Online toxic discourses could result in conflicts between groups or harm to online
communities. Hate speech is complex and multifaceted harmful or offensive content …

Hate Speech in social media is a complex phenomenon, whose detection has recently
gained significant traction in the Natural Language Processing community, as attested by …

Majority voting and averaging are common approaches used to resolve annotator
disagreements and derive single ground truth labels from multiple annotations. However …

Social media is a more common and powerful platform for communication to share views
about any topic or article, which consequently leads to unstructured toxic, and hateful …

Cyberbullying is a serious problem in online communication. It is important to find effective
ways to detect cyberbullying content to make online environments safer. In this paper, we …

Hate speech detection is a challenging problem with most of the datasets available in only
one language: English. In this paper, we conduct a large scale analysis of multilingual hate …

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 …

The rise of social networks has allowed misogynistic, xenophobic, and homophobic people
to spread their hate-speech to intimidate individuals or groups because of their gender …

Twitter is a microblogging tool that allow the creation of big data through short digital
contents. This study provides a survey of machine learning techniques for hate speech …

The research carried out so far in detecting abusive content in social media has primarily
focused on overt forms of hate speech. While explicit hate speech (HS) is more easily …