Findings of the First Shared Task on Offensive Span Identification from Code-Mixed Kannada-English Comments

Manikandan Ravikiran, Ratnavel Rajalakshmi, Bharathi Raja Chakravarthi, Anand Kumar Madasamy, Sajeetha Thavareesan


Abstract
Effectively managing offensive content is crucial on social media platforms to encourage positive online interactions. However, addressing offensive contents in code-mixed Dravidian languages faces challenges, as current moderation methods focus on flagging entire comments rather than pinpointing specific offensive segments. This limitation stems from a lack of annotated data and accessible systems designed to identify offensive language sections. To address this, our shared task presents a dataset comprising Kannada-English code-mixed social comments, encompassing offensive comments. This paper outlines the dataset, the utilized algorithms, and the results obtained by systems participating in this shared task.
Anthology ID:
2024.dravidianlangtech-1.7
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:
43–48
Language:
URL:
https://aclanthology.org/2024.dravidianlangtech-1.7
DOI:
Bibkey:
Cite (ACL):
Manikandan Ravikiran, Ratnavel Rajalakshmi, Bharathi Raja Chakravarthi, Anand Kumar Madasamy, and Sajeetha Thavareesan. 2024. Findings of the First Shared Task on Offensive Span Identification from Code-Mixed Kannada-English Comments. In Proceedings of the Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, pages 43–48, St. Julian's, Malta. Association for Computational Linguistics.
Cite (Informal):
Findings of the First Shared Task on Offensive Span Identification from Code-Mixed Kannada-English Comments (Ravikiran et al., DravidianLangTech-WS 2024)
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PDF:
https://aclanthology.org/2024.dravidianlangtech-1.7.pdf
Video:
 https://aclanthology.org/2024.dravidianlangtech-1.7.mp4