Overlapping crime: Stability and specialization of co-offending relationships

Dyadic analyses of relationships between criminals have mostly ignored the multiplex nature of criminal ties. This study attempts to provide a more complete assessment of co-offending networks by incorporating the different types of crime that relate individuals with each other. Drawing on a large dataset of arrests in Quebec between 2003 and 2009, we focus on co-offending stability and specialization and illustrate how co-offending networks based on different types of criminal activities overlap. We portray a pattern of co-offending, which extends debate of criminal specialization/versatility to the dyadic level. Our study illustrates the ways in which the frequency and spectrum of crime include a relational component. More generally, the article emphasizes the need to consider the semantics of network ties, and further, the association between different types of networks, which ultimately offers a reassessment of social structure.     

Criminal collaboration and risk: The drivers of Al Qaeda’s network structure before and after 9/11

A group’s resilience is often linked to its network structure. While decentralized network properties have been associated with resilience at the group-level, little is known about the individual-level factors that lead groups to adopt these structures. Criminal groups, consistently faced with unexpected external disruptions, provide an opportunity to examine individual decisions to collaborate across periods of increased risk. Using data on 118 terrorist offenders across six attacks we test whether individual decisions to collaborate are influenced by variation in law enforcement activity. Results from exponential random graph models demonstrate that many of the processes that drive collaboration between offenders differ when faced with greater risk. Connectivity was maximized in periods of decreased enforcement activity, with offenders more likely to collaborate in dense, local triads. Following an increase in interdictions, triad closure had no impact on co-offending.     

Neighborhood co-offending networks,structural embeddedness,and violent crime in Chicago

Neighborhood disparities in crime are a persistent feature of U.S. cities. Scholars have documented that both local structural conditions and characteristics of spatially proximate communities influence neighborhood crime rates. Previous studies on neighborhood inequality in crime, however, are limited by their focus on identifying average spillover effects between pairs of spatially contiguous neighborhoods, and have neglected to consider how the broader social organization of the city influences local outcomes. This study examines the role of neighborhood-level criminal networks in shaping the distribution of crime throughout cities. Employing arrest records and survey data from the Project on Human Development in Chicago Neighborhoods, we construct a neighborhood-level co-offending network for Chicago for 2001. We use this network to investigate how a focal neighborhood’s homicide rate is influenced by its structural embeddedness within the larger inter-neighborhood co-offending network. Results indicate that a neighborhood’s embeddedness increases the local homicide rate, even after controlling for the neighborhood’s internal propensity toward crime and accounting for unobserved spatial processes.     

Youth co-offending networks: An investigation of social and spatial effects

This research tests the relative contribution of social distance and spatial distance to the presence of ties between neighborhoods based on youth co-offending. Using official court data from a large U.S. metropolitan area, a set of dyad independence and exponential random graph models are estimated in order to investigate the characteristics of neighborhoods that foster co-offending. Results reveal significant effects of both social and spatial distance. Social distance contributes to network structure net of spatial proximity, though spatial factors better explain the overall network structure. These results have methodological implications for the analysis of spatial effects and criminal behavior.     

Communities in criminal networks: A case study

Criminal organizations tend to be clustered to reduce risks of detection and information leaks. Yet, the literature exploring the relevance of subgroups for their internal structure is so far very limited. The paper applies methods of community analysis to explore the structure of a criminal network representing the individuals’ co-participation in meetings. It draws from a case study on a large law enforcement operation (“Operazione Infinito”) tackling the ‘Ndrangheta, a mafia organization from Calabria, a southern Italian region. The results show that the network is indeed clustered and that communities are associated, in a non-trivial way, with the internal organization of the ‘Ndrangheta into different “locali” (similar to mafia families). Furthermore, the results of community analysis can improve the prediction of the “locale” membership of the criminals (up to two thirds of any random sample of nodes) and the leadership roles (above 90% precision in classifying nodes as either bosses or non-bosses). The implications of these findings on the interpretation of the structure and functioning of the criminal network are discussed.     

Network closure and integration in the mid-20th century American mafia

Criminal networks are thought to be biased toward decentralization and security rather than integration and efficiency. This article examines this tradeoff in a large-scale national criminal network spanning more than 700 members of 24 distinct American mafia families operating in the mid-20th century. Producing a novel network image of the American mafia as a set of highly differentiated yet intertwined islands of criminal activity, the analysis uncovers a small-world structure that allowed both for strong intragroup closure and high intergroup connectivity. This balance reflected a division of network labor in which integrative bridging connections were disproportionately concentrated among a small number of criminals. Furthermore, the criminals who held such bridging ties tended to be either low- or high-status—but not of middling status—within their respective organizations.     

Statistical estimation of co-offending youth networks

The relevance and potential of network approaches in criminology are well known. Friendship networks and antisocial influences conveyed by them have an impact on the spread of criminal behavior. However, there are relatively few studies reporting on the use of statistical network models in the analysis of delinquency data. The purpose here is to discuss statistical network models that might be appropriate for estimating joint participation in crime and the structure of co-offending youth networks. The discussion is largely based on problems encountered in some recent exploratory studies of juvenile crime in Stockholm with register data from the police on suspected offenders. A bipartite graph model of such data is built from assumptions about crime reporting and offender detection for a specific type of crimes committed in a certain area during a certain time period. It is shown how the model parameters and the numbers of crimes of different sizes, the numbers of offenders of different activities, and the total number of offences can be estimated from data about reported crimes and police identified offenders. The illustrations also show the need for further statistical development.     

To make and keep friends: The role of health status in adolescent network tie formation and persistence

Health status may shape network structure through network dynamics (tie formation and persistence) and direction (sent and received ties), net of typical network processes. We apply Separable Temporal Exponential Random Graph Models (STERGMs) to National Longitudinal Study of Adolescent to Adult Health survey data (n = 1779) to differentiate how health status shapes network sent and received tie formation and persistence. Results indicate that networks are shaped by withdrawal of adolescents experiencing poor health, highlighting the importance of separating distinct and directed processes of friendship formation and persistence when considering how health relates to adolescent social life.     

Social network analysis of Australian poly-drug trafficking networks: How do drug traffickers manage multiple illicit drugs?

International agencies report rising numbers of drug traffickers who deal in multiple drugs (poly-drug traffickers). This paper explores how product diversification is managed in three Australian poly-drug trafficking syndicates. Networks were constructed using judges’ sentencing comments and social network analysis applied to examine the degree of specialisation, resource flows and management structure (if any). Each syndicate had a clear management structure, but employed a different approach to diversifying including in-house production of multiple products (Syndicate 1) and outsourcing to other syndicates (Syndicate 3). This suggests traffickers will have multiple avenues for product diversification. This may create challenges for their policing.     

Ethical implications of network data in business and management settings

Reflecting on the compilation and analysis of a range of network datasets drawn from our own work and some prominent examples, we consider the ethical challenges in dealing with network data in business and management settings. We argue that the managerial processes that characterize such settings introduce particular ethical sensitivities in the stages of commissioning and research design, and when collecting, analyzing and reporting network data. These sensitivities arise from the imperatives of business, motivations for commissioning network analyses and the legal authority that managers have over employees. We argue that ethical considerations are much more pervasive in business and management network research than in many other fields.In this contribution, we present a range of ethical challenges in network research in business and management settings that arise at several stages of the research process. For each issue identified, we describe the ethical problem and propose mitigation remedies. From this reflection, we suggest guidelines for other researchers to consider when designing research projects in this application area.     

Local mobilisations and the formation of environmental networks in a democratizing Tunisia

ABSTRACT

This study examines the environmental protests that occurred in Tunisia after the 2011 uprisings. It analyses the factors underpinning the rise of the environmental networks during the period of transition (2011–2014). It details the mobilising strategies that were crucial for the networks’ growth or survival during this period of institutional instability. The study shows how networks leaders were able to bring together social and political actors from different backgrounds and ideological orientations. It is argued that the ability of networks to develop new distinctive collective identities was crucial for network sustainability. Those networks and actors who did not develop new clearly defined environmental identities and continued to rely importantly on pre-existing (authoritarian) structures and practices were more negatively impacted by ideological cleavages and political calculations. Empirically, the contribution builds on interviews and observations, as well as documents collected from Tunisian municipalities between 2013 and 2015. Conceptually, the research proposes a bottom-up perspective that highlights the interplay between micro- and macro-dynamics and strategies during a political transition. The analysis details the actors’ capacity to build alliances via interpersonal relations at the micro level, and their strategies to engage with institutional actors and processes.     

Network knowledge and the use of power

Complementing recent work on the effects of power on network perceptions, we offer a theory specifying how knowledge of network structures and exchange processes differentially affect the use of power by advantaged and disadvantaged positions. We argue that under certain conditions, network knowledge is beneficial to occupants of low-power positions, but not to occupants of high-power positions. Any low-power actor can benefit from having superior information, but if all low-power actors have equally sound knowledge, then all are worse off—a type of social trap. We tested these arguments by manipulating power and the availability of information on network structure and exchange processes in an experimental exchange network setting. The results were supportive.     

Social learning about levels of perinatal and infant mortality in Niakhar,Senegal

How individuals develop perceptions concerning the risk of infant and child mortality has important consequences for fertility and demographic transition theory and for understanding broader processes of social learning. The role of learning through social interaction in shaping demographic phenomena has been the subject of intense research in the last decade. Much previous research however has been hampered by inadequate measures of individuals’ personal networks, the proximal context in which learning takes place. Using pilot data employing an innovative social network design in conjunction with demographic surveillance data from Niakhar, Senegal, this research models perception of change in the level of infant mortality over time as a function of the experience of social network associates with perinatal and infant mortality. Results suggest relatively strong effects of network members’ mortality experience controlling for own experiences of child mortality as well as neighborhood and community levels of infant mortality among other controls.     

Binge Drinking During the First Semester of College: Continuation and Desistance From High School Patterns

Abstract

Students' first semester on campus may set the stage for their alcohol use/misuse throughout college. The authors surveyed 274 randomly sampled first-semester freshmen at a large southwestern university on their past 2 weeks' binge drinking, their high school binge drinking, and psychosocial factors possibly associated with drinking. They conducted separate analyses among high school nonbinge drinkers (testing for predictors of college binge onset vs continued nonbinge drinking) and high school binge drinkers (testing for predictors of continued binge drinking in college vs desistance from drinking). In both analyses, the variables that predicted college binge drinking largely revolved around gregarious socializing (eg, partying, having a social network of individuals who drank relatively heavily). Gender was predictive only among high school nonbinge drinkers; women had a higher probability than did men of adopting binge drinking in college.     

Keep around,drop, or revise? exploring what becomes of difficult ties in personal networks

Previous studies increasingly recognize the presence and impact of difficult individuals within personal networks. However, current research sheds little light on the turnover, retention, and change in quality of such difficult ties. The current study addresses this gap by focusing on two distinct forms of network change. We examine how role relationships, support exchange, relational homophily, and personal characteristics are associated with these processes. Data are drawn from three waves of the University of California Social Network Study (UCNets), a project containing comprehensive longitudinal data on ego networks among two adult cohorts. Findings indicate that over time, 34% of difficult ties re-appear in people’s networks as sources of aggravation; 26% of difficult ties are removed from the network; and 40% can no longer be verified as problematic network members. Most ties no longer deemed difficult are identified as providing one or more supportive functions. Multinomial multilevel models reveal that exchanging support tends to anchor difficult ties in the network. Kinship, meanwhile, plays a large role in whether difficult ties remain or get dropped. Personal characteristics such as gender, income, and relocation also play a role in these processes. Overall, we conclude that the turnover dynamics of difficult ties are similar to other ties, and the apparent change from negative to positive suggests that many ties hold ambivalent properties that make shedding such ties less common than may be expected.     

Network effects on organizational decision-making: Blended social mechanisms and IPO withdrawal

This paper develops a new approach to the study of network effects in organizations and markets by proposing that structural influences on social and economic action result from contingent blends of well-understood social mechanisms. We emphasize the interplay of three different network processes: resource and information transfer, status signaling and certification, and social influence. Different mixes of these mechanisms characterize disparate networks because the obligations imposed by ties and the capacities of partners result in situations where mechanisms amplify or diminish one another. We test hypotheses about mechanism interactions using four years (1997–2000) of data on high-technology IPOs that situate organizational decisions about whether to withdraw an offering in two distinct networks. We find that network mechanisms exert multiple moderating effects on one another and that those effects vary systematically across venture capital syndicate and director interlock networks. These findings help to explain why different networks exert disparate effects, why the effects of some structures change as their larger contexts shift, and why even very successful organizations can sometimes find themselves hamstrung by their connections.     

Cluster analysis of multiplex networks: Defining composite network measures

Social relations are multiplex by nature: actors in a group are tied together by various types of relationships. To understand and explain group processes it is, therefore, important to study multiple social networks simultaneously in a given group. However, with multiplexity the complexity of data also increases. Although some multivariate network methods (e.g. Exponential Random Graph Models, Stochastic Actor-oriented Models) allow to jointly analyze multiple networks, modeling becomes complicated when it focuses on more than a few (2–4) network dimensions. In such cases, dimension reduction methods are called for to obtain a manageable set of variables. Drawing on existing statistical methods and measures, we propose a procedure to reduce the dimensions of multiplex network data measured in multiple groups. We achieve this by clustering the networks using their pairwise similarities, and constructing composite network measures as combinations of the networks in each resulting cluster. The procedure is demonstrated on a dataset of 21 interpersonal network dimensions in 18 Hungarian high-school classrooms. The results indicate that the network items organize into three well-interpretable clusters: positive, negative, and social role attributions. We show that the composite networks defined on these three relationship groups overlap but do not fully coincide with the network measures most often used in adolescent research, such as friendship and dislike.     

In transit: Changing social networks of sub-Saharan African migrants in Turkey and Greece

Research on the role of social networks in human migration has mainly relied on single snapshots in time. This paper focuses on the changes in composition and usage of the transnational networks of migrants and why these changes occur. It is based on ethnography and network analysis with forty sub-Saharan African migrants in two transit contexts: Turkey and Greece, over a 17-month period. Findings show that relationship preferences, resources and communication infrastructures constitute an individual opportunity infrastructure affecting how critical events produce network changes. This process is ongoing through the continued experience of critical events, suggesting that the role of networks fluctuates over time.