Interpersonal Trust and Criminal Network Resilience: Computer Simulations of Law Enforcement Interventions

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Abstract

The dynamics of trust is a scarcely studied, let alone understood, concept in the context of criminal networks. We outline a proposed project in which we plan to investigate how trust between actors in a criminal network impacts the network’s vulnerability to law enforcement interventions that aim to dismantle and disrupt such a network. We plan to use computer simulations to estimate how quickly a criminal network will be dismantled by law enforcement intervention given varying trust parameters. We will simulate a network characterized by high trust, and the same network characterized by low trust, and compare a range of law enforcement strategies under these two conditions. Using computer-generated models, we will incorporate targeting strategies used in previous research on criminal network adaptation (see Bright et al., 2017): targeting actors by maximum closeness centrality (here found to be most effective), maximum betweenness centrality (previously found to be very effective), money targeting, maximum degree centrality, and targeting actors randomly (previously found to be least effective). Preliminary results suggest that the network breaks down more quickly when connections depend on trust. Low trust between actors renders the network more vulnerable, both when trust is randomly assigned and when trust is assigned according to dyadic connections.

Authors

• David Bright, Flinders University

• Thomas Britz, University of New South Wales, Sydney