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 …

With the advent of the internet and numerous social media platforms, citizens now have
enormous opportunities to express and share their opinions on various societal and political …

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 pervasiveness of abusive content on the internet can lead to severe psychological and
physical harm. Significant effort in Natural Language Processing (NLP) research has been …

The detection of abusive or offensive remarks in social texts has received significant
attention in research. In several related shared tasks, BERT has been shown to be the state …

Many online discussion platforms use a content moderation process, where human
moderators check user comments for offensive language and other rule violations. It is the …

Violence usually spread online, as it has spread in the past. With the increasing use of social
media, the violence attributed to online hate speech has increased worldwide resulting rise …

Social media content moderation is the standard practice as on today to promote healthy
discussion forums. Toxic span prediction is helpful for explaining the toxic comment …

User posts whose perceived toxicity depends on the conversational context are rare in
current toxicity detection datasets. Hence, toxicity detectors trained on current datasets will …