Using social network analysis to profile organised crime

This policy brief examines the application of Social Network Analysis (SNA) as a 'third-generation' approach to mapping organised criminal networks, contrasting it with traditional link analysis. It argues that while SNA provides an empirical, relationship-based understanding of network structures that can move policing from a reactive to a preventative stance, it requires significant technical expertise and fails to account for broader social and temporal contexts. The document uses a case study of the South African arms deal to demonstrate how SNA can reveal institutional corruption and the importance of specific nodes in a network.

• Social Network Analysis (SNA) differs from traditional mapping by determining social structures empirically based on observed relationships rather than using pre-defined theoretical categories. This allows analysts to avoid simple dichotomies, such as the distinctions between state and non-state or licit and illicit actors.
• The document identifies three generations of network mapping: first-generation 'link analysis' (manual mapping of actors), second-generation software (which automates graphics but still relies on human analysts to detect relationships), and third-generation SNA, which uses arithmetical techniques to quantitise relationships.
• SNA has significant practical limitations, including the need for high technical skill, the time-consuming nature of data entry, and the difficulty of obtaining reliable data on clandestine networks. Furthermore, as the number of actors increases, the resulting sociograms can become visually chaotic and difficult to interpret.
• A fundamental weakness of SNA is its inability to capture the underlying social forces, policy dynamics, or temporal changes of a network. Because it often presents a static 'photograph' of relationships, it may miss the trajectory of a network or the significance of individual contexts.
• A case study of the South African arms deal from the late 1990s demonstrated that corporate relationships were the primary means of facilitating potential corruption. Specifically, 42% of relationships that could facilitate corrupt resource transfer were through institutional means, while direct bribery accounted for only 13%.

APA

Kriegler, A. (2014). Using social network analysis to profile organised crime. Institute for Security Studies. https://issafrica.s3.amazonaws.com/site/uploads/PolBrief57.pdf

Chicago

Kriegler, Anine. Using social network analysis to profile organised crime. Institute for Security Studies, 2014. https://issafrica.s3.amazonaws.com/site/uploads/PolBrief57.pdf.

Wikipedia

{{cite report |last1=Kriegler |first1=Anine |title=Using social network analysis to profile organised crime |publisher=Institute for Security Studies |date=September 2014 |url=https://issafrica.s3.amazonaws.com/site/uploads/PolBrief57.pdf |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{kriegler2014using, author = {Kriegler, Anine}, title = {{Using social network analysis to profile organised crime}}, institution = {Institute for Security Studies}, year = {2014}, month = sep, url = {https://issafrica.s3.amazonaws.com/site/uploads/PolBrief57.pdf}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }