Hate Speech and Cyberbullying Detection
This cluster of papers focuses on the automated detection of hate speech, offensive language, and cyberbullying in social media platforms such as Twitter. It explores various techniques including machine learning, natural language processing, and deep learning to identify and categorize abusive content, with a specific emphasis on mitigating online harassment and promoting online safety.
Papers listed on taxonomy pages are the top few works per node from the OpenAlex snapshot. That list is not exhaustive and is not an endorsement. The topic map and the journal registry remain separate: there is still no authoritative topic-to-venue or topic-to-organization edge. Search is a lexical lookup, not a claim that a venue publishes a topic.