Findings of the Shared Task on Offensive Span Identification from Code-Mixed Tamil-English Comments
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Abstract (arXiv)
Offensive content moderation is vital in social media platforms to support healthy online discussions. However, their prevalence in codemixed Dravidian languages is limited to classifying whole comments without identifying part of it contributing to offensiveness. Such limitation is primarily due to the lack of annotated data for offensive spans. Accordingly, in this shared task, we provide Tamil-English code-mixed social comments with offensive spans. This paper outlines the dataset so released, methods, and results of the submitted systems
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 10 of its 54 references that are in the map. First posted on arXiv 12 May 2022.
Builds on
10 of 54 references.
References · 10
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- 2021MuRIL: Multilingual Representations for Indian Languagescited by 177
- 2020SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)cited by 138
- 2019A Survey of Code-switched Speech and Language Processingcited by 73
- 2020Corpus Creation for Sentiment Analysis in Code-Mixed Tamil-English Textcited by 67
- 2021Dataset for Identification of Homophobia and Transophobia in Multilingual YouTube Commentscited by 20
- 2021DravidianCodeMix: Sentiment Analysis and Offensive Language Identification Dataset for Dravidian Languages in Code-Mixed Textcited by 18
- 2021Cross-platform analysis of user comments in YouTube videos linked on Reddit conspiracy theory forumcited by 1
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Citing papers per year: 2022: 1; 2023: 0; 2024: 0; 2025: 0; 2026: 1.
2 papers.