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.
Based on work on hate speech, cyberbullying and online abuse, REF proposses a typology that captures central similarities and differences between subtasks and discuss its implications for data annotation and feature construction.
Understanding Abuse: A Typology of Abusive Language Detection Subtasks
ArXiv
ArXiv
Computer Science Psychology