Online Library

This thesis explores how extremism manages to survive in moderated online spaces. This work follows the attempts of the Instagram platform to minimize the presence of the right-wing extremist groups, specifically the Boogaloo movement, as a means of understanding how such groups survive and proselytize in the face of censorship. Addressing this question is done through the use of a multi-sited virtual ethnography spanning the Instagram Boogaloo community, Telegram channels and other external links shared by the accounts within the sample group over the course of two years. Publicly available posts from relevant accounts were archived and subject to content analysis to provide a baseline understanding of the group’s ideology and determine existing and emergent themes in order to demonstrate the evolution of the group. Collection and analysis was a concurrent and cyclical process which yielded a deeper understanding of the Boogaloo movement’s ideology and the meaning behind the symbols employed by the group. Furthermore, the results of this work showcase that the longer the Boogaloo movement spent circumnavigating censorship, the more the group began to resemble other successful extremist groups. Subsequently the analysis was informed by social movement theory and new institutionalism to explain how extremist groups approach adversity and uncertainty in a similar fashion to how institutions behave, which ultimately leads to homogenization.

Tech platforms have been through several regulatory phases concerning the countering of terrorist content on their platforms: from a lack of regulation, to the government demands of self-regulation, to the present day where regulation has been implemented across the world. Much of this regulation, however, has been heavily criticised. After consideration of these criticisms, and research into regulatory approaches in a range of other industries, this article proposes a responsive regulatory approach to countering online terrorist content. Responsive regulation argues that regulation should be responsive to specific industry structure because different structures are conducive to different degrees and forms of regulation. This article categorizes tech platforms based on different compliance issues: awareness and expertise; capacity; and willingness. It then proposes four regulatory tracks in response, in order to try to mitigate the occurrence of these compliance issues.

This report provides a review of the research on the exploitation of gaming and gaming‑adjacent platforms by violent extremists and the policies seeking to mitigate the impact of that exploitation. There is increasing interest in the nexus of online gaming and (violent) extremism. This report builds on the work of the Extremism and Gaming Research Network (EGRN) to provide a primer for those new to this space and an updated state of play of the cutting‑edge research taking place among members of the network and beyond.

Radical, terroristic organizations pose threats to business, government, and society. The ubiquity of the modern Web and its participatory architecture have enabled such groups to become full-blown online propaganda machines. Today, radicalization that eventually leads to acts of terror occurs predominantly on the Web. Radical ideologies can be spread, in many cases unchecked, by malicious actors who take advantage of the frequently lax surveillance apparatus of online social platforms. This paper argues that an overlooked, essential first step to interdicting this threat is the large-scale, structured collection of knowledge regarding these ideologies in open machine-readable formats. Using Collective Action Framing Theory, this study develops a trio of design artifacts: the Terror Beliefs Ontology (TBO) for a general ontology of terroristic ideology, the Frame Discovery System (FDS) to automatically populate this ontology, and the Frame Resonance Detection System (FRDS) to accurately identify online personae or postings that espouse a radical ideology known to TBO. With a comprehensive evaluation, we demonstrate how these three instantiated design artifacts, working in concert, can automatically construct a knowledge representation of heterogeneous terroristic ideologies and accurately detect radical online postings. We offer the first design that can assign Web text to any radical ideology without the use of a hand-labeled training corpus.