This article describes the development of foreign fighters’ preparatory modes of operation between 2000 and 2013, based on an analysis of 17 closed police investigations and 21 semi-structured interviews with police investigators, public prosecutors, and lawyers. Through the use of grounded theory methods and a crime script analysis, we find that the phenomenon is not as new as is often portrayed. It changes over time as changing opportunity structures have an impact on the activities foreign fighters undertake during the preparation phase. We demonstrate how geopolitical changes, social opportunity structures, and technological developments affect themodus operandiover time. One of the implications of our findings is that the dynamic nature of the foreign fighting phenomenon requires flexible and tailored prevention measures.
Crime script analysis as a methodology to analyse criminal processes is underdeveloped. This is apparent from the various approaches in which scholars apply crime scripting and present their cybercrime scripts. The plethora of scripting methods raise significant concerns about the reliability and validity of these scripting studies. In this methodological paper, we demonstrate how object-oriented modelling (OOM) could address some of the currently identified methodological issues, thereby refining crime script analysis. More specifically, we suggest to visualise crime scripts using static and dynamic modelling with the Unified Modelling Language (UML) to harmonise cybercrime scripts without compromising their depth. Static models visualise objects in a system or process, their attributes and their relationships. Dynamic models visualise actions and interactions during a process. Creating these models in addition to the typical textual narrative could aid analysts to more systematically consider, organise and relate key aspects of crime scripts. In turn, this approach might, amongst others, facilitate alternative ways of identifying intervention measures, theorising about offender decision-making, and an improved shared understanding of the crime phenomenon analysed. We illustrate the application of these models with a phishing script.
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