While social media has become an empowering agent to individual voices and freedom of expression, it also facilitates anti-social behaviors including online harassment, cyberbullying, and hate speech. In this paper, we present the first comparative study of hate speech instigators and target users on Twitter. Through a multi-step classification process, we curate a comprehensive hate speech dataset capturing various types of hate. We study the distinctive characteristics of hate instigators and targets in terms of their profile self-presentation, activities, and online visibility. We find that hate instigators target more popular and high profile Twitter users, and that participating in hate speech can result in greater online visibility. We conduct a personality analysis of hate instigators and targets and show that both groups have eccentric personality facets that differ from the general Twitter population. Our results advance the state of the art of understanding online hate speech engagement.
Alternatively, cheng2017anyone find that prior negative mood and the context of the discussion can combine to double participants' baseline engagement in trolling behavior. While the authors only used sentiment analysis to investigate mood, we incorporate a full analysis of the Big Five personality traits. In addition, we study the personality traits of both instigators and targets and compare results to a random sample of general Twitter users. Silva @cite_7 identified hate target groups in terms of their class and ethnicity on Twitter and Whisper by searching for sentence structures similar to I @math intensity @math hate @math targeted group @math .'' However, we identify the actual accounts of hate targets on Twitter, those that are explicitly mentioned by hate instigators. Therefore, our analysis provides a unique lens to analyze characteristics of target accounts.
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Social media systems allow Internet users a congenial platform to freely express their thoughts and opinions. Although this property represents incredible and unique communication opportunities, it also brings along important challenges. Online hate speech is an archetypal example of such challenges. Despite its magnitude and scale, there is a significant gap in understanding the nature of hate speech on social media. In this paper, we provide the first of a kind systematic large scale measurement study of the main targets of hate speech in online social media. To do that, we gather traces from two social media systems: Whisper and Twitter. We then develop and validate a methodology to identify hate speech on both these systems. Our results identify online hate speech forms and offer a broader understanding of the phenomenon, providing directions for prevention and detection approaches.