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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 indeed the incidents themselves mimic aspects of previous attacks. Building on previous research, this paper examines these deep Web social media sites. Through an analysis of traffic and posts, we confirm that these sites often act as a self-reinforcing community of users encouraging each other to violence, and we map a statistically significant rise in post volume; on these sites immediately following terrorist attacks.

The rise of the alt-right as a potent and sometimes violent political force has been well documented. Yet the journey of an individual towards upholding these ideologies is less well understood. Alt-righters are not instantly converted, but rather incrementally nudged along a particular medial pathway. Drawing on video testimonies, chat logs, and other studies, this paper explores the interaction between this alt-right “pipeline” and the psyche of a user. It suggests three overlapping cognitive phases that occur within this journey: normalization, acclimation, and dehumanization. Finally, the article examines the individual who has reached the end of this journey, an extremist who nevertheless remains largely unregistered within traditional terrorist classifications.

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.

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 using hate speech in the future. In addition, most existing hate speech datasets treat each post as an isolated instance, ignoring the conversational context. In this paper, we propose a novel task of generative hate speech intervention, where the goal is to automatically generate responses to intervene during online conversations that contain hate speech. As a part of this work, we introduce two fully-labeled large-scale hate speech intervention datasets collected from Gab and Reddit. These datasets provide conversation segments, hate speech labels, as well as intervention responses written by Mechanical Turk Workers. In this paper, we also analyze the datasets to understand the common intervention strategies and explore the performance of common automatic response generation methods on these new datasets to provide a benchmark for future research.

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. We analyze 330,925 videos posted on 349 channels, which we broadly classified into four types: Media, the Alt-lite, the Intellectual Dark Web (I.D.W.), and the Alt-right. According to the aforementioned radicalization hypothesis, channels in the I.D.W. and the Alt-lite serve as gateways to fringe far-right ideology, here represented by Alt-right channels. Processing 72M+ comments, we show that the three channel types indeed increasingly share the same user base; that users consistently migrate from milder to more extreme content; and that a large percentage of users who consume Alt-right content now consumed Alt-lite and I.D.W. content in the past. We also probe YouTube’s recommendation algorithm, looking at more than 2M video and channel recommendations between May/July 2019. We find that Alt-lite content is easily reachable from I.D.W. channels, while Alt-right videos are reachable only through channel recommendations. Overall, we paint a comprehensive picture of user radicalization on YouTube.

This chapter illustrates that online and offline measures to counter violent extremism in Australia have targeted jihadism over other forms of extremism. With attention to the open and intensifying state of far-right extremism in Australia, it advocates for increased attention to this situation. It contends that, given the recursive nature of online extremism and its political and international dimensions, material disseminated by far-right and jihadist groups should be addressed from a comparative perspective.