Islamic terrorism in Germany – the use of social network analysis to detect high-risk criminal networks

Authors

DOI:

https://doi.org/10.3013/57bdcd15

Keywords:

radicalisation, terrorism, covert networks, social network analysis, police training

Abstract

This article pays particular attention to the networks of homegrown terrorist in Germany who were engaged in conflicts and war zones in Syria, Iraq, and Africa by ISIS (and other terrorist organisations). Based on the combination of a court file analysis and social network analysis it was possible to highlight a network with 255 persons and 650 connections, key actors and the infrastructure of the network itself. This article presents the social network analysis as a possible tool for police investigations on how to detect terroristic networks as high-risk networks. Using the example of a terrorist network from Germany, it is possible to explain how terrorist networks are organised and how they can be destabilised or even disrupted. By identifying relevant key players and subgroups, their connections and position within the network it is possible to gain a deeper understanding on radicalisation and create more effective counter-terrorism strategies.

Author Biography

  • Kristin Weber, Centre for Criminological Research

    Dr Kristin Weber is a criminologist and sociologist. Since April 2023, she has been working as a postdoctoral researcher at the Center for Criminological Research Saxony (ZKFS) in Chemnitz. At ZKFS, she leads a research project on prejudice-motivated crime and the recording system for politically motivated criminal offences.

    Her research focuses on extremism, radicalisation, and terrorism studies, file-based and social network analysis, as well as practice-oriented police research.

    Before joining ZKFS, she worked at the German Police University (DHPol) from 2015 until March 2023. There, she was involved in several research projects, including X-Sonar: Analysis of Extremist Tendencies in Social Networks (funded by the Federal Ministry of Education and Research) and ZURECHT – The Police in an Open Society (funded by the Mercator Foundation). She received her doctorate from the German Police University.

    Research Interest

    • Radicalization and Extremism

    Islamism, Salafism and Jihadism, right wing extremism/white supremacy; socialization processes into religiously/politically motivated violence; transnational Islamist movements.

    Radicalization trajectories and dynamics; pathways into violent extremism and terrorism; psychosocial drivers; ideology and narrative formation; identity, gender, masculinity.

    (Social ) Networks, recruitment strategies, online and offline radicalization (social media e.g. TikTok)

    • Terrorist Organizations and Militant Networks

    Jihadist organizations such as ISIS and ISKP; transnational militant structures; recruiter–follower dynamics; affiliations and facilitators; governance strategies within terrorist entities, financially support of terrorist organizations

    • Digital Extremism and Online Mobilization

    Extremist use of social media platforms (esp. TikTok, Telegram, Instagram); algorithmic radicalization and online affect; AI-driven propaganda and digital recruitment strategies.

    • Bias-Motivated and Hate Crime

    Right-wing extremism and white supremacy; antisemitism and misogyny in extremist milieus (e.g., Incels); political violence and prejudice-driven crime in comparative perspective.

    • Methodology (qualitative and quantitative)

    Qualitative and mixed-method approaches to studying radical milieus (e.g., court file analysis, social network analysis), interdisciplinary research between criminology, political sociology, and psychology; application of SNA in terrorism studies. Grounded Theory, Expert interviews, case studies, biography analysis, evaluation and many more

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Published

31-08-2026

How to Cite

Islamic terrorism in Germany – the use of social network analysis to detect high-risk criminal networks. (2026). European Law Enforcement Research Bulletin, 7(1). https://doi.org/10.3013/57bdcd15