2025 NAACL NAACL 2025

Code_Conquerors@DravidianLangTech 2025: Deep Learning Approach for Sentiment Analysis in Tamil and Tulu

Abstract

AbstractIn this paper we propose a novel approach to sentiment analysis in languages with mixed Dravidian codes, specifically Tamil-English and Tulu-English social media text. We introduce an innovative hybrid deep learning architecture that uniquely combines convolutional and recurrent neural networks to effectively capture both local patterns and long-term dependencies in code-mixed text. Our model addresses critical challenges in low-resource language processing through a comprehensive preprocessing pipeline and specialized handling of class imbalance and out-of-vocabulary words. Evaluated on a substantial dataset of social media comments, our approach achieved competitive macro F1 scores of 0.3357 for Tamil (ranked 18) and 0.3628 for Tulu (ranked 13)

🌉 Interdisciplinary Bridge — Deep Learning and Natural Language Processing
🐝 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, Robotics, Security & Privacy, Speech & Audio