Skip to main content

Dynamic Simulation of Community Crime and Crime-Reporting Behavior

  • Conference paper
Social Computing, Behavioral-Cultural Modeling and Prediction (SBP 2011)

Abstract

An agent-based model was developed to explore the effectiveness of possible interventions to reduce neighborhood crime and violence. Both offenders and non-offenders (or citizens) were modeled as agents living in neighborhoods, with a set of rules controlling changes in behavior based on individual experience. Offenders may become more or less inclined to actively commit criminal offenses, depending on the behavior of the neighborhood residents and other nearby offenders, and on their arrest experience. In turn, citizens may become more or less inclined to report crimes, based on the observed prevalence of criminal activity within their neighborhood. This paper describes the basic design and dynamics of the model, and how such models might be used to investigate practical crime intervention programs.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Center for Disease Control and Prevention, National Center for Injury Prevention and Control. Web-based Injury Statistics Query and Reporting System (WISQARS), www.cdc.gov/injury/wisqars/ (accessed 2010 June 14)

  2. Center for Disease Control and Prevention, National Center for Injury Prevention and Control. Web-based Injury Statistics Query and Reporting System (WISQARS), Youth Violence Data Sheet, www.cdc.gov/violenceprevention/pdf/YV-DataSheet-a.pdf (accessed 2010 June 14)

  3. Kellerman, A.L., Fuqua-Whitley, D.S., Rivara, F.P., Mercy, J.: Preventing Youth Violence: What Works? Annual Review of Public Health 19, 271–292 (1998)

    Article  Google Scholar 

  4. National Youth Violence Prevention Resource Center (NYVPRC), www.safeyouth.gov/Resources/Prevention/Pages/PreventionStrategies.aspx

  5. Anderson, E.: Code of the Street: Decency, Violence and the Moral Life of the Inner City. Norton, New York (1999)

    Google Scholar 

  6. Earls, F.J.: Violence and Todays Youth: Critical Health Issues for Children and Youth. Future of Children 4(3), 4–23 (1994)

    Article  Google Scholar 

  7. Sampson, R.J., Raudenbush, S.W., Earls, F.: Neighborhoods and Violent Crime: A Multilevel Study of Collective Efficacy. Science 277, 918–924 (1997)

    Article  Google Scholar 

  8. Taylor, R.B., Gottfredson, S.D., Brower, S.: Understanding Block Crime and Fear. Journal of Research in Crime and Delinquency 21, 303–331 (1984)

    Article  Google Scholar 

  9. Wilson, J.M., Chermak, S., McGarrell, E.F.: Community-Based Violence Prevention: An Assessment of Pittsburgh’s One Vision One Life Program. RAND Corp., Santa Monica (2010)

    Google Scholar 

  10. Bibb, M.: Gang Related Services of Mobilization for Youth. In: Klein, M.W. (ed.) Juvenile Gangs in Context: Theory, Research, and Action. Prentice-Hall, Englewood Cliffs (1967)

    Google Scholar 

  11. Bennett, T.H., Holloway, K.R., Farrington, D.P.: Effectiveness of Neighbourhood Watch in Reducing Crime. National Council on Crime Prevention, Stockholm (2008)

    Google Scholar 

  12. Reiss, A.J., Roth, J.A.: Measuring Violent Crime and Their Consequences. In: Understanding and Preventing Violence. National Research Council, pp. 404–429. National Academy Press, Washington DC (1993)

    Google Scholar 

  13. Epstein, J.: Modeling Civil Violence: An Agent-based Computational Approach. Proceedings of the National Academy of Sciences of the United States of America 99 (suppl. 3), 7243–7250 (2002)

    Article  Google Scholar 

  14. Groff, E.: Characterizing the Spatio-temporal Aspects of Routine Activities and the Geographical Distribution of Street Robbery. In: Liu, L., Eck, J. (eds.) Artificial Crime Analysis Systems, pp. 226–251. IGI Global, Hershey (2008)

    Chapter  Google Scholar 

  15. Furtado, V., Melo, A., Coelho, A.L.V., Menezes, R., Belchio, M.: Simulating Crime against Properties using Swarm Intelligence and Social Networks. In: Liu, L., Eck, J. (eds.) Artificial Crime Analysis Systems, pp. 300–318. IGI Global, Hershey (2008)

    Chapter  Google Scholar 

  16. Dray, A., Mazerolle, L., Perez, P., Ritter, A.: Drug Law Enforcement in an Agent-Based Model: Simulating the Disruption. In: Liu, L., Eck, J. (eds.) Artificial Crime Analysis Systems, pp. 352–371. IGI Global, Hershey (2008)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Yonas, M.A. et al. (2011). Dynamic Simulation of Community Crime and Crime-Reporting Behavior. In: Salerno, J., Yang, S.J., Nau, D., Chai, SK. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2011. Lecture Notes in Computer Science, vol 6589. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19656-0_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-19656-0_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19655-3

  • Online ISBN: 978-3-642-19656-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics