KEC AI DSNLP@LT-EDI-2024:Caste and Migration Hate Speech Detection using Machine Learning Techniques
Kogilavani Shanmugavadivel, Malliga Subramanian, Aiswarya M, Aruna T, Jeevaananth S
Abstract
Commonly used language defines “hate speech” as objectionable statements that may jeopardize societal harmony by singling out a group or a person based on fundamental traits (including gender, caste, or religion). Using machine learning techniques, our research focuses on identifying hate speech in social media comments. Using a variety of machine learning methods, we created machine learning models to detect hate speech. An approximate Macro F1 of 0.60 was attained by the created models.- Anthology ID:
- 2024.ltedi-1.24
- Volume:
- Proceedings of the Fourth Workshop on Language Technology for Equality, Diversity, Inclusion
- Month:
- March
- Year:
- 2024
- Address:
- St. Julian's, Malta
- Editors:
- Bharathi Raja Chakravarthi, Bharathi B, Paul Buitelaar, Thenmozhi Durairaj, György Kovács, Miguel Ángel García Cumbreras
- Venues:
- LTEDI | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 206–210
- Language:
- URL:
- https://aclanthology.org/2024.ltedi-1.24
- DOI:
- Cite (ACL):
- Kogilavani Shanmugavadivel, Malliga Subramanian, Aiswarya M, Aruna T, and Jeevaananth S. 2024. KEC AI DSNLP@LT-EDI-2024:Caste and Migration Hate Speech Detection using Machine Learning Techniques. In Proceedings of the Fourth Workshop on Language Technology for Equality, Diversity, Inclusion, pages 206–210, St. Julian's, Malta. Association for Computational Linguistics.
- Cite (Informal):
- KEC AI DSNLP@LT-EDI-2024:Caste and Migration Hate Speech Detection using Machine Learning Techniques (Shanmugavadivel et al., LTEDI-WS 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/2024.ltedi-1.24.pdf