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        <title>Simon @ DravidianLangTech-EACL2021: Meme Classification for Tamil with BERT</title>
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        <namePart type="given">Qinyu</namePart>
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            <title>Proceedings of the First Workshop on Speech and Language Technologies for Dravidian Languages</title>
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            <namePart type="given">Bharathi</namePart>
            <namePart type="given">Raja</namePart>
            <namePart type="family">Chakravarthi</namePart>
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        <name type="personal">
            <namePart type="given">Ruba</namePart>
            <namePart type="family">Priyadharshini</namePart>
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    <abstract>In this paper, we introduce the system for the task of meme classification for Tamil, submitted by our team. In today’s society, social media has become an important platform for people to communicate. We use social media to share information about ourselves and express our views on things. It has gradually developed a unique form of emotional expression on social media – meme. The meme is an expression that is often ironic. This also gives the meme a unique sense of humor. But it’s not just positive content on social media. There’s also a lot of offensive content. Meme’s unique expression makes it often used by some users to post offensive content. Therefore, it is very urgent to detect the offensive content of the meme. Our team uses the natural language processing method to classify the offensive content of the meme. Our team combines the BERT model with the CNN to improve the model’s ability to collect statement information. Finally, the F1-score of our team in the official test set is 0.49, and our method ranks 5th.</abstract>
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%0 Conference Proceedings
%T Simon @ DravidianLangTech-EACL2021: Meme Classification for Tamil with BERT
%A Que, Qinyu
%Y Chakravarthi, Bharathi Raja
%Y Priyadharshini, Ruba
%Y Kumar M, Anand
%Y Krishnamurthy, Parameswari
%Y Sherly, Elizabeth
%S Proceedings of the First Workshop on Speech and Language Technologies for Dravidian Languages
%D 2021
%8 April
%I Association for Computational Linguistics
%C Kyiv
%F que-2021-simon-dravidianlangtech
%X In this paper, we introduce the system for the task of meme classification for Tamil, submitted by our team. In today’s society, social media has become an important platform for people to communicate. We use social media to share information about ourselves and express our views on things. It has gradually developed a unique form of emotional expression on social media – meme. The meme is an expression that is often ironic. This also gives the meme a unique sense of humor. But it’s not just positive content on social media. There’s also a lot of offensive content. Meme’s unique expression makes it often used by some users to post offensive content. Therefore, it is very urgent to detect the offensive content of the meme. Our team uses the natural language processing method to classify the offensive content of the meme. Our team combines the BERT model with the CNN to improve the model’s ability to collect statement information. Finally, the F1-score of our team in the official test set is 0.49, and our method ranks 5th.
%U https://aclanthology.org/2021.dravidianlangtech-1.41
%P 287-290

Markdown (Informal)

[Simon @ DravidianLangTech-EACL2021: Meme Classification for Tamil with BERT](https://aclanthology.org/2021.dravidianlangtech-1.41) (Que, DravidianLangTech 2021)

• Simon @ DravidianLangTech-EACL2021: Meme Classification for Tamil with BERT (Que, DravidianLangTech 2021)

ACL

• Qinyu Que. 2021. Simon @ DravidianLangTech-EACL2021: Meme Classification for Tamil with BERT. In Proceedings of the First Workshop on Speech and Language Technologies for Dravidian Languages, pages 287–290, Kyiv. Association for Computational Linguistics.