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 …

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 …

We present NusaCrowd, a collaborative initiative to collect and unify existing resources for
Indonesian languages, including opening access to previously non-public resources …

In this paper, we introduce HateBERT, a re-trained BERT model for abusive language
detection in English. The model was trained on RAL-E, a large-scale dataset of Reddit …

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

In today's digital era, the rise of hate speech has emerged as a critical concern, driven by the
rapid information-sharing capabilities of social media platforms and online communities. As …

Online hate speech is a recent problem in our society that is rising at a steady pace by
leveraging the vulnerabilities of the corresponding regimes that characterise most social …

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 …

Social networking platforms gained widespread popularity and are used for various activities
like: promoting products, sharing news, achievements and many more. On the other hand, it …

Abstract Analysis of subjective texts like offensive content or hate speech is a great
challenge, especially regarding annotation process. Most of current annotation procedures …