In this paper, we (HRS-TECHIE) present our submissions to challenges Dravidian-CodeMix
and HASOC at FIRE 2020. Classification of sentiments from social media posts and …

The research of discerning the offensive language formatted with code-mixed in social
media has a wide range of applications in mining the available information to provide …

With the popularity of social media, communications through blogs, Facebook, Twitter, and
other plat-forms have increased. Initially, English was the only medium of communication …

The definition of the term “hate speech” as per Oxford isa speech that might involve abusive
or threatening words which can have or can express pre-bias against a special …

The current paper describes the system submitted by team AI_ML_NIT_Patna. The task aims
to identify offensive language in code-mixed dataset of comments in Indo-European …

Human behaviour remains the same whether it is a physical or cyber world. They express
their emotions like happy, sad, angry, frustrated, bullying, and so on at both places. To …

The use of social media has grown rapidly in the past few years. User generated data often
contains objectionable content. Identifying hate speech, cyber-attacks and offensive …

With the dramatic growth of hate speech on social media during the COVID-19 pandemic,
there is an urgent need to detect various hate speech effectively. Existing methods only …

The aim of sentiment analysis is to automatically extract the opinions from a certain text and
decide its sentiment. In this paper, we introduce the first publicly-available Twitter dataset on …

In recent years, the advent of social media platforms has led users to freely express their
opinions on various subjects, including politics, society, health, education, finance, and even …