Automated Hate Speech Detection and the Problem of Offensive Language

A key challenge for automatic hate-speech detection on social media is the separation of hate speech from other instances of offensive language. Lexical detection methods tend to have low precision because they classify all messages containing particular terms as hate speech and previous work using supervised learning has failed to distinguish between the two categories. We used a crowd-sourced hate speech lexicon to collect tweets containing hate speech keywords. We use crowd-sourcing to label a sample of these tweets into three categories: those containing hate speech, only offensive language, and those with neither. We train a multi-class classifier to distinguish between these different categories. Close analysis of the predictions and the errors shows when we can reliably separate hate speech from other offensive language and when this differentiation is more difficult. We find that racist and homophobic tweets are more likely to be classified as hate speech but that sexist tweets are generally classified as offensive. Tweets without explicit hate keywords are also more difficult to classify.Comment: To appear in the Proceedings of ICWSM 2017. Please cite that versio

Analyzing the Targets of Hate in Online Social Media

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.Comment: Short paper, 4 pages, 4 table

Race riots on the beach: A case for criminalising hate speech?

noThis paper analyses the verbal and textual hostility employed by rioters, politicians and the media in Sydney (Australia) in December 2005 in the battle over Sutherland Shire¿s Cronulla Beach. By better understanding the linguistic conventions underlying all forms of maledictive hate, we are better able to address the false antimonies between free speech and the regulation of speech. It is also argued that understanding the harms of hate speech provides us with the tools necessary to create a more responsive framework for criminalising some forms of hate speech as a preliminary process in reducing or eliminating hate violence

Taking North American White Supremacist groups seriously: The scope and the challenge of hate speech on the internet

This article aims to address two questions: how does hate speech manifest on North American white supremacist websites; and is there a connection between online hate speech and hate crime? Firstly, hate speech is defined and the research methodology upon which the article is based is explained. The ways that ‘hate’ groups utilise the Internet and their purposes in doing so are then analysed, with the content and the functions of their websites as well as their agenda examined. Finally, the article explores the connection between hate speech and hate crime. I argue that there is sufficient evidence to suggest that speech can and does inspire crime. The article is based in the main on primary sources: a study of many ‘hate’ websites; and interviews and discussions with experts in the field

Regulating hate speech online

The exponential growth in the Internet as a means of communication has been emulated by an increase in far-right and extremist web sites and hate based activity in cyberspace. The anonymity and mobility afforded by the Internet has made harassment and expressions of hate effortless in a landscape that is abstract and beyond the realms of traditional law enforcement. This paper examines the complexities of regulating hate speech on the Internet through legal and technological frameworks. It explores the limitations of unilateral national content legislation and the difficulties inherent in multilateral efforts to regulate the Internet. The paper develops to consider how technological innovations can restrict the harm caused by hate speech while states seek to find common ground upon which to harmonise their approach to regulation. Further, it argues that a broad coalition of government, business and citizenry is likely to be most effective in reducing the harm caused by hate speech