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 …

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 …

This paper presents the HASOC track and its two parts. HASOC is dedicated to evaluate
technology for finding Offensive Language and Hate Speech. HASOC is creating test …

Sentiment analysis of Dravidian languages has received attention in recent years. However,
most social media text is code-mixed and there is no research available on sentiment …

In recent years, given the exponential increase in social media content also led to an
increase in online hate speech. We need automatic hate speech detection methods due to …

The pervasiveness of offensive content in social media has become an important reason for
concern for online platforms. With the aim of improving online safety, a large number of …

The current study represents an integrated model of explicit and implicit offensive language
taxonomy. First, it focuses on a definitional revision and enrichment of the explicit offensive …

The substantial growth in social media users has led to a significant increase in code-mixed
content on social media platforms. Millions of users on these platforms upload pictures and …

We present the results and main findings of the HASOC-Offensive Language Identification
on code mixed Dravidian languages. The task featured two tasks. Task 1 is about offensive …

Social media has become a platform for expressing opinions and emotions, but some
people also use it to spread hate, targeting individuals, groups, communities, or countries …