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Why do people engage in violent extremism? Why do people deem killing others as a reasonable way – the only reasonable way – to get their political voice heard? How do driving a cargo truck into crowds on a promenade or shooting at random believers in a mosque come to be seen as legitimate alternatives? The short answer is that we have no answer. However, over the last 20 years, radicalization has been the cornerstone concept used by academics, media and policymakers to describe how ordinary individuals become violent extremists. Radicalization outlines the process of embracing an extremist ideology and justifying or perpetrating violent actions in the name of such ideology. Originally, the purpose of this concept was to investigate the roots behind the series of jihadist terrorist attacks that shook the heart of Western democracies at the beginning of the 21st century. For instance, the train bombings of Madrid (2004) and London (2005) with a combined death toll of 249 civilians were not carried out by Islamists educated under the banner of Al-Qaeda sponsored madrassas but by second-generation immigrants born and raised within the liberal social fabric of the European Union. As a result, these attacks were labelled cases of homegrown terrorism and their causes were linked to the perpetrators “acting out” a violent Islamist ideology. Explanations harkening back to situational factors like group structure and settings were difficult to digest at that time, probably because it would have amounted to admitting that Western societies could prepare the structural soil conducive to jihadist terrorism. More comforting was framing the perpetrators as vulnerable individuals who fell prey to the luring speeches of unscrupulous recruiters (e.g., preachers, combatants) and led the former to reach the “tipping point” and turn the words into actions (Crone 2016).

Most analyses of far-right communication on social media focus on one specific platform, while findings are generalized. In this study, I argue that the far right’s use of social media depends on technology affordances – the linkage between platform design and usage – and, thus, might not always be generalizable. After discussing six affordances – persistence, scalability, replicability, connectivity, searchability, and identifiability – I apply them to studies about the far right on Facebook, Twitter, Instagram, YouTube, and Telegram in a systematic literature review. I conclude that most research focuses on aspects linked to connectivity, scalability, and replicability, while persistence, searchability, and identifiability are barely researched so far. I further discuss shortcomings and possibilities for future research to consider aspect of technology affordances.

Research examining radical visual communication and its manifestation on the trending platform TikTok is limited. This paper presents a novel methodological framework for studying mobilization strategies of far-right groups on TikTok, employing a mixed-method approach that combines manual annotation, unsupervised image classification, and named-entity recognition to analyze the dynamics of radical visuals at scale. Differentiating between internal and external mobilization, we use popularity and engagement cues to investigate far-right mobilization efforts on TikTok within and outside their community. Our findings shed light on the effectiveness of unsupervised image classification when utilized within a broader mixed-method framework, as each observed far-right group employs unique platform characteristics. While Conspiracists flourish in terms of overall popularity and internal mobilization, nationalist and protest content succeeds by using a variety of persuasive visual content to attract and engage external audiences. The study contributes to existing literature by bridging the gap between visual political communication at scale and radicalization research. By offering insights into mobilization strategies of far-right groups, our study provides a foundation for policymakers, researchers, and online platforms to develop proactive measures to address the risks associated with the dissemination of extremist ideologies on social media.

Do social media companies exacerbate antisemitism and hate through their own recommendation and amplification tools? We investigated how four of the biggest social media platforms treated users who searched for or engaged with content related to anti-Jewish tropes, conspiracy theories, and other topics. Three of them–Facebook, Instagram, and Twitter1 (now known as X after a rebranding by owner Elon Musk)–filled their feeds with far more antisemitic content and conspiratorial accounts and recommended the most hateful influencers and pages to follow. One platform, YouTube, did not.

In this joint study by the ADL Center for Technology and Society (CTS) and Tech Transparency Project (TTP), researchers created six test personas of different ages and genders and set up accounts for them on Facebook, Instagram, Twitter, and YouTube. Researchers had them search each platform for a basket of terms related to conspiracy theories as well as popular internet personalities, commentators, and video games. The study then examined the content that the platforms’ algorithms recommended to these hypothetical users.

Do social media and search companies exacerbate antisemitism and hate through their own design and system functions? In this joint study by the ADL Center for Technology and Society (CTS) and Tech Transparency Project (TTP), we investigated search functions on both social media platforms and Google. Our results show how these companies’ own tools–such as autocomplete and auto-generation of content–made finding and engaging with antisemitism easier and faster.1 In some cases, the companies even helped create the content themselves.

Our researchers compiled a list of 130 hate groups and movements from ADL’s Glossary of Extremism, picking terms that were tagged in the glossary with all three of the following categories: “groups/movements,” “white supremacist,” and “antisemitism.”2 The researchers then typed each term into the respective search bars of Facebook, Instagram and YouTube, and recorded the results.