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2022 ACL ACL 2022

BPHC@DravidianLangTech-ACL2022-A comparative analysis of classical and pre-trained models for troll meme classification in Tamil

Abstract

AbstractTrolling 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.

🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio

Authors

Achyuta V , Mithun Kumar S R , Aruna Malapati , Lov Kumar

Topics

Machine Learning > Core Methods > Classification Deep Learning > Models > Transformers Machine Learning > Learning Types > Multi-Lingual Learning

Keywords

text classification meme classification code-mixed text pre-trained model pretrained model comparative analysis troll detection
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