Authors

Raey Ageze

Document Type

Honors Thesis

Abstract

The spread of hate speech is one of the major issues that social media platforms, like Twitter, have been facing as digital activism becomes more common. The spread of hate speech is often facilitated by the existence of echo chambers. To gain a better understanding of the type of users that engage in hate speech, tweets related to the Black Lives Matter movement were studied. Tweets that were for and against the Black Lives Matter movement were collected and labeled as hate, counter-hate, and natural. The followers and friends of the selected users of each type were then examined to gather racial data. The racial diversity and homophily of the central users’ egonets were analyzed to construct a model. The model suggests that users with egonets of high racial homophily and lower racial diversity are more likely to engage in hate speech related to the Black Lives Matter movement.

Publication Date

12-1-2020

Language

English

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