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In response to the rise of various fringe movements in recent years, from anti-vaxxers to QAnon, there has been increased public and scholarly attention to misinformation and conspiracy theories and the online communities that produce them. However, efforts at understanding the radicalisation process largely focus on those who go on to commit violent crimes. This article draws on three waves of research exploring the experiences of individuals currently or formerly involved in fringe communities, including the different stages of investment they progressed through, and ultimately, what made people leave. We propose a pathway model for understanding contemporary online radicalisation, including potential interventions that could be safely made at each stage. Insight into the experience of being immersed in these communities is essential for engaging with these people empathetically, and therefore preventing both the emergence of violent terrorists and protecting vulnerable people from being drawn into these communities.

The purpose of this report is to provide a comprehensive overview of existing knowledge on contemporary extremist narratives circulating online in three countries across Europe; Austria, Bulgaria and Sweden. To achieve this, the report draws on a review of an extensive body of previous research and secondary data sources, pursuing two primary objectives: firstly, it maps what kind of extremist narratives are on offer across Europe today, and second, it identifies where across the digital mainstream, these are currently in circulation.

This report presents the main theories and ways radical groups influence and attract individuals online, and the most common tools and strategies governments use to counter its impact.

Many cases of radicalism, especially violent radicalism, manifest within the context of inter-ethnic conflict and war. Research in this domain has significantly contributed to our overarching comprehension of the issue. This form of radicalism is inherently linked to the dynamics of group affiliation. However, our focus here is directed towards the individual motivation driving radical actions. While radical actions may encompass dynamics of group affiliation (e.g., the most radical pro-life activists being members of the Army of God), they also possess a substantial individual component. For instance, numerous attacks on abortion doctors or clinics are categorized as ’lone-wolf terrorism’.

In this study, we sought to examine whether state-of-the-art Machine Learning tech- nology for text analysis could effectively discern the intent behind radical actions from user-generated content. We analyzed a diverse array of radical texts published online by various activists, including anarchists, Iranian guerrilla members, Indian revolution- aries, activists from the US civil rights movement, and The Army of God. Our analysis reveals that Machine Learning models can successfully identify potential signals indica- tive of the author’s intent behind radical actions.

VOX-Pol Blog post.

VOX-Pol Blog post.