Social Network Analysis Applied to Criminal Networks: Recent Developments in Dutch Law Enforcement

Abstract

See, stats, and : https : / / www . researchgate . net / publication / 264726951 Lecture Chapter DOI : 10 . 1007 /978-3-319- 04247- 6 CITATIONS 2 READS 771 2 : Paul Dutch 7 SEE Peter Politieacademie 7 SEE All . The . Abstract This article examines the application of social network theory in Dutch law enforcement . Increasing amounts of information about habitual lawbreakers and criminal networks are collected under the paradigm of Intelligence - Led Policing . Combined with data gathered from open sources such as social media , such resources allow criminal analysts trained in social network analysis (SNA) at the Police Academy of The Netherlands to apply advanced network analysis methodology and crime scripting . This in turn helps the police to identify crucial weak spots in illicit arrangements and criminal business processes . A case study of the ' Blackbird ' crime network , involved in the wholesale cultivation of cannabis is presented to illustrate the power of SNA when combined with crime script anal - ysis . Using a mix of quantitative and qualitative analysis , the topology of the 86 - strong Blackbird network is laid out and its substructures and key individuals exposed . In detailing the network ' s social embeddedness , the authors clarify the importance of female actors for the flexibility and efficiency of the network structure and thereby for the continuity of criminal business . Applying SNA is already helping criminal intelligence units of the Dutch police in identifying intelligence gaps and potential informants . Working in symbiosis , analysts and informant handlers develop a better understanding of strategic targeting and access points to relatively unknown criminal communities and – markets . To be delivered in a timely way to be useful in ongoing criminal investigations , SNA products require even faster data processing . Also , when applied to dark networks SNA should be tailored to better take network dynamics into account , in particular regarding the adaptability to network disruption .