DLRG-DravidianLangTech@EACL2024 : Combating Hate Speech in Telugu Code-mixed Text on Social Media
Ratnavel Rajalakshmi, Saptharishee M, Hareesh S, Gabriel R, Varsini Sr
Abstract
Detecting hate speech in code-mixed language is vital for a secure online space, curbing harmful content, promoting inclusive communication, and safeguarding users from discrimination. Despite the linguistic complexities of code-mixed languages, this study explores diverse pre-processing methods. It finds that the Transliteration method excels in handling linguistic variations. The research comprehensively investigates machine learning and deep learning approaches, namely Logistic Regression and Bi-directional Gated Recurrent Unit (Bi-GRU) models. These models achieved F1 scores of 0.68 and 0.70, respectively, contributing to ongoing efforts to combat hate speech in code-mixed languages and offering valuable insights for future research in this critical domain.- Anthology ID:
- 2024.dravidianlangtech-1.23
- Volume:
- Proceedings of the Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages
- Month:
- March
- Year:
- 2024
- Address:
- St. Julian's, Malta
- Editors:
- Bharathi Raja Chakravarthi, Ruba Priyadharshini, Anand Kumar Madasamy, Sajeetha Thavareesan, Elizabeth Sherly, Rajeswari Nadarajan, Manikandan Ravikiran
- Venues:
- DravidianLangTech | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 140–145
- Language:
- URL:
- https://aclanthology.org/2024.dravidianlangtech-1.23
- DOI:
- Cite (ACL):
- Ratnavel Rajalakshmi, Saptharishee M, Hareesh S, Gabriel R, and Varsini Sr. 2024. DLRG-DravidianLangTech@EACL2024 : Combating Hate Speech in Telugu Code-mixed Text on Social Media. In Proceedings of the Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, pages 140–145, St. Julian's, Malta. Association for Computational Linguistics.
- Cite (Informal):
- DLRG-DravidianLangTech@EACL2024 : Combating Hate Speech in Telugu Code-mixed Text on Social Media (Rajalakshmi et al., DravidianLangTech-WS 2024)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2024.dravidianlangtech-1.23.pdf