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Abuse Detection

Abuse detection is the task of identifying abusive behaviors, such as hate speech, offensive language, sexism and racism, in utterances from social media platforms (Source: https://arxiv.org/abs/1802.00385).

Papers

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Showing 31–40 of 73 papers

TitleStatusHype
Pay ``Attention'' to your Context when Classifying Abusive LanguageCode0
Author Profiling for Abuse DetectionCode0
Predictive Response Optimization: Using Reinforcement Learning to Fight Online Social Network Abuse—0
Stereotypical Bias Removal for Hate Speech Detection Task using Knowledge-based Generalizations—0
Tackling Online Abuse: A Survey of Automated Abuse Detection Methods—0
The Online Behaviour of the Algerian Abusers in Social Media Networks—0
Modeling Users and Online Communities for Abuse Detection: A Position on Ethics and Explainability—0
Throttling Poisson Processes—0
Toxicity Detection for Indic Multilingual Social Media Content—0
UoB at SemEval-2020 Task 12: Boosting BERT with Corpus Level Information—0
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