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Researchers have used SNA and computer simulations to evaluate the impact of law enforcement interventions designed to dismantle and disrupt criminal networks. Previous simulations tend to use simplistic scenarios (e.g., sequential “arrest” of actors with the highest number of connections in the network) and rarely model network adaptation (e.g., replacement of “arrested” actors). The aim of the current project was to design and test a realistic range of law enforcement interventions against criminal networks. Data on a drug trafficking network was extracted from criminal justice files. As well as the topology of the network, the data included node-level and link-level attributes, reflecting the skills and resources of the individuals or the relationships within the networks. These attributes were also provided as input to the simulations. Law enforcement simulations included interventions hypothesized to be effective (targeting a particular critical resource e.g., money, drugs) and interventions hypothesized to be ineffective (targeting actors low in degree and betweenness). Another simulation aimed to break the network into a small number of highly centralized fragments. Outcome measures of dismantlement and disruption included a fragmentation measure, a measure of key expertise within the network, and a measure of the disruption of the flow of key resources. Network adaptation was incorporated into the simulations by modelling replacement of removed actors. Implications for law enforcement investigations and interventions are discussed.
David Anthony Bright, University of New South Wales, Australia
Catherine Greenhill, University of New South Wales
Alison Ritter, University of New South Wales
Thomas Britz, University of New South Wales, Australia
Carlo Morselli, Université de Montréal