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This report analyses the networks and narratives of German-speaking far-right, far-left and Islamist extremist actors on mainstream and alternative social media platforms and extremist websites in the context of the COVID-19 pandemic. Our results show: Extremists from Germany, Austria and Switzerland have been able to increase their reach since the introduction of the lockdown measures.

In this report, we present an empirical cross-national study of supporters of right-wing extremists’ (RWE) and Islamist extremists’ (ISE) activities and interactions on Twitter. The study is based on
ethnographic and automatic text and network analyses of data from Belgian, British, Dutch, French, German, Greek and Norwegian female and male Twitter accounts.

The primary objective of this paper is to map the online presence of Hayat Tahrir al-Sham’s (HTS) media branch – Ebaa News Agency (ENA) – on the surface web. It also measures three years of propaganda output of the group and its viewership, as well as outlines the thematic landscape of its productions based on the content analysis of a sample. It argues that Ebaa’s messaging pattern constitutes a peculiar mixture of opposing priorities. It paid a great deal of attention to portraying itself as an independent news agency that has nothing to do with violent terrorist organizations (VEOs). In effect, its productions are easily available on the surface web. A closer look, however, proves that since 2017 ENA has been dedicated to supporting HTS’s radical Islamist agenda. This paper provides evidence of this. Moreover, Ebaa adopted a two-vector distribution strategy of its productions, composed of standalone websites and Telegram channels. In this context, the output of this media cell appears to be quite impressive. Between 2017 and 2020, it was capable of releasing more than 13,000 pieces of propaganda on its websites. At the same time, however, their viewership was lower than initially expected.

VOX-Pol Blog Post.

Crowdfunding platforms remain understudied as conduits for ideological struggle. While other social media platforms may enable the expression of hateful and harmful ideas, crowdfunding can actively facilitate their enaction through financial support. In addressing such risks, crowdfunding platforms attempt to mitigate complicity but retain legitimacy. That is, ensuring their fundraising tools are not exploited for intolerant, violent or hate-based purposes, yet simultaneously avoiding restrictive policies that undermine their legitimacy as ‘open’ platforms. Although social media platforms are routinely scrutinized for enabling misinformation, hateful rhetoric and extremism, crowdfunding has largely escaped critical inquiry, despite being repeatedly implicated in amplifying such threats. Drawing on the ‘Freedom Convoy’ movement as a case study, this article employs critical discourse analysis to trace how crowdfunding platforms reveal their underlying values in privileging either collective safety or personal liberty when hosting divisive causes. The radically different policy decisions adopted by crowdfunding platforms GoFundMe and GiveSendGo expose a concerning divide between ‘Big Tech’ and ‘Alt-Tech’ platforms regarding what harms they are willing to risk, and the ideological rationales through which these determinations are made. There remain relatively few regulatory safeguards guiding such impactful strategic choices, leaving crowdfunding platforms susceptible to weaponization. With Alt-Tech platforms aspiring to build an ‘alternative internet’, this paper highlights the urgent need to explore digital constitutionalism in the crowdfunding space, establishing firmer boundaries to better mitigate fundraising platforms becoming complicit in catastrophic harms.

This systematic review explores the utilization of crowdsourcing for geoinformation in enhancing awareness and mitigating terrorism-related disasters. Out of 519 studies identified in the database search, 108 were deemed eligible for analysis. We focused on articles employing various forms of crowdsourcing platforms, such as Twitter (now known as X), Facebook, and Telegram, across three distinct phases of terrorism-related disasters: monitoring and detection, onset, and post-incident analysis. Notably, we placed particular emphasis on the integration of Machine Learning (ML) algorithms in studying crowdsourced terrorism geoinformation to assess the current state of research and propose future directions. The findings revealed that Twitter emerged as the predominant crowdsourcing platform for terrorism-related information. Despite the prevalence of natural language processing for data mining, the majority of studies did not incorporate ML algorithms in their analyses. This preference for qualitative research methods can be attributed to the multifaceted nature of terrorism, spanning security, governance, politics, religion, and law. Our advocacy is for increased studies from the domains of geography, earth observation, and big data. Simultaneously, we encourage advancements in existing ML algorithms to enhance the accurate real-time detection of planned and onset terrorism disasters.