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 …

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 …

The performance of hate speech detection models relies on the datasets on which the
models are trained. Existing datasets are mostly prepared with a limited number of instances …

The rise in web and social media interactions has resulted in the efortless proliferation of
offensive language and hate speech. Such online harassment, insults, and attacks are …

Abuse on the Internet represents a significant societal problem of our time. Previous
research on automated abusive language detection in Twitter has shown that community …

Social media platforms were conceived to act as online town squares' where people could
get together, share information and communicate with each other peacefully. However …

Comment sections of online news platforms are an essential space to express opinions and
discuss political topics. In contrast to other online posts, news discussions are related to …

Abuse on the Internet represents an important societal problem of our time. Millions of
Internet users face harassment, racism, personal attacks, and other types of abuse on online …

The automatic detection of conflictual languages (harmful, aggressive, abusive, and
offensive languages) is essential to provide a healthy conversation environment on the Web …

Natural Language Processing (NLP) research has traditionally been predominantly focused
on English, driven by the availability of resources, the size of the research community, and …