Overview of the 2023 ICON Shared Task on Gendered Abuse Detection in Indic Languages
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Abstract (arXiv)
This paper reports the findings of the ICON 2023 on Gendered Abuse Detection in Indic Languages. The shared task deals with the detection of gendered abuse in online text. The shared task was conducted as a part of ICON 2023, based on a novel dataset in Hindi, Tamil and the Indian dialect of English. The participants were given three subtasks with the train dataset consisting of approximately 6500 posts sourced from Twitter. For the test set, approximately 1200 posts were provided. The shared task received a total of 9 registrations. The best F-1 scores are 0.616 for subtask 1, 0.572 for subtask 2 and, 0.616 and 0.582 for subtask 3. The paper contains examples of hateful content owing to its topic.
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References · 9
- 2019Predicting the Type and Target of Offensive Posts in Social Mediacited by 268
- 2019SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)cited by 206
- 2017Understanding Abuse: A Typology of Abusive Language Detection Subtaskscited by 115
- 2018Aggression-annotated Corpus of Hindi-English Code-mixed Datacited by 40
- 2020Hate Speech detection in the Bengali language: A dataset and its baseline evaluationcited by 37
- 2020Developing a Multilingual Annotated Corpus of Misogyny and Aggressioncited by 31
- 2021Hate and Offensive Speech Detection in Hindi and Marathicited by 17
- 2016Modeling Trolling in Social Media Conversationscited by 6
- 2023The Uli Dataset: An Exercise in Experience Led Annotation of oGBVcited by 2
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