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Applying cutting-edge psychiatric theories to an analysis of online Taliban literature in four languages, Neil Krishan Aggarwal constructs a game-changing narrative of the organization’s broad appeal and worldview.
Aggarwal focuses on the Taliban’s creation of culture, evoking religion in Arabic and English writings, nationalism in Dari sources, and regionalism in Urdu texts. The group also promotes a specific form of argumentation, citing religious scriptures in Arabic works, canonical poets in Dari and Urdu writings, and scholars and journalists in English publications. We see clearly how the Taliban categorizes all Muslims as members and all non-Muslims as outsiders; how they convince Muslims of the need for violence; and how they apply the insider/outside dichotomy to foreign policy. By isolating these themes, Aggarwal helps us craft better counter-messaging strategies.

Since the declaration of the War on Terror in 2001, militant groups such as al-Qaeda and the Islamic State have used the internet to disseminate their message and persuade people to commit violence. While many books have studied their operational strategies and battlefield tactics, Media Persuasion in the Islamic State is the first to analyze the culture and psychology of militant persuasion.

Drawing upon decades of research in cultural psychiatry, cultural psychology, and psychiatric anthropology, Neil Krishan Aggarwal investigates how the Islamic State has convinced people to engage in violence since its founding in 2003. Through analysis of hundreds of articles, speeches, videos, songs, and bureaucratic documents in English and Arabic, the book traces how the jihadist Abu Musab al-Zarqawi created a new culture and psychology, one that would pit Sunni Muslims against all others after the U.S.-led invasion of Iraq. Aggarwal tracks how Osama bin Laden and al-Zarqawi disagreed over the goal of militancy in jihad before reaching a détente in 2004 and how al-Qaeda in Iraq merged with five other groups to diffuse its militant cultural identity in 2006 before taking advantage of the Syrian civil war to emerge as the Islamic State. Aggarwal offers a definitive analysis of how culture is created, debated, and disseminated within militant organizations like the Islamic State. Psychiatrists, psychologists, and area-studies experts will find a comprehensive, systematic method for analyzing culture and psychology so they can partner with political scientists, policy makers, and counterterrorism experts in crafting counter-messaging strategies against militants.

This paper will examine how extremist organizations manage to present themselves as credible actors in the eyes of potential supporters on social media. This paper will address this question by exploring the role of authenticity in strategic narratives, which is believed to help these groups achieve this purpose. Apart from introducing this new theoretical concept, the paper will also apply it to a new case study of the Russian Imperial Movement (RIM) – the first far-right organization to be designated as terrorist by the U.S. and Canada. By conducting discourse analysis of the group’s social media propaganda on the Russian network VKontakte, the paper will show how the RIM makes its strategic narratives authentic and, as a consequence, creates an image of a credible and trustworthy actor and thus manages to reach out to its target audience.

Since the beginning of 2021, ISD Germany has been researching right-wing extremist actors on alternative platforms on the internet. Three reports were published as part of the German Federal Ministry for Justice (BMJ)-funded project “Countering radicalisation in right-wing extremist online subcultures”. The last report in 2021, “Detours and Diversions – Online Strategies for the Dissemination of Right-Wing Extremist Content”, provides a summary of the projects central findings and presents them in a comparative manner.

This report thus combines the methodological and theoretical groundwork of the report “Wegweiser” with the results of the empirical research of the reports “Fluchtwege” and “Stützpfeiler Telegram”, and puts them into context. The report presents a comparison of data from established platforms and Telegram, and thus helps to gain a better understanding of the behaviour of far-right actors on the selected platforms. It also includes a comparative analysis of the strategies and linkages of far-right and radical right actors on established and alternative platforms. This research is based on the empirical data collected by the platforms. Given, that data collection is different for each platform, and given that this project also explores alternative platforms, it also furthers the exploration of data collection options, which are described in more detail in this report.

Terror attacks have been linked in part to online extremist content. Although tens of thousands of Islamist extremism supporters consume such content, they are a small fraction relative to peaceful Muslims. The efforts to contain the ever-evolving extremism on social media platforms have remained inadequate and mostly ineffective. Divergent extremist and mainstream contexts challenge machine interpretation, with a particular threat to the precision of classification algorithms. Our context-aware computational approach to the analysis of extremist content on Twitter breaks down this persuasion process into building blocks that acknowledge inherent ambiguity and sparsity that likely challenge both manual and automated classification. We model this process using a combination of three contextual dimensions — religion, ideology, and hate — each elucidating a degree of radicalization and highlighting independent features to render them computationally accessible. We utilize domain-specific knowledge resources for each of these contextual dimensions such as Qur’an for religion, the books of extremist ideologues and preachers for political ideology and a social media hate speech corpus for hate. Our study makes three contributions to reliable analysis: (i) Development of a computational approach rooted in the contextual dimensions of religion, ideology, and hate that reflects strategies employed by online Islamist extremist groups, (ii) An in-depth analysis of relevant tweet datasets with respect to these dimensions to exclude likely mislabeled users, and (iii) A framework for understanding online radicalization as a process to assist counter-programming. Given the potentially significant social impact, we evaluate the performance of our algorithms to minimize mislabeling, where our approach outperforms a competitive baseline by 10.2% in precision.