Journal Article

This essay adopts a critical rhetorical perspective attuned to affect to investigate white nationalist rhetoric on Stormfront, a popular white nationalist message board. My analysis illuminates how Stormfront attempts to appeal to mainstream white audiences by resisting normative expectations and affects articulated with white supremacy and (re)constructing white nationalism as a formation of white racial ...

In the space of 36 minutes on March 15, 2019, it is alleged that Brenton Tarrant, an Australian far-right extremist, fatally shot 51 people in two mosques in Christchurch in the deadliest terrorist attack in New Zealand’s history. What was unique about Tarrant’s attack—at least insofar as extreme-right terrorism is concerned—is that he livestreamed his ...

Several incidents of mass violence in 2019 were preceded by manifestoes posted to deep Web social media sites by their perpetrators. These sites, most notably 4chan and 8chan, are buried in the deep Web, away from the neutralizing effects of broad public discourse. Many of the posts to these sites reference earlier extremist incidents, and ...

Countering online hate speech is a critical yet challenging task, but one which can be aided by the use of Natural Language Processing (NLP) techniques. Previous research has primarily focused on the development of NLP methods to automatically and effectively detect online hate speech while disregarding further action needed to calm and discourage individuals from ...

Non-profits, as well as the media, have hypothesized the existence of a radicalization pipeline on YouTube, claiming that users systematically progress towards more extreme content on the platform. Yet, there is to date no substantial quantitative evidence of this alleged pipeline. To close this gap, we conduct a large-scale audit of user radicalization on YouTube. ...

This paper presents a survey on hate speech detection. Given the steadily growing body of social media content, the amount of online hate speech is also increasing. Due to the massive scale of the web, methods that automatically detect hate speech are required. Our survey describes key areas that have been explored to automatically recognize ...

Online social media platforms generally attempt to mitigate hateful expressions, as these comments can be detrimental to the health of the community. However, automatically identifying hateful comments can be challenging. We manually label 5,143 hateful expressions posted to YouTube and Facebook videos among a dataset of 137,098 comments from an online news media. We then ...

The increasing presence of hate speech on social media has drawn significant investment from governments, companies, and empirical research. Existing methods typically use a supervised text classification approach that depends on carefully engineered features. However, it is unclear if these features contribute equally to the performance of such methods. We conduct a feature selection analysis ...

Existing work on automated hate speech detection typically focuses on binary classification or on differentiating among a small set of categories. In this paper, we propose a novel method on a fine-grained hate speech classification task, which focuses on differentiating among 40 hate groups of 13 different hate group categories. We first explore the Conditional ...

Social media has become an indispensable part of the everyday lives of millions of people around the world. It provides a platform for expressing opinions and beliefs, communicated to a massive audience. However, this ease with which people can express themselves has also allowed for the large scale spread of propaganda and hate speech. To ...