The responsiveness of criminal networks to intentional attacks: Disrupting darknet drug trade.

Physical, technological, and social networks are often at risk of intentional attack. Despite the wide-spanning importance of network vulnerability, very little is known about how criminal networks respond to attacks or whether intentional attacks affect criminal activity in the long-run. To assess criminal network responsiveness, we designed an empirically-grounded agent-based simulation using population-level network data on 16,847 illicit drug exchanges between 7,295 users of an active darknet drug market and statistical methods for simulation analysis. We consider three attack strategies: targeted attacks that delete structurally integral vertices, weak link attacks that delete large numbers of weakly connected vertices, and signal attacks that saturate the network with noisy signals. Results reveal that, while targeted attacks are effective when conducted at a large-scale, weak link and signal attacks deter more potential drug transactions and buyers when only a small portion of the network is attacked. We also find that intentional attacks affect network behavior. When networks are attacked, actors grow more cautious about forging ties, connecting less frequently and only to trustworthy alters. Operating in tandem, these two processes undermine long-term network robustness and increase network vulnerability to future attacks.

School suspension and social selection: Labeling, network change, and adolescent, academic achievement.

The growing body of research detailing the pronounced effects of criminal stigma on inequality in the US underscores the importance of labeling theory. In spite of the renewed interest in labeling, little research has evaluated the theoretical mechanisms underlying the theory. Drawing on the labeling perspective, this article evaluates mechanisms underlying the relationship between school punishment and reductions in adolescent academic achievement. It uses recent innovations in longitudinal network analysis to examine the consequences of school punishment as a dynamic interplay of labeling, network selection, and group influence. Results indicate that school punishment facilitates selection into academically underperforming peer networks and that this change in network composition is largely responsible for the association between school punishment and reductions in adolescent academic achievement.