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
