A Measurement Study on Racist Hate Speech in Twitter using Tweet Binder

Abstract

The role of social media is in our daily lives is immense. It has many positive sides as well as negative sides especially in the society and human behaviors. Some people are trying to use the social media for tarnishing the routine setup of the society. Some people use these websites for anti-social behaviors including cyber stalking, cyber bullying, trolling, harassments and hate speech. At present, social media websites have started creating serious efforts to control racist hate speech. But, most of them are still facing challenges to come up with an efficient solution. The aim of this research is to explore and measure the racism hate speeches in Twitter. Predictive research method of quantitative studies was applied to carry out this research. Since it is a technological based research, Tweet Binder analytical tool was used to analyze the data. For this research work, the researcher use the dataset for racist hate speech distributed via data world which consists 517 racist hate speeches. Simple random sampling method was used to test the data. As a results, it found that all formats of tweets including text, replies, retweet, pictures and links have most number of racist hate speeches. Especially replies and retweets have highest number of hate speeches. It is highly recommended to Twitter and other social media websites to implement strict policies and mechanisms to control hate speeches to control them to create a peaceful social media environment