With the multiplication of social media platforms, which offer anonymity, easy access and
online community formation and online debate, the issue of hate speech detection and …

Data-driven and machine learning based approaches for detecting, categorising and
measuring abusive content such as hate speech and harassment have gained traction due …

The'manosphere'has been a recent subject of feminist scholarship on the web. Serious
accusations have been levied against it for its role in encouraging misogyny and violent …

Online platforms have become an increasingly prominent means of communication. Despite
the obvious benefits to the expanded distribution of content, the last decade has resulted in …

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 …

Cyber-aggression, cyberbullying, and cyber-grooming are distinctive and similar
phenomena that represent the objectionable content appearing on online social media …

With widespread usage of online social networks and its popularity, social networking
platforms have given us incalculable opportunities than ever before, and its benefits are …

Hate speech is plaguing the cyberspace along with user-generated content. This paper
investigates the role of conversational context in the annotation and detection of online hate …

The fast spread of hate speech on social media impacts the Internet environment and our
society by increasing prejudice and hurting people. Detecting hate speech has aroused …

Abusive language is an important issue in online communication across different platforms
and languages. Having a robust model to detect abusive instances automatically is a …