Understanding the role of Emojis for emotion detection in Tamil

Rajalakshmi, R; Mattins R, F; Selvaraj, S; Shibani, A; Kumar M, A; Raja Chakravarthi, B

Understanding the role of Emojis for emotion detection in Tamil

Rajalakshmi, R Mattins R, F Selvaraj, S Shibani, A Kumar M, A Raja Chakravarthi, B

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Publisher:: Association for Computational Linguistics
Publication Type:: Conference Proceeding
Citation:: Proceedings of the First Workshop on Multimodal Machine Learning in Low-resource Languages, 2022, pp. 9-17
Issue Date:: 2022-12

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Field	Value	Language
dc.contributor.author	Rajalakshmi, R
dc.contributor.author	Mattins R, F
dc.contributor.author	Selvaraj, S
dc.contributor.author	Shibani, A
dc.contributor.author	Kumar M, A
dc.contributor.author	Raja Chakravarthi, B
dc.date.accessioned	2023-03-31T12:26:46Z
dc.date.available	2023-03-31T12:26:46Z
dc.date.issued	2022-12
dc.identifier.citation	Proceedings of the First Workshop on Multimodal Machine Learning in Low-resource Languages, 2022, pp. 9-17
dc.identifier.uri	http://hdl.handle.net/10453/169029
dc.description.abstract	of expressing relevant idea through social media platforms and forums. At the same time, these memes are trolled by a person who tries to get identified from the other internet users like social media users, chat rooms and blogs. The memes contain both textual and visual information. Based on the content of memes, they are trolled in online community. There is no restriction for language usage in online media. The present work focuses on whether memes are trolled or not trolled. The proposed multi modal approach achieved considerably better weighted average F1 score of 0.5437 compared to Unimodal approaches. The other performance metrics like precision, recall, accuracy and macro average have also been studied to observe the proposed system.
dc.language	en
dc.publisher	Association for Computational Linguistics
dc.relation.ispartof	Proceedings of the First Workshop on Multimodal Machine Learning in Low-resource Languages
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Understanding the role of Emojis for emotion detection in Tamil
dc.type	Conference Proceeding
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Provost
pubs.organisational-group	/University of Technology Sydney/Provost/TD School
utslib.copyright.status	closed_access	*
dc.date.updated	2023-03-31T12:26:45Z
pubs.place-of-publication	IIIT Delhi, New Delhi, India
dc.location	IIIT Delhi, New Delhi, India

Abstract:

of expressing relevant idea through social media platforms and forums. At the same time, these memes are trolled by a person who tries to get identified from the other internet users like social media users, chat rooms and blogs. The memes contain both textual and visual information. Based on the content of memes, they are trolled in online community. There is no restriction for language usage in online media. The present work focuses on whether memes are trolled or not trolled. The proposed multi modal approach achieved considerably better weighted average F1 score of 0.5437 compared to Unimodal approaches. The other performance metrics like precision, recall, accuracy and macro average have also been studied to observe the proposed system.

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http://hdl.handle.net/10453/169029