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 …

Language models (LMs) are becoming the foundation for almost all major language
technologies, but their capabilities, limitations, and risks are not well understood. We present …

Sentiment analysis (SA) has been a long-standing research area in natural language
processing. It can offer rich insights into human sentiments and opinions and has thus seen …

Majority voting and averaging are common approaches used to resolve annotator
disagreements and derive single ground truth labels from multiple annotations. However …

As government pressure on major technology companies builds, both firms and legislators
are searching for technical solutions to difficult platform governance puzzles such as hate …

We investigate how annotators' insensitivity to differences in dialect can lead to racial bias in
automatic hate speech detection models, potentially amplifying harm against minority …

In this paper, we describe our approach to utilize pre-trained BERT models with
Convolutional Neural Networks for sub-task A of the Multilingual Offensive Language …

With the rise in cases of COVID-19, a bizarre situation of pressure was mounted on each
country to make arrangements to control the population and utilize the available resources …

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 …