Bits2020@ Dravidian-CodeMix-FIRE2020: Sub-Word Level Sentiment Analysis of Dravidian Code Mixed Data

Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16389

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DC Field	Value	Language
dc.contributor.author	Sharma, Yashvardhan	-
dc.date.accessioned	2024-11-15T07:04:35Z	-
dc.date.available	2024-11-15T07:04:35Z	-
dc.date.issued	2020	-
dc.identifier.uri	https://www.academia.edu/download/88147088/T4-4.pdf	-
dc.identifier.uri	http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16389	-
dc.description.abstract	This paper presents the methodologies implemented while classifying Dravidian code-mixed comments according to their polarity in the evaluation of the track ‘Sentiment Analysis for Davidian Languages in Code-Mixed Text’ proposed by Forum of Information Retrieval Evaluation in 2020. The implemented method used a sub-word level representation to capture the sentiment of the text. Using a Long Short Term Memory (LSTM) network along with language-specific preprocessing, the model classified the text according to its polarity. With F1-scores of 0.61 and 0.60, the model achieved an overall rank of 5 and 12 in the Tamil and Malayalam tasks respectively.	en_US
dc.language.iso	en	en_US
dc.publisher	CEUR-WS	en_US
dc.subject	Computer Science	en_US
dc.subject	Sentiment analysis	en_US
dc.subject	Recurrent neural networks	en_US
dc.subject	Sub-word Analysis	en_US
dc.title	Bits2020@ Dravidian-CodeMix-FIRE2020: Sub-Word Level Sentiment Analysis of Dravidian Code Mixed Data	en_US
dc.type	Article	en_US
Appears in Collections:	Department of Computer Science and Information Systems

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