Online Library

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.

Hateful and antagonistic content published and propagated via the World Wide Web has the potential to cause harm and suffering on an individual basis, and lead to social tension and disorder beyond cyber space. Despite new legislation aimed at prosecuting those who misuse new forms of communication to post threatening, harassing, or grossly offensive language – or cyber hate – and the fact large social media companies have committed to protecting their users from harm, it goes largely unpunished due to difficulties in policing online public spaces. To support the automatic detection of cyber hate online, specifically on Twitter, we build multiple individual models to classify cyber hate for a range of protected characteristics including race, disability and sexual orientation. We use text parsing to extract typed dependencies, which represent syntactic and grammatical relationships between words, and are shown to capture ‘othering’ language – consistently improving machine classification for different types of cyber hate beyond the use of a Bag of Words and known hateful terms. Furthermore, we build a data-driven blended model of cyber hate to improve classification where more than one protected characteristic may be attacked (e.g. race and sexual orientation), contributing to the nascent study of intersectionality in hate crime.

To see the Internet as only a ‘tool’ or ‘resource’ for disseminating ideas and products, as much of the literature has done, is to miss an even more significant aspect of online venues. The Internet is also a site of important ‘identity work’, in which collective identities can be accomplished interactively. This chapter explores how collective identities are constructed by white supremacists who specifically exploit the web as a venue for expressing ‘white pride worldwide’. Drawing on social movement literature around the building of collective identities, we examine the online identity work of the ‘globalizing’ right-wing extremist movement through four key frames: alternative media/alternative messaging; identity borders; shared identity; and mobilizing hate. Here, we explore the Internet not as a tool, but as site for the active construction of collective white identity.

VOX-Pol Blog post.

VOX-Pol Blog post.

VOX-Pol Blog post.