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2022 ACL ACL 2022

Findings of the Shared Task on Offensive Span Identification fromCode-Mixed Tamil-English Comments

Abstract

AbstractOffensive content moderation is vital in social media platforms to support healthy online discussions. However, their prevalence in code-mixed 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.

🐣 Hot Topic Early Bird — code-mixed language
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio

Authors

Manikandan Ravikiran , Bharathi Raja Chakravarthi , Anand Kumar Madasamy , Sangeetha Sivanesan , Ratnavel Rajalakshmi , Sajeetha Thavareesan , Rahul Ponnusamy , Shankar Mahadevan

Topics

Interdisciplinary > Social > Social Media Analysis

Keywords

social media code-mixed language offensive span identification
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