LinguAIsts@DravidianLangTech 2025: Abusive Tamil and Malayalam Text targeting Women on Social Media

AbstractSocial media sites are becoming crucial sites for communication and interaction, yet they are increasingly being utilized to commit gender-based abuse, with horrific, harassing, and degrading comments targeted at women. This paper tries to solve the common issue of women being subjected to abusive language in two South Indian languages, Malayalam and Tamil. To find explicit abuse, implicit bias, preconceptions, and coded language, we were given a set of YouTube comments labeled Abusive and Non-Abusive. To solve this problem, we applied and compared different machine learning models, i.e., Support Vector Machines (SVM), Logistic Regression (LR), and Naive Bayes classifiers, to classify comments into the given categories. The models were trained and validated using the given dataset to achieve the best performance with respect to accuracy and macro F1 score. The solutions proposed aim to make robust content moderation systems that can detect and prevent abusive language, ensuring safer online environments for women.