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Predicting Violent Victimization Using Social Network Analysis From Police Data

Fox, Andrew M., Novak, Kenneth J., Van Camp, Tinneke, James, Chadley·2021·Violence and Victims
DOI 10.1891/vv-d-19-00037
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Abstract

Extant research suggests that membership in crime networks explains vulnerability to violent crime victimization. Consequently, identifying deviant social networks and understanding their structure and individual members' role in them could provide insight into victimization risk. Identifying social networks may help tailor crime prevention strategies to mitigate victimization risks and dismantle deviant networks. Social network analysis (SNA) offers a particular means of comprehending and measuring such group-level structures and the roles that individuals play within them. When applied to research on crime and victimization, it could provide a foundation for developing precise, effective prevention, intervention, and suppression strategies. This study uses police data to examine whether individuals most central to a deviant social network are those who are most likely to become victims of violent crime, and which crime network roles are most likely to be associated with vulnerability to violent victimization. SNA of these data indicates that network individuals who are in a position to manage the flow of information in the network (betweenness centrality), regardless of their number of connections (degree centrality), are significantly more likely to be homicide and aggravated assault victims. Implications for police practice are discussed.

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Metadata

Authors
Fox, A. M., Novak, K. J., Van Camp, T., & James, C.
Affiliations
  • State of Washington (US)
  • University of Missouri–Kansas City (US)
  • California State University, Fresno (US)
ORCID
Venue
Violence and Victims
Publisher
Springer Publishing Company
Published
2021-06-01
Volume
36
Issue
3
Pages
436-454
ISSN
  • 0886-6708 (ISSN-L)
  • 1945-7073
DOI
10.1891/vv-d-19-00037
OpenAlex
W3168567143
Cited by
9
References
3
Citations by year
2026: 3 · 2025: 1 · 2024: 2 · 2022: 3
FWCI
1.73
Type
journal article
Language
en
Open access
closed
Locations
  • Violence and Victims (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Crime Patterns and Interventions
  • Social Sciences › Law › Cybercrime and Law Enforcement Studies
  • Social Sciences › Law › Criminal Justice and Penology
Keywords
violent victimization, criminal networks, network centrality, betweenness centrality, degree centrality, murder victims, aggravated assault, victimization risk, crime prevention, police practice
MeSH terms
Social Network Analysis, Homicide, Humans, Police, Crime Victims, Bullying

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CoChat. (2026). Citation check: Predicting Violent Victimization Using Social Network Analysis From Police Data. https://app.cochat.ai/papers/10.1891/vv-d-19-00037
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Fox, A. M., Novak, K. J., Van Camp, T., & James, C. (2021). Predicting Violent Victimization Using Social Network Analysis From Police Data. Violence and Victims. https://doi.org/10.1891/vv-d-19-00037