Online Library

This study involved the creation of factors and indicators that can detect radicalization in social media posts. A concurrent approach of an expert knowledge acquisition process (modified Delphi technique) and literature review was utilized. Seven Singapore subject-matter experts in the field of terrorism evaluated factors that were collated from six terrorism risk assessment tools (ERG 22+, IVP, TRAP-18, MLG, VERA-2, and Cyber-VERA). They identify those that are of most considerable relevance for detecting radicalization in social media posts. A parallel literature review on online radicalization was conducted to complement the findings from the expert panel. In doing so, 12 factors and their 42 observable indicators were derived. These factors and indicators have the potential to guide the development of cyber-focused screening tools to detect radicalization in social media posts.

The counterterrorism and CVE community has long questioned the effectiveness of counterspeech in countering extremism online. While most evaluation of counterspeech rely on limited reach and engagement metrics, this paper explores two models to better measure behavioral change and sentiment analysis. Conducted via partnerships between Facebook and counter-extremism NGOs, the first model uses A/B testing to analyze the effects of counterspeech exposure on low-prevalence-high-risk audiences engaging with Islamist extremist terrorist content. The second model builds upon online safety intervention approaches and the Redirect Method
through a search based “get-help” module, redirecting whitesupremacy and Neo-Nazi related search-terms to disengagement NGOs.

Extreme, anti-establishment actors are being characterized increasingly as ‘dangerous individuals’ by the social media platforms that once aided in making them into ‘Internet celebrities’. These individuals (and sometimes groups) are being ‘deplatformed’ by the leading social media companies such as Facebook, Instagram, Twitter and YouTube for such offences as ‘organised hate’. Deplatforming has prompted debate about ‘liberal big tech’ silencing free speech and taking on the role of editors, but also about the questions of whether it is effective and for whom. The research reported here follows certain of these Internet celebrities to Telegram as well as to a larger alternative social media ecology. It enquires empirically into some of the arguments made concerning whether deplatforming ‘works’ and how the deplatformed use Telegram. It discusses the effects of deplatforming for extreme Internet celebrities, alternative and mainstream social media platforms and the Internet at large. It also touches upon how social media companies’ deplatforming is affecting critical social media research, both into the substance of extreme speech as well as its audiences on mainstream as well as alternative platforms.

This paper reports on a study that is part of a project which aims to develop a multimodal analytical approach for big data analytics, initially in the context of violent extremism. The findings reported here tested the application of natural language processing models to the text of a sample of articles from the online magazines Dabiq and Rumiyah, produced by the Islamic extremist organisation ISIS. For comparison, text of articles found by reverse image search software which re-used the lead images from the original articles in text which either reported on or opposed extremist activities was also analysed. The aim was to explore what insights the natural language processing models could provide to distinguish between texts produced as propaganda to incite violent extremism and texts which either reported on or opposed violent extremism. The results showed that some valuable insights can be gained from such an approach and that these results could be improved through integrating automated analyses with a theoretical approach with analysed language and images in their immediate and social contexts. Such an approach will inform the interpretation of results and will be used in training software so that stronger results can be achieved in the future.

This article begins by outlining four post-WWII strategies of right-wing revolutionary resistance: vanguardism; the cell system; leaderless resistance; and metapolitics. Next, the article argues that metapolitics became a preferred strategy for many right-wing revolutionaries during the 2000s and early 2010s, and proposes three conditions that may help explain this metapolitical turn: limited opportunities for armed resistance; a subcultural style shift; and new opportunities for promoting alternative worldviews online. Finally, the article theorizes about the types of threats that may emerge in the wake of this metapolitical turn, and speculates about the likelihood of a new and more violent turn in the near future.

This report aims to contribute to our understanding of online hate in the context of the requirements of the revised Audiovisual Media Services Directive (AVMSD) for Video Sharing Platforms (VSPs) to protect the general public from incitement to hatred or violence. However, online hate is complex and it can only be fully understood by considering issues beyond the very specific focus of these regulations. Hence, we draw on recent social and computational research to consider a range of points outside VSP regulations, such as the impact, nature and dynamics of online hate. For similar reasons,
we have considered expressions of hate across a range of online spaces, including VSPs as well as other online platforms. In particular, we have closely examined how online hate is currently addressed by industry, identifying key and emerging issues in content moderation practices. Our analyses will be relevant to a range of experts and stakeholders working to address online hate, including researchers, platforms, regulators and civil society organisations.