Hate speech detection has substantially increased interest among researchers in the
domain of natural language processing (NLP) and text mining. The number of studies on this …

Technologies for abusive language detection are being developed and applied with little
consideration of their potential biases. We examine racial bias in five different sets of Twitter …

Aiming to enhance the safety of their users, social media platforms enforce terms of service
by performing active moderation, including removing content or suspending users …

The rise of social media platforms has significantly changed the way our world
communicates, and part of those changes includes a rise in inappropriate behaviors, such …

Abstract The realm of Natural Language Processing and Text Mining has seen a surge in
interest from researchers in hate speech detection, leading to an increase in related studies …

The analysis and detection of offensive content in textual information have become a great
challenge for the Natural Language Processing community. Most of the research conducted …

Hate speech is an important problem in the management of user-generated content. To
remove offensive content or ban misbehaving users, content moderators need reliable hate …

In traditional machine learning, classifiers training is typically undertaken in the setting of
single-task learning, so the trained classifier can discriminate between different classes …

Abstract Information and communication technology has evolved dramatically, and now the
majority of people are using internet and sharing their opinion more openly, which has led to …

Hate speech detection mostly involves the use of text data. This data, usually sourced from
various social media platforms, have been known to be plagued with numerous issues that …