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The purpose of this scoping review is to highlight the machine learning tools used in research to address and prevent violent extremism. To achieve this goal, the following objectives guide this study: (1) describe outcomes that have been studied; (2) summarize the data sources used; and (3) determine whether the reporting of machine learning predictive models aligns with the established reporting guidelines for reporting of prediction models. ProQuest, Compendex, IEEE, JStor and PubMed were searched from June to July 2022. Based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines, databases were searched for articles related to machine learning models applied to the address and prevention of violent extremism. Following standards established by reporting guidelines, findings were extracted from published articles, including general study characteristics, aspects of model development, and reporting of results. Of 53 unique articles identified by the search, 18 were included in the review. Most articles were published between 2016 and 2022 (n = 16, 88.8%). Studies focused on violent extremism worldwide, with the majority of studies not specifically focused on a distinct region (n = 11, 61.1%). The most frequently used machine learning algorithms were support vector machines (n = 9, 50%), followed by random forests (n = 5, 27.7%), natural language processing (n = 4, 22.2%), and deep learning (n = 4, 22.2%). The number of features used varied greatly, ranging from 17 to 7556. Many studies did not report an epistemological or theoretical framework which guided their machine learning approaches or interpretation of findings (n = 8, 44.4%). Many studies did not incorporate the TRIPOD or any other recommended guidelines for the reporting of predictive models. Future research in this field should prioritize evaluating the impact of prediction models on decisions for addressing and preventing violent extremism.

We are on the cusp of a “Big Data” Revolution, in which increasingly large datasets are mined for important predictions and often surprising insights. The predictions and decisions this revolution will enable will transform our society in ways comparable to the Industrial Revolution. We are now at a critical moment; big data uses today will be sticky and will settle both default norms and public notions of what is “no big deal” regarding big data predictions for years to come.
This paper argues that big data, broadly defined, is producing increased powers of institutional awareness and power that require the development of a Big Data Ethics. We are building a new digital society, and the values we build or fail to build into our new digital structures will define us. Critically, if we fail to balance the human values that we care about, like privacy, confidentiality, transparency, identity and free choice with the compelling uses of big data, our Big Data Society risks abandoning these values for the sake of innovation and expediency.

Expressions of ‘eco-fascism’ are said to entail ethnonationalist actors advocating extreme population control measures, and accelerationists hastening the collapse of societies worldwide. These expressions emerge from political-ideological environments in which Global North actors have erroneously assigned blame for climate change with the Global South, through rhetoric about migration, population control and fossil fuel usage. To assess the influence of these themes in the development of eco-fascist ideologies online, this paper presents insights from a mixed-methods analysis of climate change discussions on Stormfront; the first dedicated online white nationalist media platform still drawing cross-national participation and viewership from generalized public audiences.

In recent years, there has been an intensification of international extremist violence linked in varying degrees to Internet-facilitated radicalisation. This has related to, among other things, a growth in prevalence of politically violent actors, including far-right and jihadist collectives. Extreme political polarisation, sometimes termed the ‘hyper-tribalism’ of those with violent or extreme views, is to some extent reinforced by these entities’ participation in social media. Radicalisation to terrorism is also arguably facilitated by the architectures of social media platforms, which comprise of personalisation algorithms and the re-mediating functions of ‘likes’, ‘shares’, and ‘re-tweets’ (Sunstein 2009; Pariser 2011; Wood 2017). This chapter reflects on characteristics of social media that can be perceived to encourage violent extremism and terrorism, and legal, security, and technological measures that have been developed internationally to prevent and counter online violent extremist expression. With reference to recent terrorism-related trends, it also highlights a disparity in legal measures to address far-right hate speech (Gelber & McNamara 2016; Davey et al. 2018), relative to thoseused to police and restrict online activity related to jihadism (Conway et al. 2018).

This chapter illustrates that online and offline measures to counter violent extremism in Australia have targeted jihadism over other forms of extremism. With attention to the open and intensifying state of far-right extremism in Australia, it advocates for increased attention to this situation. It contends that, given the recursive nature of online extremism and its political and international dimensions, material disseminated by far-right and jihadist groups should be addressed from a comparative perspective.

This article analyzes ideological and organizational characteristics of the pan-European youth movement, “Generation Identity” (GI), through a philosophical and historical lens. With a synoptic perspective on existing and original research, it outlines an analysis of key GI literature as well as its ideological influences, activist behavior, and media strategies. This research reveals that, like other twentieth and twenty-first century examples of neo-fascism, the movement is syncretic and attempts to legitimize its political aims through reference to historical quasi- and proto-fascist cases, in combination with popular left and right-wing political ideals. A reflection on GI’s activist behavior, on the other hand, demonstrates that the movement is relatively unique in the field of current far-right politics; particularly in the extent to which it draws practical inspiration from the tactics and propagandizing strategies of contemporary left-wing movements. GI’s online presence, including its leaders’ promotion of gamification, also illustrates its distinctive appeal to young, relatively affluent, countercultural and digitally literate populations. Finally, while in many respects GI is characteristic of the “European New Right” (ENR), the analysis finds that its spokespersons’ various promotion of capitalism and commodification, including through their advocacy of international trade and sale of merchandise, diverges from the anti-capitalist philosophizing of contemporary ENR thinkers.