arXiv:1705.09899
Understanding Abuse: A Typology of Abusive Language Detection Subtasks
원문 초록
As the body of research on abusive language detection and analysis grows, there is a need for critical consideration of the relationships between different subtasks that have been grouped under this label. Based on work on hate speech, cyberbullying, and online abuse we propose a typology that captures central similarities and differences between subtasks and we discuss its implications for data annotation and feature construction. We emphasize the practical actions that can be taken by researchers to best approach their abusive language detection subtask of interest.
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ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Abuse Detection in Conversational AI
Intersectional Bias in Hate Speech and Abusive Language Datasets
HateMonitors: Language Agnostic Abuse Detection in Social Media
토론
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