Giulia Berlusconi

Objectives: This paper explores whether and to what extent individuals’ strategic positioning within a criminal network changes over time, and how these changes reflect differential involvement in illicit activities. It incorporates time as a crucial variable to identify key players in criminal networks and assesses the accuracy of the results against the uncertainty around network data collected from criminal justice records. Methods: Network data are from a judicial document for a two-year investigation targeting a drug trafficking and distribution network. We use Katz centrality in its dynamic version to explore changes in relationships and relative importance of network actors. We then use a novel method of introducing new edges to the network using Bernoulli random trials to simulate missing data and assess the extent to which node rankings based on Katz centrality change or remain the same when introducing some level of uncertainty to our observed network. Results: We identify actors who consistently held a central role over the course of the two-year investigation and differentiate them from actors who provided key contributions to the group’s activities, but only for a limited period. We show that compared to centrality measures commonly used in criminal network analysis, dynamic Katz centrality is helpful to differentiate individual contributions even among central nodes and explore individual trajectories over time, even when data are incomplete. Conclusions: This paper demonstrates the value of key player identification using temporal network data and offers an additional analytical tool to both organised crime scholars trying to capture the complex nature of criminal collaboration and law enforcement agencies aiming at identifying appropriate targets and disrupting criminal groups.

This paper investigates the impact of the targeting of key players by law enforcement on the structure, communication strategies, and activities of a drug trafficking network. Data are extracted from judicial court documents. The unique nature of the investigation – which saw a key player being arrested mid-investigation but police monitoring continuing for another year – allows to compare the network before and after targeting. This paper combines a quantitative element where network statistics and exponential random graph models are used to describe and explain structural changes over time, and a qualitative element where the content of wiretapped conversations is analysed. After law enforcement targeting, network members favoured security over efficiency, although criminal collaboration continued after the arrest of the key player. This paper contributes to the growing literature on the efficiency-security trade-off in criminal networks, and discusses policy implications for repressive policies in illegal drug markets.

There is a relative dearth of literature on both the effects of cross-border interdictions and the impact of different types of interventions on international drug trafficking. This study identifies the main trafficking routes for cocaine and heroin, along with comparing the disruptive effects induced by targeted and non-coordinated interventions. It adopts a social network approach to identify the routes along which cocaine and heroin are trafficked, and then simulates the impact of different interdiction strategies on these two trafficking networks. The findings indicate that targeting countries based on their respective positions in the networks, as opposed to on the basis of the quantity of drugs exchanged, is more likely to disrupt drug flows. More specifically, concentrating law enforcement resources on countries with several incoming or outgoing trafficking connections, or those countries that mediate between producer, transit and consumer countries, would appear to be particularly effective in this regard. Interventions focused on specific trafficking routes are also likely to be effective if these routes have high edge betweenness centrality scores. This study contributes to extant understanding on the vulnerability of cocaine and heroin international trafficking networks, and, moreover, demonstrates that empirically-driven strategies are potentially more effective at interdicting international trafficking than non-strategic and non-coordinated interventions.

This study analyses large-scale online data to examine the characteristics of a national commercial sex network of off-street female sex workers and their male clients to identify implications for public health policy and practice. We collected sexual contact information from the largest online community dedicated to reviewing sex workers’ services in the UK. We built the sexual network using reviews reported between January 2014 and December 2017. We then quantified network parameters using social network analysis measures. The network is composed of 6477 vertices with 59% of them concentred in a giant component clustered around London and Milton Keynes. We found minimal disassortative mixing by degree between sex workers and their clients, and that a few clients and sex workers are highly connected whilst the majority only have one or few sexual contacts. Finally, our simulation models suggested that prevention strategies targeting both sex workers and clients with high centrality scores are the most effective in reducing network connectedness and average closeness centrality scores, thus limiting the transmission of STIs.

Illegal enterprise and social embeddedness theories have highlighted the importance of market forces and social factors, respectively, for analyzing organized crime and organized criminal activities. This paper empirically demonstrates the joint explanatory power of these respective theories in the case of the transnational trafficking of cocaine. It does so by conceptualizing transnational cocaine trafficking as a network of relationships among countries; a network whose structure reflects the actions of manifold organized criminal groups. The analysis utilizes exponential random graph models to analyze quantitative data on cocaine trafficking which are ordinarily difficult to capture in empirical research. The analysis presented focuses on a set of 36 European countries. The results yield insights into the nature of the relationship among economic incentives, social ties, geographic features and corruption, and how, in turn, this relationship influences the structure of the transnational cocaine network and the modi operandi of cocaine traffickers.

In the burgeoning criminological literature on security, risk and preventive justice which has followed the 9/11 attacks on the Twin Towers, ‘contagion’ or the deleterious effect of counterterrorist policies on the ordinary criminal law has been the subject of some discussion, mostly in the context of the threat which such ‘exceptional’ policies pose to mainstream procedural values. This article seeks to build on this literature through an examination of the impact of post 9/11 counterterrorism law and policy on the ordinary criminal justice system in France. Given the extent to which counterterrorist law now encroaches on various aspects of French criminal law, the argument is made for greater criminological attention to be paid to the ‘trickle-down’ effect of extraordinary law on the ordinary business of the criminal justice system.

Mafia homicides are usually committed for retaliation, economic profit, or rivalry among groups. The variety of possible reasons suggests the inefficacy of a preventive approach. However, like most violent crimes, mafia homicides concentrate in space due to place-specific social and environmental features. Starting from the existing literature, this study applies the Risk Terrain Modeling approach to forecast the Camorra homicides in Naples, Italy. This approach is based on the identification and evaluation of the underlying risk factors able to affect the risk of a homicide. This information is then used to predict the most likely location of future events. The findings of this study demonstrate that past homicides, drug dealing, confiscated assets, and rivalries among groups make it possible to predict up to 85% of 2012 mafia homicides, identifying 11% of city areas at highest risk. By contrast, variables controlling for the socio-economic conditions of areas are not significantly related to the risk of homicide. Moreover, this study shows that, even in a restricted space, the same risk factors may combine in different ways, giving rise to areas of equal risk but requiring targeted remedies. These results provide an effective basis for short- and long-term targeted policing strategies against organized crime- and gang-related violence. A similar approach may also provide practitioners, policy makers, and local administrators in other countries with significant support in understanding and counteracting also other forms of violent behavior by gangs or organized crime groups.