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This chapter will examine the role of the Internet and associated technology such as the Internet of Things (IoT) and cloud computing (CC) in the process of radicalisation to terrorism and violent extremism. Particular emphasis will be placed upon the role of online environments in facilitating communication and the spread of extremist ideology, as opposed to operational and strategic recruiting functions of the Internet. Before assessing the debate, this chapter shall define two key concepts, radicalisation and violent extremism. Firstly, the chapter will provide an assessment of academic literature that has perpetuated a false offline and online dichotomy. Then, the chapter will demonstrate the new communicative role of technology within violent extremist movements since the emergence of Web 2.0. Following this, Sageman’s (Leaderless Jihad: Terror networks in the twenty-first century, University of Pennsylvania Press, 2008) ‘bunch of guys’ bottom-up framework will be employed to understand how the process of radicalisation can be facilitated and amplified by the digital age, referring to the concepts of moral outrage, othering, virtual communities and echo chambers. Lastly, contemporary literature that considers the interplay between online and offline domains will be explored.

Emerging alongside the progression of women’s rights in the twenty-first century is the development of the men’s rights movement, parts of which have culminated into the contemporary ‘manosphere.’ Consisting of online communities that ascribe to misogynistic ideologies, which objectify, disparage, and dehumanise women, the manosphere also houses those who identify as involuntary celibate (incel).

This article examines the radicalization of young adults in relation to internet access and the social media content produced and managed by radical groups in Indonesia. Some of the research problems that become the major concern of this article were how young people respond to the internet and social media that provide radical content, how they find out about and access the content, what their purposes are for accessing radical content, and what they do with the radical content. The data discussed in this article were obtained from surveys and interviews with 700 students from seven state universities in Indonesia who were allegedly exposed to radicalism, according to the National Agency for Combating Terrorism (BNPT). The state universities that became research locations were the University of Indonesia (UI), Bandung Institute of Technology (ITB), Bogor Agriculture University (IPB), Diponegoro University (Undip), the Sepuluh Nopember Institute of Technology (ITS), Universitas Airlangga (UNAIR), and the University of Brawijaya (UB). This study revealed that in addition to accessing and consuming various radical content, some students also acted as prosumers. That is, they did not only read, but also produced information related to radicalization, and then recirculated it via social media.

Polarization is implicated in the erosion of democracy and the progression to violence, which makes the polarization properties of large algorithmic content selection systems (recommender systems) a matter of concern for peace and security. While algorithm-driven social media do not seem to be a primary driver of polarization at the country level, they could be a useful intervention point in polarized societies. This paper examines algorithmic depolarization interventions aimed at transforming conflict: not suppressing or eliminating conflict, but making it more constructive. Algorithmic intervention is considered at three stages: what content is available (moderation), how content is selected and personalized (ranking), and content presentation and controls (user interface). Empirical studies of online conflict suggest that not only could the exposure-diversity intervention proposed as an antidote to ‘filter bubbles’ be improved: under some conditions, it can even worsen polarization. Using civility metrics in conjunction with diversity in content selection may be more effective. However, diversity-based interventions have not been tested at scale, and may not work in the diverse and dynamic contexts of real platforms. Instead, intervening in platform polarization dynamics will likely require continuous monitoring of polarization metrics, such as the widely used ‘feeling thermometer’. These metrics can be used to evaluate product features, and can potentially be engineered as algorithmic objectives. While using any metric as an optimization target may have harmful consequences, to prevent optimization processes from creating conflict as a side effect it may prove necessary to include polarization measures in the objective function of recommender algorithms.

VOX-Pol Blog post.

VOX-Pol Blog post.