NCJ Number
224502
Journal
IALEIA Journal Volume: 18 Issue: 1 Dated: April 2008 Pages: 18-43
Date Published
April 2008
Length
26 pages
Annotation
Using social network analysis (SNA), this article proposes a strategic model for systematically targeting actors in criminal networks.
Abstract
When criminal networks become complex, involving relatively large numbers of actors and connections, SNA may be required in order to identify the central actors in the network. Steve Borgatti has developed a useful SNA-based approach for identifying key players in a social network. Borgatti’s “key-player” approach recognizes a critical distinction relevant to law enforcement. He distinguishes between enforcement and intelligence priorities within criminal networks. Enforcement priorities correspond generally to network actors whose removal will maximize network disruption. The more a network is disrupted by the removal of one or more actors, the greater its degree of fragmentation. Intelligence priorities correspond generally to network actors whose surveillance will provide the greatest amount of information on other network actors, thus leading to greater knowledge of the network. Intelligence efforts, therefore, should focus on network actors with a high degree of connectedness to other actors in the network. The authors of this article adopt Borgatti’s approach to identifying key players in a criminal network, but modify it in order to incorporate the weighting of network actors and their associations. With these modifications, the authors present a more comprehensive SNA-based model for developing enforcement and intelligence priorities for law enforcement. The modification addresses the assumption of Borgatti’s model that all network actors are equally potent and that they are linked to one another with equal strength. The proposed model does not advocate any particular system for attribute or link weights; the methodology is designed to be compatible with any numerical system used by law enforcement that can be appropriately scaled. 6 figures, 3 tables, and 7 references