期刊
SOCIAL NETWORKS
卷 70, 期 -, 页码 325-333出版社
ELSEVIER
DOI: 10.1016/j.socnet.2022.02.013
关键词
Triadic closure; Co-offending networks; Null models; Bipartite networks
资金
- Colfuturo (Colombia)
- University College London, United Kingdom through the UCL-Overseas Research Scholarship
This study measures triadic closure in co-offending networks and assesses its statistical significance using null models. The results show that accomplices become sources of information about potential associates. This supports the idea of preventing crime by targeting offenders' trustworthiness and disrupting information flows.
We measured triadic closure in co-offending networks - i.e., the tendency of two individuals to co-offend if they share an accomplice - using a method that addresses the risk of overestimating clustering coefficients when using one-mode projections. We also assess the statistical significance of clustering coefficients using null models. The data relates to adult offenders (N = 274,689) connected to criminal investigations (N = 286,591) in Colombia. The observed coefficients range between 0.05 and 0.53 and are statistically significant, indicating that accomplices become sources of information about potential associates. They support the idea of preventing crime by targeting offenders' trustworthiness and disrupting information flows.
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