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

The widespread of offensive content online, such as hate speech and cyber-bullying, is a
global phenomenon. This has sparked interest in the artificial intelligence (AI) and natural …

This paper presents the Graded Word Similarity in Context (GWSC) task which asked
participants to predict the effects of context on human perception of similarity in English …

Identifying informative tweets is an important step when building information extraction
systems based on social media. WNUT-2020 Task 2 was organised to recognise informative …

This paper describes the submissions by team HWR to the Dravidian Language
Identification (DLI) shared task organized at VarDial 2021 workshop. The DLI training set …

This paper describes the WLV-RIT entry to the Hate Speech and Offensive Content
Identification in Indo-European Languages (HASOC) shared task 2020. The HASOC 2020 …

The massive spread of false information on social media has become a global risk
especially in a global pandemic situation like COVID-19. False information detection has …

Identifying whether a word carries the same meaning or different meaning in two contexts is
an important research area in natural language processing which plays a significant role in …

In recent years, the widespread use of social media has led to an increase in the generation
of toxic and offensive content on online platforms. In response, social media platforms have …

This paper addresses the identification of toxic, engaging, and fact-claiming comments on
social media. We used the dataset made available by the organizers of the GermEval-2021 …