KEC_TECH_TITANS@DravidianLangTech 2025: Abusive Text Detection in Tamil and Malayalam Social Media Comments Using Machine Learning

AbstractSocial media platforms have become a breeding ground for hostility and toxicity, with abusive language targeting women becoming a pervasive issue. This paper addresses the detection of abusive content in Tamil and Malayalam social media comments using machine learning models. We experimented with GRU, LSTM, Bidirectional LSTM, CNN, FastText, and XGBoost models, evaluating their performance on a code-mixed dataset of Tamil and Malayalam comments collected from YouTube. Our findings demonstrate that FastText and CNN models yielded the best performance among the evaluated classifiers, achieving F1-scores of 0.73 each. This study contributes to the ongoing research on abusive text detection for under-resourced languages and highlights the need for robust, scalable solutions to combat online toxicity.