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Some moderation strategies of online content have targeted the individuals believed to be the most influential in the diffusion of such material, while others have focused on censorship of the content itself. Few approaches consider these two aspects simultaneously. The present study addresses this gap by showing how a socio-semantic network analysis can help identify individuals and subgroups who are strategically positioned in radical networks and whose comments encourage the use of violence. It also made it possible to identify the individuals and subgroups who act as intermediaries and whose statements are often the most violent.

Disrupting the emergence and evolution of potentially violent online extremist movements is a crucial challenge. Extremism research has analyzed such movements in detail, focusing on individual- and movement-level characteristics. But are there system-level commonalities in the ways these movements emerge and grow? Here we compare the growth of the Boogaloos, a new and increasingly prominent U.S. extremist movement, to the growth of online support for ISIS, a militant, terrorist organization based in the Middle East that follows a radical version of Islam. We show that the early dynamics of these two online movements follow the same mathematical order despite their stark ideological, geographical, and cultural differences. The evolution of both movements, across scales, follows a single shockwave equation that accounts for heterogeneity in online interactions. These scientific properties suggest specific policies to address online extremism and radicalization. We show how actions by social media platforms could disrupt the onset and ‘flatten the curve’ of such online extremism by nudging its collective chemistry. Our results provide a system-level understanding of the emergence of extremist movements that yields fresh insight into their evolution and possible interventions to limit their growth.

The independent Commission for Countering Extremism has published a legal review, to examine whether existing legislation adequately deals with hateful extremism.

Acts of terror lead to both a rise of an extended sense of fear that goes beyond the physical location of the attacks and to increased expressions of online hate. In this longitudinal study, we analyzed dynamics between the exposure to online hate and the fear of terrorism after the Paris attacks in November 13, 2015. We hypothesized that exposure to online hate is connected to a perceived Zeitgeist of fear (i.e., collective fear). In turn, the perceived Zeitgeist of fear is related to higher personal fear of terrorism both immediately after the attacks and a year later. Hypotheses were tested using path modeling and panel data (N = 2325) from Norway, Finland, Spain, France, and the United States a few weeks after the Paris attacks in November 2015 and again a year later in January 2017. With the exception of Norway, exposure to online hate had a positive association with the perceived Zeitgeist of fear in all our samples. The Zeitgeist of fear was correlated with higher personal fear of terrorism immediately after the attacks and one year later. We conclude that online hate content can contribute to the extended sense of fear after the terrorist attacks by skewing perceptions of social climate.

Moonshot partnered with the Anti-Defamation League (ADL) to analyze US search traffic in response to the threats posed by white supremacist narratives and ideology in the US this past year. The dominant socio-political events of 2020-2021—the COVID-19 pandemic, the widespread BLM protests and counter-protests, and the presidential election—coalesced to create fertile ground for white supremacists and other violent extremist movements to mobilize and recruit. From 18 August 2020 – 7 March 2021, we recorded 511,759 white supremacist searches across the United States. We identified trends such as anti-Black search traffic, interest in anti-Semitic conspiracy theories, and a sustained appetite for “The Great Replacement” conspiracy theory. Ultimately, we found that offline events seemed to catalyze search traffic for extremist content online.

Objective: This paper applies Reinforcement Sensitivity Theory to explain the role of exposure to violent extremist content online in the wider psychological process of “radicalization.” Reinforcement Sensitivity Theory is a suitable theory to apply to this domain given that (a) the motivation to engage in violent extremism is widely discussed, yet motivational theories are rarely applied and (b) current risk factors for engagement in violent extremist behavior show a high degree of overlap with core Reinforcement Sensitivity Theory variables (e.g., impulsivity and social dominance). Method: This study uses an experimental design in which 479 participants from Amazon’s Mechanical Turk were randomly assigned one of two short vignettes (violent extremist/violent nonextremist) to frame the content of a social media-based behavioral task. The effect of exposure to violent extremist content online on intentions for political mobilization was measured via the Activism and Radicalism Intentions Scale. Results: While exposure to online violent extremist content did not increase tendencies for political mobilization, Behavioral Activation System traits were positively associated with the willingness to engage with violent extremist content online and with intentions for political mobilization. Conclusions: Behavioral Activation System traits provide a possible avenue to explain individual differences in the process of radicalization and the potential relevance of Reinforcement Sensitivity Theory for theories of radicalization provides further evidence that new knowledge that can be gleaned by applying established psychological theories to the study of radicalization.