Search

In this study we investigate organized crime by studying the degree of criminal organization. We use population-level register data on criminal suspicions between 2011 and 2016 to analyze the territoriality of Swedish street gangs in terms of geographical mobility, their collaboration in crime through their co-offending network's clustering and community structure, and their crime versatility. Although Swedish street gangs exhibit varying degrees of geographical mobility and criminal collaboration, overall, they have limited reach along these dimensions, characterized by low clustering and limited crime specialization. Violence seems to become a necessary tool only when a gang reaches a certain degree of organization. By unbraiding criminal mobility and its association with other organizational elements such as criminal collaboration in different settings, we provide insights into the structure and dynamics of criminal organizations and contribute to a richer understanding and conceptualization of how crime is organized., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

The field of social network analysis has received increasing attention during the past decades and has been used to tackle a variety of research questions, from prevention of sexually transmitted diseases to humanitarian relief operations. In particular, social network analyses are becoming an important component in studies of criminal networks and in criminal intelligence analysis. At the same time, intelligence analyses and assessments have become a vital component of modern approaches in policing, with policy implications for crime prevention, especially in the fight against organized crime. In this study, we have a unique opportunity to examine one specific Swedish street gang with three different datasets. These datasets are the most common information sources in studies of criminal networks: intelligence, surveillance and co-offending data. We use the data sources to build networks, and compare them by computing distance, centrality, and clustering measures. This study shows the complexity factor by which different data sources about the same object of study have a fundamental impact on the results. The same individuals have different importance ranking depending on the dataset and measure. Consequently, the data source plays a vital role in grasping the complexity of the phenomenon under study. Researchers, policy makers, and practitioners should therefore pay greater attention to the biases affecting the sources of the analysis, and be cautious when drawing conclusions based on intelligence assessments and limited network data. This study contributes to strengthening social network analysis as a reliable tool for understanding and analyzing criminality and criminal networks.

Outlaw motorcycle gangs (OMGs) have received increased attention from both law enforcement agencies and the research community. This study investigates the criminal collaboration patterns of two OMGs with a long history of hostilities. We use government data on individuals registered as belonging to Hells Angels MC, Bandidos MC and individuals with multiple OMG memberships, and suspicion data from 2011 to 2016 to build co-offending networks. Our results show that members of multiple OMGs tend to have higher centrality and clustering. These members also have the highest levels of suspicions per capita, and most of the co-offending is related to nexus links involving multiple membership individuals. They can be described as 'criminal nomads', collaborating with individuals from different organisations. Our results suggest that core members tend to engage in white-collar crime to a greater extent than those on the periphery, which tend to engage more in violence and drug crime. [ABSTRACT FROM AUTHOR]

In this study we investigate the application of the Maxson and Klein gang typology on a dataset of seven Swedish street gangs. Individual-level data on 239 gang members were analyzed. While some Swedish criminologists maintain that no street gangs exist in Sweden, this research project provides evidence to the contrary. Findings support the utility of the Maxson and Klein typology. Results show that the “compressed gang” was the most common type of street gang in the dataset. This finding is also in concert with other European gang studies, adding further evidence for the applicability of the gang typology. Findings also suggest a similar pattern of gang development and structure to that of American and European street gangs. [ABSTRACT FROM AUTHOR]