Achyuta V

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2022

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BPHC@DravidianLangTech-ACL2022-A comparative analysis of classical and pre-trained models for troll meme classification in Tamil
Achyuta V | Mithun Kumar S R | Aruna Malapati | Lov Kumar
Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages

Trolling refers to any user behaviour on the internet to intentionally provoke or instigate conflict predominantly in social media. This paper aims to classify troll meme captions in Tamil-English code-mixed form. Embeddings are obtained for raw code-mixed text and the translated and transliterated version of the text and their relative performances are compared. Furthermore, this paper compares the performances of 11 different classification algorithms using Accuracy and F1- Score. We conclude that we were able to achieve a weighted F1 score of 0.74 through MuRIL pretrained model.
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