana-3460	216	3	informatics	informatics	PROPN
cana-3460	216	4	,	,	PUNCT
cana-3460	216	5	12	12	NUM
cana-3460	216	6	.	.	PUNCT
cana-3460	217	1	[	[	X
cana-3460	217	2	22	22	NUM
cana-3460	217	3	]	]	X
cana-3460	217	4	liu	liu	PROPN
cana-3460	217	5	,	,	PUNCT
cana-3460	217	6	j.	j.	PROPN
cana-3460	217	7	,	,	PUNCT
cana-3460	217	8	xu	xu	PROPN
cana-3460	217	9	,	,	PUNCT
cana-3460	217	10	f.	f.	PROPN
cana-3460	217	11	and	and	CCONJ
cana-3460	217	12	liu	liu	PROPN
cana-3460	217	13	,	,	PUNCT
cana-3460	217	14	x.	x.	NOUN
cana-3460	217	15	,	,	PUNCT
cana-3460	217	16	2024	2024	NUM
cana-3460	217	17	.	.	PUNCT
cana-3460	218	1	financial	financial	ADJ
cana-3460	218	2	market	market	NOUN
cana-3460	218	3	sentiment	sentiment	NOUN
cana-3460	218	4	analysis	analysis	NOUN
cana-3460	218	5	and	and	CCONJ
cana-3460	218	6	investment	investment	NOUN
cana-3460	218	7	strategy	strategy	NOUN
cana-3460	218	8	formulation	formulation	NOUN
cana-3460	218	9	based	base	VERB
cana-3460	218	10	on	on	ADP
cana-3460	218	11	social	social	ADJ
cana-3460	218	12	network	network	NOUN
cana-3460	218	13	data	datum	NOUN
cana-3460	218	14	.	.	PUNCT
cana-3460	219	1	journal	journal	PROPN
cana-3460	219	2	of	of	ADP
cana-3460	219	3	electrical	electrical	ADJ
cana-3460	219	4	systems	system	NOUN
cana-3460	219	5	,	,	PUNCT
cana-3460	219	6	20(9	20(9	NUM
cana-3460	219	7	)	)	PUNCT
cana-3460	219	8	,	,	PUNCT
cana-3460	219	9	pp	pp	PROPN
cana-3460	219	10	.	.	PUNCT
cana-3460	220	1	655	655	NUM
cana-3460	220	2	-	-	SYM
cana-3460	220	3	660	660	NUM
cana-3460	220	4	.	.	PUNCT
cana-3460	221	1	[	[	X
cana-3460	221	2	23	23	NUM
cana-3460	221	3	]	]	X
cana-3460	221	4	liu	liu	PROPN
cana-3460	221	5	,	,	PUNCT
cana-3460	221	6	p.	p.	NOUN
cana-3460	221	7	,	,	PUNCT
cana-3460	221	8	2024	2024	NUM
cana-3460	221	9	.	.	PUNCT
cana-3460	222	1	consumer	consumer	NOUN
cana-3460	222	2	behavior	behavior	NOUN
cana-3460	222	3	prediction	prediction	NOUN
cana-3460	222	4	and	and	CCONJ
cana-3460	222	5	market	market	NOUN
cana-3460	222	6	application	application	NOUN
cana-3460	222	7	exploration	exploration	NOUN
cana-3460	222	8	based	base	VERB
cana-3460	222	9	on	on	ADP
cana-3460	222	10	social	social	ADJ
cana-3460	222	11	network	network	NOUN
cana-3460	222	12	data	datum	NOUN
cana-3460	222	13	analysis	analysis	NOUN
cana-3460	222	14	.	.	PUNCT
cana-3460	223	1	journal	journal	NOUN
cana-3460	223	2	of	of	ADP
cana-3460	223	3	electrical	electrical	ADJ
cana-3460	223	4	systems	system	NOUN
cana-3460	223	5	,	,	PUNCT
cana-3460	223	6	20(6	20(6	NOUN
cana-3460	223	7	)	)	PUNCT
cana-3460	223	8	,	,	PUNCT
cana-3460	223	9	pp	pp	PROPN
cana-3460	223	10	.	.	PUNCT
cana-3460	223	11	806	806	NUM
cana-3460	223	12	-	-	SYM
cana-3460	223	13	811	811	NUM
cana-3460	223	14	.	.	PUNCT
cana-3460	224	1	communications	communication	NOUN
cana-3460	224	2	on	on	ADP
cana-3460	224	3	applied	apply	VERB
cana-3460	224	4	nonlinear	nonlinear	ADJ
cana-3460	224	5	analysis	analysis	NOUN
cana-3460	224	6	issn	issn	NOUN
cana-3460	224	7	:	:	PUNCT
cana-3460	224	8	1074	1074	NUM
cana-3460	224	9	-	-	PUNCT
cana-3460	224	10	133x	133x	NUM
cana-3460	224	11	vol	vol	NOUN
cana-3460	224	12	32	32	NUM
cana-3460	224	13	no	no	NOUN
cana-3460	224	14	.	.	PUNCT
cana-3460	225	1	7s	7	NOUN
cana-3460	225	2	(	(	PUNCT
cana-3460	225	3	2025	2025	NUM
cana-3460	225	4	)	)	PUNCT
cana-3460	225	5	515	515	NUM
cana-3460	225	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3460	226	1	[	[	X
cana-3460	226	2	24	24	NUM
cana-3460	226	3	]	]	SYM
cana-3460	226	4	liyanage	liyanage	NOUN
cana-3460	226	5	,	,	PUNCT
cana-3460	226	6	d.k	d.k	PROPN
cana-3460	226	7	.	.	PROPN
cana-3460	226	8	,	,	PUNCT
cana-3460	226	9	malluwawadu	malluwawadu	PROPN
cana-3460	226	10	,	,	PUNCT
cana-3460	226	11	k.t	k.t	PROPN
cana-3460	226	12	.	.	PROPN
cana-3460	226	13	,	,	PUNCT
cana-3460	226	14	rathnayake	rathnayake	PROPN
cana-3460	226	15	r.m.t.p	r.m.t.p	PROPN
cana-3460	226	16	.	.	PROPN
cana-3460	226	17	,	,	PUNCT
cana-3460	226	18	vitharana	vitharana	PROPN
cana-3460	226	19	,	,	PUNCT
cana-3460	226	20	y.b	y.b	PROPN
cana-3460	226	21	.	.	PROPN
cana-3460	226	22	,	,	PUNCT
cana-3460	226	23	tissera	tissera	PROPN
cana-3460	226	24	,	,	PUNCT
cana-3460	226	25	w.	w.	NOUN
cana-3460	226	26	and	and	CCONJ
cana-3460	226	27	panduwawala	panduwawala	ADJ
cana-3460	226	28	,	,	PUNCT
cana-3460	226	29	p.	p.	NOUN
cana-3460	226	30	,	,	PUNCT
cana-3460	226	31	2023	2023	NUM
cana-3460	226	32	.	.	PUNCT
cana-3460	227	1	increasing	increase	VERB
cana-3460	227	2	the	the	DET
cana-3460	227	3	productivity	productivity	NOUN
cana-3460	227	4	and	and	CCONJ
cana-3460	227	5	production	production	NOUN
cana-3460	227	6	of	of	ADP
cana-3460	227	7	the	the	DET
cana-3460	227	8	apparel	apparel	NOUN
cana-3460	227	9	industry	industry	NOUN
cana-3460	227	10	using	use	VERB
cana-3460	227	11	social	social	ADJ
cana-3460	227	12	media	medium	NOUN
cana-3460	227	13	platform	platform	NOUN
cana-3460	227	14	.	.	PUNCT
cana-3460	228	1	international	international	ADJ
cana-3460	228	2	research	research	PROPN
cana-3460	228	3	journal	journal	NOUN
cana-3460	228	4	of	of	ADP
cana-3460	228	5	innovations	innovation	NOUN
cana-3460	228	6	in	in	ADP
cana-3460	228	7	engineering	engineering	NOUN
cana-3460	228	8	and	and	CCONJ
cana-3460	228	9	technology	technology	NOUN
cana-3460	228	10	,	,	PUNCT
cana-3460	228	11	7(10	7(10	NUM
cana-3460	228	12	)	)	PUNCT
cana-3460	228	13	,	,	PUNCT
cana-3460	228	14	pp	pp	ADJ
cana-3460	228	15	.	.	PUNCT
cana-3460	228	16	154161	154161	NUM
cana-3460	228	17	.	.	PUNCT
cana-3460	229	1	[	[	X
cana-3460	229	2	25	25	NUM
cana-3460	229	3	]	]	PUNCT
cana-3460	229	4	mandava	mandava	NOUN
cana-3460	229	5	,	,	PUNCT
cana-3460	229	6	s.	s.	PROPN
cana-3460	229	7	,	,	PUNCT
cana-3460	229	8	oyer	oyer	NOUN
cana-3460	229	9	,	,	PUNCT
cana-3460	229	10	s.l	s.l	PROPN
cana-3460	229	11	.	.	PROPN
cana-3460	229	12	and	and	CCONJ
cana-3460	229	13	park	park	PROPN
cana-3460	229	14	,	,	PUNCT
cana-3460	229	15	s.s	s.s	PROPN
cana-3460	229	16	.	.	PROPN
cana-3460	229	17	,	,	PUNCT
cana-3460	229	18	2024	2024	NUM
cana-3460	229	19	.	.	PUNCT
cana-3460	230	1	a	a	DET
cana-3460	230	2	quantitative	quantitative	ADJ
cana-3460	230	3	analysis	analysis	NOUN
cana-3460	230	4	of	of	ADP
cana-3460	230	5	twitter	twitter	NOUN
cana-3460	230	6	(	(	PUNCT
cana-3460	230	7	“	"	PUNCT
cana-3460	230	8	x	x	NOUN
cana-3460	230	9	”	"	PUNCT
cana-3460	230	10	)	)	PUNCT
cana-3460	230	11	trends	trend	NOUN
cana-3460	230	12	in	in	ADP
cana-3460	230	13	the	the	DET
cana-3460	230	14	discussion	discussion	NOUN
cana-3460	230	15	of	of	ADP
cana-3460	230	16	rhinoplasty	rhinoplasty	NOUN
cana-3460	230	17	.	.	PUNCT
cana-3460	231	1	laryngoscope	laryngoscope	NOUN
cana-3460	231	2	investigative	investigative	ADJ
cana-3460	231	3	otolaryngology	otolaryngology	NOUN
cana-3460	231	4	,	,	PUNCT
cana-3460	231	5	9(1	9(1	NUM
cana-3460	231	6	)	)	PUNCT
cana-3460	231	7	,	,	PUNCT
cana-3460	231	8	.	.	PUNCT
cana-3460	232	1	[	[	X
cana-3460	232	2	26	26	NUM
cana-3460	232	3	]	]	X
cana-3460	232	4	miah	miah	PROPN
cana-3460	232	5	,	,	PUNCT
cana-3460	232	6	m.s.u	m.s.u	NOUN
cana-3460	232	7	.	.	PROPN
cana-3460	232	8	,	,	PUNCT
cana-3460	232	9	kabir	kabir	PROPN
cana-3460	232	10	,	,	PUNCT
cana-3460	232	11	m.m	m.m	PROPN
cana-3460	232	12	.	.	PROPN
cana-3460	232	13	,	,	PUNCT
cana-3460	232	14	sarwar	sarwar	PROPN
cana-3460	232	15	,	,	PUNCT
cana-3460	232	16	t.b	t.b	PROPN
cana-3460	232	17	.	.	PROPN
cana-3460	232	18	,	,	PUNCT
cana-3460	232	19	safran	safran	NOUN
cana-3460	232	20	,	,	PUNCT
cana-3460	232	21	m.	m.	NOUN
cana-3460	232	22	,	,	PUNCT
cana-3460	232	23	alfarhood	alfarhood	PROPN
cana-3460	232	24	,	,	PUNCT
cana-3460	232	25	s.	s.	PROPN
cana-3460	232	26	and	and	CCONJ
cana-3460	232	27	mridha	mridha	PROPN
cana-3460	232	28	,	,	PUNCT
cana-3460	232	29	m.f	m.f	PROPN
cana-3460	232	30	.	.	PROPN
cana-3460	232	31	,	,	PUNCT
cana-3460	232	32	2024	2024	NUM
cana-3460	232	33	.	.	PUNCT
cana-3460	233	1	a	a	DET
cana-3460	233	2	multimodal	multimodal	ADJ
cana-3460	233	3	approach	approach	NOUN
cana-3460	233	4	to	to	ADP
cana-3460	233	5	cross	cross	ADJ
cana-3460	233	6	-	-	ADJ
cana-3460	233	7	lingual	lingual	ADJ
cana-3460	233	8	sentiment	sentiment	NOUN
cana-3460	233	9	analysis	analysis	NOUN
cana-3460	233	10	with	with	ADP
cana-3460	233	11	ensemble	ensemble	ADJ
cana-3460	233	12	of	of	ADP
cana-3460	233	13	transformer	transformer	NOUN
cana-3460	233	14	and	and	CCONJ
cana-3460	233	15	llm	llm	NOUN
cana-3460	233	16	.	.	PUNCT
cana-3460	234	1	scientific	scientific	ADJ
cana-3460	234	2	reports	report	NOUN
cana-3460	234	3	(	(	PUNCT
cana-3460	234	4	nature	nature	NOUN
cana-3460	234	5	publisher	publisher	NOUN
cana-3460	234	6	group	group	PROPN
cana-3460	234	7	)	)	PUNCT
cana-3460	234	8	,	,	PUNCT
cana-3460	234	9	14(1	14(1	NUM
cana-3460	234	10	)	)	PUNCT
cana-3460	234	11	,	,	PUNCT
cana-3460	234	12	pp	pp	ADJ
cana-3460	234	13	.	.	PUNCT
cana-3460	234	14	9603	9603	NUM
cana-3460	234	15	.	.	PUNCT
cana-3460	235	1	[	[	X
cana-3460	235	2	27	27	NUM
cana-3460	235	3	]	]	X
cana-3460	235	4	mirugwe	mirugwe	PROPN
cana-3460	235	5	,	,	PUNCT
cana-3460	235	6	a.	a.	PROPN
cana-3460	235	7	,	,	PUNCT
cana-3460	235	8	ashaba	ashaba	PROPN
cana-3460	235	9	,	,	PUNCT
cana-3460	235	10	c.	c.	PROPN
cana-3460	235	11	,	,	PUNCT
cana-3460	235	12	namale	namale	NOUN
cana-3460	235	13	,	,	PUNCT
cana-3460	235	14	a.	a.	NOUN
cana-3460	235	15	,	,	PUNCT
cana-3460	235	16	akello	akello	PROPN
cana-3460	235	17	,	,	PUNCT
cana-3460	235	18	e.	e.	PROPN
cana-3460	235	19	,	,	PUNCT
cana-3460	235	20	bichetero	bichetero	PROPN
cana-3460	235	21	,	,	PUNCT
cana-3460	235	22	e.	e.	PROPN
cana-3460	235	23	,	,	PUNCT
cana-3460	235	24	kansiime	kansiime	PROPN
cana-3460	235	25	,	,	PUNCT
cana-3460	235	26	e.	e.	PROPN
cana-3460	235	27	and	and	CCONJ
cana-3460	235	28	nyirenda	nyirenda	PROPN
cana-3460	235	29	,	,	PUNCT
cana-3460	235	30	j.	j.	PROPN
cana-3460	235	31	,	,	PUNCT
cana-3460	235	32	2024	2024	NUM
cana-3460	235	33	.	.	PUNCT
cana-3460	235	34	sentiment	sentiment	NOUN
cana-3460	235	35	analysis	analysis	NOUN
cana-3460	235	36	of	of	ADP
cana-3460	235	37	social	social	ADJ
cana-3460	235	38	media	medium	NOUN
cana-3460	235	39	data	datum	NOUN
cana-3460	235	40	on	on	ADP
cana-3460	235	41	ebola	ebola	PROPN
cana-3460	235	42	outbreak	outbreak	NOUN
cana-3460	235	43	using	use	VERB
cana-3460	235	44	deep	deep	ADJ
cana-3460	235	45	learning	learning	NOUN
cana-3460	235	46	classifiers	classifier	NOUN
cana-3460	235	47	.	.	PUNCT
cana-3460	236	1	life	life	NOUN
cana-3460	236	2	,	,	PUNCT
cana-3460	236	3	14(6	14(6	NOUN
cana-3460	236	4	)	)	PUNCT
cana-3460	236	5	,	,	PUNCT
cana-3460	236	6	pp	pp	PROPN
cana-3460	236	7	.	.	PUNCT
cana-3460	236	8	708	708	NUM
cana-3460	236	9	.	.	PUNCT
cana-3460	237	1	[	[	X
cana-3460	237	2	28	28	NUM
cana-3460	237	3	]	]	SYM
cana-3460	237	4	nakka	nakka	PROPN
cana-3460	237	5	,	,	PUNCT
cana-3460	237	6	r.	r.	PROPN
cana-3460	237	7	,	,	PUNCT
cana-3460	237	8	talasila	talasila	NOUN
cana-3460	237	9	,	,	PUNCT
cana-3460	237	10	s.l	s.l	PROPN
cana-3460	237	11	.	.	PROPN
cana-3460	237	12	,	,	PUNCT
cana-3460	237	13	priyanka	priyanka	PROPN
cana-3460	237	14	,	,	PUNCT
cana-3460	237	15	d.	d.	PROPN
cana-3460	237	16	,	,	PUNCT
cana-3460	237	17	nallagatla	nallagatla	NOUN
cana-3460	237	18	,	,	PUNCT
cana-3460	237	19	r.s	r.s	PROPN
cana-3460	237	20	.	.	PROPN
cana-3460	237	21	,	,	PUNCT
cana-3460	237	22	surapaneni	surapaneni	NOUN
cana-3460	237	23	,	,	PUNCT
cana-3460	237	24	p.p	p.p	PROPN
cana-3460	237	25	.	.	PROPN
cana-3460	237	26	and	and	CCONJ
cana-3460	237	27	sirisha	sirisha	PROPN
cana-3460	237	28	,	,	PUNCT
cana-3460	237	29	u.	u.	NOUN
cana-3460	237	30	,	,	PUNCT
cana-3460	237	31	2024	2024	NUM
cana-3460	237	32	.	.	PUNCT
cana-3460	238	1	lambda	lambda	NOUN
cana-3460	238	2	:	:	PUNCT
cana-3460	238	3	lexicon	lexicon	NOUN
cana-3460	238	4	and	and	CCONJ
cana-3460	238	5	aspect	aspect	NOUN
cana-3460	238	6	-	-	PUNCT
cana-3460	238	7	based	base	VERB
cana-3460	238	8	multimodal	multimodal	NOUN
cana-3460	238	9	data	datum	NOUN
cana-3460	238	10	analysis	analysis	NOUN
cana-3460	238	11	of	of	ADP
cana-3460	238	12	tweet	tweet	NOUN
cana-3460	238	13	.	.	PUNCT
cana-3460	239	1	ingenierie	ingenierie	VERB
cana-3460	239	2	des	des	PROPN
cana-3460	239	3	systemes	systemes	PROPN
cana-3460	239	4	d'information	d'information	PROPN
cana-3460	239	5	,	,	PUNCT
cana-3460	239	6	29(3	29(3	NUM
cana-3460	239	7	)	)	PUNCT
cana-3460	239	8	,	,	PUNCT
cana-3460	239	9	pp	pp	ADP
cana-3460	239	10	.	.	PUNCT
cana-3460	240	1	1097	1097	NUM
cana-3460	240	2	-	-	SYM
cana-3460	240	3	1106	1106	NUM
cana-3460	240	4	.	.	PUNCT
cana-3460	241	1	[	[	X
cana-3460	241	2	29	29	NUM
cana-3460	241	3	]	]	SYM
cana-3460	241	4	nhp	nhp	PROPN
cana-3460	241	5	,	,	PUNCT
cana-3460	241	6	r.s	r.s	PROPN
cana-3460	241	7	.	.	PROPN
cana-3460	241	8	,	,	PUNCT
cana-3460	241	9	chathurika	chathurika	PROPN
cana-3460	241	10	,	,	PUNCT
cana-3460	241	11	b.	b.	PROPN
cana-3460	241	12	,	,	PUNCT
cana-3460	241	13	subasinghe	subasinghe	PROPN
cana-3460	241	14	b.n.w	b.n.w	NOUN
cana-3460	241	15	,	,	PUNCT
cana-3460	241	16	aththanayake	aththanayake	PROPN
cana-3460	241	17	,	,	PUNCT
cana-3460	241	18	k.a	k.a	PROPN
cana-3460	241	19	.	.	PROPN
cana-3460	241	20	,	,	PUNCT
cana-3460	241	21	waidyarathna	waidyarathna	VERB
cana-3460	241	22	w.d.m.u.p	w.d.m.u.p	NOUN
cana-3460	241	23	and	and	CCONJ
cana-3460	241	24	asahara	asahara	PROPN
cana-3460	241	25	,	,	PUNCT
cana-3460	241	26	g.a	g.a	PROPN
cana-3460	241	27	.	.	PROPN
cana-3460	241	28	,	,	PUNCT
cana-3460	241	29	2023	2023	NUM
cana-3460	241	30	.	.	PUNCT
cana-3460	242	1	sentiment	sentiment	NOUN
cana-3460	242	2	analysis	analysis	NOUN
cana-3460	242	3	in	in	ADP
cana-3460	242	4	social	social	ADJ
cana-3460	242	5	media	medium	NOUN
cana-3460	242	6	data	datum	NOUN
cana-3460	242	7	for	for	ADP
cana-3460	242	8	depression	depression	NOUN
cana-3460	242	9	detection	detection	NOUN
cana-3460	242	10	system	system	NOUN
cana-3460	242	11	.	.	PUNCT
cana-3460	243	1	international	international	ADJ
cana-3460	243	2	research	research	PROPN
cana-3460	243	3	journal	journal	NOUN
cana-3460	243	4	of	of	ADP
cana-3460	243	5	innovations	innovation	NOUN
cana-3460	243	6	in	in	ADP
cana-3460	243	7	engineering	engineering	NOUN
cana-3460	243	8	and	and	CCONJ
cana-3460	243	9	technology	technology	NOUN
cana-3460	243	10	,	,	PUNCT
cana-3460	243	11	7(10	7(10	NUM
cana-3460	243	12	)	)	PUNCT
cana-3460	243	13	,	,	PUNCT
cana-3460	243	14	pp	pp	PROPN
cana-3460	243	15	.	.	PUNCT
cana-3460	244	1	639	639	NUM
cana-3460	244	2	-	-	SYM
cana-3460	244	3	647	647	NUM
cana-3460	244	4	.	.	PUNCT
cana-3460	245	1	[	[	X
cana-3460	245	2	30	30	NUM
cana-3460	245	3	]	]	X
cana-3460	245	4	olaniyan	olaniyan	ADJ
cana-3460	245	5	,	,	PUNCT
cana-3460	245	6	d.	d.	PROPN
cana-3460	245	7	,	,	PUNCT
cana-3460	245	8	ogundokun	ogundokun	PROPN
cana-3460	245	9	,	,	PUNCT
cana-3460	245	10	r.o	r.o	PROPN
cana-3460	245	11	.	.	PROPN
cana-3460	245	12	,	,	PUNCT
cana-3460	245	13	olorunfemi	olorunfemi	PROPN
cana-3460	245	14	,	,	PUNCT
cana-3460	245	15	p.b	p.b	PROPN
cana-3460	245	16	.	.	PROPN
cana-3460	245	17	,	,	PUNCT
cana-3460	245	18	olaniyan	olaniyan	ADJ
cana-3460	245	19	,	,	PUNCT
cana-3460	245	20	j.	j.	PROPN
cana-3460	245	21	,	,	PUNCT
cana-3460	245	22	maskeliūnas	maskeliūnas	PROPN
cana-3460	245	23	,	,	PUNCT
cana-3460	245	24	r.	r.	PROPN
cana-3460	245	25	and	and	CCONJ
cana-3460	245	26	hakeem	hakeem	PROPN
cana-3460	245	27	,	,	PUNCT
cana-3460	245	28	b.a	b.a	PROPN
cana-3460	245	29	.	.	PROPN
cana-3460	245	30	,	,	PUNCT
cana-3460	245	31	2023	2023	NUM
cana-3460	245	32	.	.	PUNCT
cana-3460	246	1	utilizing	utilize	VERB
cana-3460	246	2	an	an	DET
cana-3460	246	3	attention	attention	NOUN
cana-3460	246	4	-	-	PUNCT
cana-3460	246	5	based	base	VERB
cana-3460	246	6	lstm	lstm	NOUN
cana-3460	246	7	model	model	NOUN
cana-3460	246	8	for	for	ADP
cana-3460	246	9	detecting	detect	VERB
cana-3460	246	10	sarcasm	sarcasm	NOUN
cana-3460	246	11	and	and	CCONJ
cana-3460	246	12	irony	irony	NOUN
cana-3460	246	13	in	in	ADP
cana-3460	246	14	social	social	ADJ
cana-3460	246	15	media	medium	NOUN
cana-3460	246	16	.	.	PUNCT
cana-3460	247	1	computers	computer	NOUN
cana-3460	247	2	,	,	PUNCT
cana-3460	247	3	12(11	12(11	NUM
cana-3460	247	4	)	)	PUNCT
cana-3460	247	5	,	,	PUNCT
cana-3460	247	6	pp	pp	ADJ
cana-3460	247	7	.	.	PUNCT
cana-3460	247	8	231	231	NUM
cana-3460	247	9	.	.	PUNCT