Since its earliest days, harassment and abuse have plagued the Internet. Recent research
has focused on in-domain methods to detect abusive content and faces several challenges …

The ability to recognize harmful content within online communities has come into focus for
researchers, engineers and policy makers seeking to protect users from abuse. While the …

Online abuse can inflict harm on users and communities, making online spaces unsafe and
toxic. Progress in automatically detecting and classifying abusive content is often held back …

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 …

Online abusive behavior affects millions and the NLP community has attempted to mitigate
this problem by developing technologies to detect abuse. However, current methods have …

Online social spaces provide much needed connection and belonging—particularly in a
context of continued lack of global mobility due to the ongoing Covid-19 pandemic and …

Detection of abusive language in user generated online content has become an issue of
increasing importance in recent years. Most current commercial methods make use of …

The rapid growth of social media in recent years has fed into some highly undesirable
phenomena such as proliferation of hateful and offensive language on the Internet. Previous …

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 …

The issues of cyberbullying and online harassment have gained considerable coverage in
the last number of years. Social media providers need to be able to detect abusive content …