Online Library

The literature shows that there are two fields that can feed radicalization, online and offline domains. However, the arbitrary separation has been challenged since radicalised individuals use both domains for their activities and they seamlessly move across the two (Pauwels & Schils, 2016; Gill et al., 2017; Whittaker, 2022). Furthermore, most scholars today agree that radicalization is not a linear or a step-by-step process, but rather a multifactorial phenomenon (Frissen, 2021), where different mechanisms operate in different ways for different people in different contexts (Borum, 2011). 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.

The policy brief makes the case that policymakers and practitioners need to consider who the state defines as ‘extremists.’ In the West, terrorism and violent extremism are seen as the most radical expressions of anti-government resistance. Things, however, look different in the Global South where some governments effectively foster extremists of their own while targeting legitimate and often nonviolent opposition. Echoes of such an approach are also present in Europe where certain (semi-) authoritarian governments securitise their responses to political dissent while seemingly drawing inspiration from more autocratic regimes outside this continent. Thus, in their case, an attempt to counter real or imagined extremism could consequently and likewise lead them to foster extremists of their own.

Current literature on online criminal and deviant groups recognizes the role of online forums in the transfer of knowledge and socialization of members, but debates on the role of the Internet in the socialization and radicalization processes in the context of online extremist groups. This study contributes to the discussion by examining online radicalization process through the use of social learning theory and social network analysis. This innovation allows for assessment on the impact of online interactions with forum members on radicalization process. Findings found strong support of differential association and differential reinforcement, but showed the possibility of other mechanisms, such as self-radicalization, at play. Findings from the study highlight the need to for theory integration, the inclusion of online peer association, and replication to address the complex phenomenon of online radicalization.

Major social media platforms have recently taken a more proactive stand against harmful far-right content and pandemic-related disinformation on their sites. However, these actions have catalysed the growth of fringe online social networks for participants seeking right-wing content, safe havens, and unhindered communication channels. To better understand these isolated systems of online activity and their success, the study on Gab Social examines the mechanisms used by the far right to form an alternative collective on fringe social media. My analysis showcases how these online communities are built by perpetuating meso-level identity-building narratives. By examining Gab’s emphasis on creating its lasting community base, the work offers an experiential examination of the different communication devices and multimedia within the platform through a netnographic and qualitative content analysis lens. The emergent findings and discussion detail the far right’s virtual community-building model, revolving around its sense of in-group superiority and the self-reinforcing mechanisms of collective. Not only does this have implications for understanding Gab’s communicative dynamics as an essential socialisation space and promoter of a unique meso-level character, but it also reflects the need for researchers to (re)emphasise identity, community, and collectives in far-right fringe spaces.

From politicians to podcast hosts, online platforms have systematically banned (“deplatformed”) influential users for breaking platform guidelines. Previous inquiries on the effectiveness of this intervention are inconclusive because 1) they consider only few deplatforming events; 2) they consider only overt engagement traces (e.g., likes and posts) but not passive engagement (e.g., views); 3) they do not consider all the potential places users impacted by the deplatforming event might migrate to. We address these limitations in a longitudinal, quasi-experimental study of 165 deplatforming events targeted at 101 influencers. We collect deplatforming events from Reddit posts and then manually curate the data, ensuring the correctness of a large dataset of deplatforming events. Then, we link these events to Google Trends and Wikipedia page views, platform-agnostic measures of online attention that capture the general public’s interest in specific influencers. Through a difference-in-differences approach, we find that deplatforming reduces online attention toward influencers. After 12 months, we estimate that online attention toward deplatformed influencers is reduced by -63% (95% CI [-75%,-46%]) on Google and by -43% (95% CI [-57%,-24%]) on Wikipedia. Further, as we study over a hundred deplatforming events, we can analyze in which cases deplatforming is more or less impactful, revealing nuances about the intervention. Notably, we find that both permanent and temporary deplatforming reduce online attention toward influencers; Overall, this work contributes to the ongoing effort to map the effectiveness of content moderation interventions, driving platform governance away from speculation.