Discriminatory Speech on Digital Platform a case study of Twitter (Gender, Race, Politics, Sexuality)

Abstract

In recent years communication via social media has become more personal and available for every individual or group of people irrespective of their interests. This has enable people express their thoughts, ideas and views freely. Though it brings lots of ease to communication, it also gives rise to discriminatory challenges. Online hate is a major example of such challenge.As these social media users grow, so does the impact of hate speech. Despite the magnitude and growth level of research in this field there is a hug gap in understanding the hate speech and how it affects certain aspects of human life’s e.g race,gender,sexuality, politics. This has prompted researchers to apply techniques like social networks analysis to detect hate groups. But in this research we strongly believe that the content of hate matters as well.Thus in this paper we apply sentiment analysis and topic modelling to understand the discuss of hate as it affect race, gender, sexuality, politics. Our result shows that the content plays an important role in preventing and eradicating discrimination of these platforms.