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Radicalization Trajectories: An Evidence-Based Computational Approach to Dynamic Risk Assessment of “Homegrown” Jihadists

Author

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  • Jytte Klausen
  • Rosanne Libretti
  • Benjamin W. K. Hung
  • Anura P. Jayasumana

Abstract

The research aimed to develop and test a new dynamic approach to preventive risk assessment of violent extremists. The well-known New York Police Department four-phase model was used as a starting point for the conceptualization of the radicalization process, and time-stamped biographical data collected from court documents and other public sources on American homegrown Salafi-jihadist terrorism offenders were used to test the model. Behavioral sequence patterns that reliably anticipate terrorist-related criminality were identified and the typical timelines for the pathways to criminal actions estimated for different demographic subgroups in the study sample. Finally, a probabilistic simulation model was used to assess the feasibility of the model to identify common high-frequency and high-risk sequential behavioral segment pairs in the offenders’ pathways to terrorist criminality.

Suggested Citation

  • Jytte Klausen & Rosanne Libretti & Benjamin W. K. Hung & Anura P. Jayasumana, 2020. "Radicalization Trajectories: An Evidence-Based Computational Approach to Dynamic Risk Assessment of “Homegrown” Jihadists," Studies in Conflict and Terrorism, Taylor & Francis Journals, vol. 43(7), pages 588-615, July.
    • Handle: RePEc:taf:uterxx:v:43:y:2020:i:7:p:588-615
    DOI: 10.1080/1057610X.2018.1492819
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