GS_DravidianLangTech@2025: Women Targeted Abusive Texts Detection on Social Media
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Abstract (arXiv)
The increasing misuse of social media has become a concern; however, technological solutions are being developed to moderate its content effectively. This paper focuses on detecting abusive texts targeting women on social media platforms. Abusive speech refers to communication intended to harm or incite hatred against vulnerable individuals or groups. Specifically, this study aims to identify abusive language directed toward women. To achieve this, we utilized logistic regression and BERT as base models to train datasets sourced from DravidianLangTech@2025 for Tamil and Malayalam languages. The models were evaluated on test datasets, resulting in a 0.729 macro F1 score for BERT and 0.6279 for logistic regression in Tamil and Malayalam, respectively.
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References · 5
- 2017Attention Is All You Needcited by 60,361
- 2024Analyzing Emotional Trends from X platform using SenticNet: A Comparative Analysis with Cryptocurrency Pricecited by 6
- 2025Comparative Approaches to Sentiment Analysis Using Datasets in Major European and Arabic Languagescited by 3
- 2022Identifying Different Layers of Online Misogynycited by 2
- 2025Online Social Support Detection in Spanish Social Media Textscited by 2
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