Criminal network dynamics: The formation and evolution of a drug trafficking network.

David Bright, Aili Malm, & Johan Koskinen

Objectives: The project aims to: (1) investigate structural and functional changes in criminal networks across time to determine ways in which criminal networks form and evolve.  To meet this aim, the project will answer the following research questions: (1) What social structural changes occur in criminal networks across time?; (2) How are these structural changes related to roles/tasks performed by network members?; and (3) What social processes (e.g., reciprocity, transitivity) can account for the growth and change over time in criminal networks?

Methods: The relational data on the network was divided into four time periods each of two years duration.  Actors were allocated to specific roles.  We applied a Stochastic Actor-Oriented Model (SAOM) to explain the dynamics of an Australian drug trafficking network across time.  Using RSiena we estimated three models: (1) a model with relational data only; (2) relational data plus endogenous effects including: degree effect, popularity/activity effect, transitive triad effects and an indirect relations effect. 


Illicit drug trafficking: The structure of illicit networks and implications for resilience and vulnerability (ARC Discovery Project)

David Bright, Catherine Greenhill, Alison Ritter, Carlo Morselli

The overall aim is to examine the structure of illicit networks (drug trafficking networks) to determine areas of vulnerability and resilience. The project aims to improve existing knowledge and empirical accounts of criminal networks by employing an innovative multi-level analytic approach which incorporates structural factors, node positing effects, links between nodes, and node-level or individual factors. The results will shed light on poorly understood phenomena using intersecting methodologies from the social sciences and mathematics, and have the potential to lead to enhanced law enforcement capacities for detecting and dismantling these networks.