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offensive-language

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HausaHate is a benchmark dataset for Hausa hate speech detection task. it was extracted from West African Facebook pages and comprises 2,000 comments annotated according to a binary class (offensive and non-offensive) and hate speech targets (race, gender and none).

  • Updated Nov 15, 2025

Detect hate speech in tweets using NLP and Machine Learning. This project automates classification into hate speech, offensive language, and neutral content. 🐙💻

  • Updated Aug 26, 2025
  • Jupyter Notebook

DravidaKavacham is an open-source tool for detecting abusive content in Dravidian (Tamil and Malayalam), focused on harmful language targeting women. Developed as part of the DravidianLangTech@NAACL 2025 shared task, it uses NLP and machine learning for accurate text classification and content analysis.

  • Updated Jan 10, 2025
  • Jupyter Notebook

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