Though often not mentioned by name, the importance of social networks in explaining criminal behavior, delinquency, and patterns has long been recognized in the study of crime. Theories that explain criminal behavior at the individual level being learned through the impacts of peer influences presume that the transmission of ideas and influences flow among social ties (networks) that link individuals. Cultural theories of crime work in the same way. At the community level, delinquency and criminal behavior are born among members of a community or group that adhere to a particular cultural set of norms or beliefs. The concentration of crime in particular geographic areas results when there are insufficient ties among local residents to affect informal social control in the area. Impacted neighborhoods are often described as socially isolated, lacking social ties to institutions of power that provide the investment and services needed in a healthy community. The history of the formation and activities of street gangs is a clear example of how understanding the ties among individuals, and between groups of these individuals, matter in our understanding these phenomena. Comprehending social ties among gangs and gang members and employment of social network analysis (SNA) have become mainstays of local law enforcement efforts to address the issue of gang violence.
Much of the early criminological work that implicated social networks but did not explicitly acknowledge a network by name, or did not employ SNA on formal network data, did so because collecting such data is difficult at best and sometimes impossible. Though criminology has been a “late adopter” of SNA, the field is making great strides in this area. The National Longitudinal Study of Adolescent to Adult Health (Add Health) research program has provided a rich set of network data to explore issues of peer influence. Researchers are using carefully collected social network data at the individual and organizational level to better understand the ability of communities to self-regulate delinquency and crime in an area. Arrest data and field identification stops are being used to generate large networks in an effort to understand how one’s position in a larger social structure might be related to an actor’s involvement in future offending or victimization.
As the field of criminology continues to adopt a network perspective in the study of crime, it is important to understand the development of social networks within the field. Critically examining the strengths and weaknesses of network data, especially in terms of the process by which data are generated, can lead to better applications of network analysis in the future.
Burning the Haystack to Save the Needle: Dimension Reduction and Privacy in Text and Network Data
