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2021 EACL EACL 2021

IIITK@DravidianLangTech-EACL2021: Offensive Language Identification and Meme Classification in Tamil, Malayalam and Kannada

Abstract

AbstractThis paper describes the IIITK team’s submissions to the offensive language identification, and troll memes classification shared tasks for Dravidian languages at DravidianLangTech 2021 workshop@EACL 2021. Our best configuration for Tamil troll meme classification achieved 0.55 weighted average F1 score, and for offensive language identification, our system achieved weighted F1 scores of 0.75 for Tamil, 0.95 for Malayalam, and 0.71 for Kannada. Our rank on Tamil troll meme classification is 2, and offensive language identification in Tamil, Malayalam and Kannada are 3, 3 and 4 respectively.

πŸŒ‰ Interdisciplinary Bridge β€” Interdisciplinary and Natural Language Processing
🧭 Keyword Pioneer β€” offensive language detection
🐣 Hot Topic Early Bird β€” multilingual nlp
🐝 Cross-Pollinator β€” Artificial Intelligence, Deep Learning, Interdisciplinary, Machine Learning, Natural Language Processing, Speech & Audio

Authors

Nikhil Ghanghor , Parameswari Krishnamurthy , Sajeetha Thavareesan , Ruba Priyadharshini , Bharathi Raja Chakravarthi

Topics

Natural Language Processing > Applications > Text Classification Interdisciplinary > Linguistics > Computational Linguistics Natural Language Processing > Applications > Sentiment Analysis

Keywords

text classification multilingual nlp offensive language detection meme classification
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