Applied Network Science (Jan 2023)
Examining the importance of existing relationships for co-offending: a temporal network analysis in Bogotá, Colombia (2005–2018)
Abstract
Abstract This study aims to improve our understanding of criminal accomplice selection by studying the evolution of co-offending networks—i.e., networks that connect those who commit crimes together. To this end, we tested four growth mechanisms (popularity, reinforcement, reciprocity, and triadic closure) on three components observed in a network connecting criminal investigations ( $$M = 286$$ M = 286 K) with adult offenders ( $$N = 274$$ N = 274 K) in Bogotá (Colombia) between 2005 and 2018. The first component had 4286 offenders (component ‘A’), the second 227 (‘B’), and the third component 211 (‘C’). The evolution of these components was examined using temporal information in tandem with discrete choice models and simulations to understand the mechanisms that could explain how these components grew. The results show that they evolved differently during the period of interest. Popularity yielded negative statistically significant coefficients for ‘A’, suggesting that having more connections reduced the odds of connecting with incoming offenders in this network. Reciprocity and reinforcement yielded mixed results as we observed negative statistically significant coefficients in ‘C’ and positive statistically significant coefficients in ‘A’. Moreover, triadic closure produced positive, statistically significant coefficients in all the networks. The results suggest that a combination of growth mechanisms might explain how co-offending networks grow, highlighting the importance of considering offenders’ network-related characteristics when studying accomplice selection. Besides adding evidence about triadic closure as a universal property of social networks, this result indicates that further analyses are needed to understand better how accomplices shape criminal careers.
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