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 …

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 …

The identification of Hate Speech in Social Media is of great importance and receives much
attention in the text classification community. There is a huge demand for research for …

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

Text-embedded images are frequently used on social media to convey opinions and
emotions, but they can also be a medium for disseminating hate speech, propaganda, and …

Offensive content is pervasive in social media and a reason for concern to companies and
government organizations. Several studies have been recently published investigating …

Users of online platforms have negative effects on their mental health as a direct result of the
spread of abusive content across social media networks. Homophobia are terms that refer to …

Detecting online toxicity has always been a challenge due to its inherent subjectivity. Factors
such as the context, geography, socio-political climate, and background of the producers …

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 …

A considerable body of research deals with the automatic identification of hate speech and
related phenomena. However, cross-dataset model generalization remains a challenge. In …