Encyclopedia of Criminology and Criminal Justice

2014 Edition
| Editors: Gerben Bruinsma, David Weisburd

Predictive Policing

  • Craig D. UchidaEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-5690-2_260

Synonyms

Overview

Predictive policing is a new concept for law enforcement in the twenty-first century. While still in its infancy and relatively untested, predictive policing has the potential to change the way in which law enforcement deals with crime and victims. This entry describes predictive policing in terms of its definition and roots, the theories and models that have been developed, applications in law enforcement, and the issues that surround it.

Conceptually, predictive policing involves the use of data and predictive analytics to predict or forecast where and when the next crime or series of crimes will take place. The concept has engendered new terminology in law enforcement. “Predictive analytics,” “data mining,” “nonobvious relationships,” and “predictive spatial analysis” are among the new phrases used by chief executives, policy makers, and researchers to describe aspects of predictive policing. These and other phrases will be...

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Recommended Reading and References

  1. Beck C, McCue C (2009) Predictive policing: what can we learn from Wal-Mart and Amazon about fighting crime in a recession? The Police Chief 76(11)Google Scholar
  2. Berk R (2008) Forecasting methods in crime and justice. Ann Rev Law Soc Sci 4:219–238Google Scholar
  3. Berk R (2009) Statistical learning from a regression perspective. Springer, New YorkGoogle Scholar
  4. Berk R (2011) Asymmetric loss functions for forecasting in criminal justice settings. J Quant Criminol 27:107–123Google Scholar
  5. Bowers K, Johnson S, Pease K (2004) Prospective hot spotting: the future of crime mapping? Brit J Criminol 44(5):641–658Google Scholar
  6. Bratton W, Morgan J, Malinowski S (2009) The need for innovation in policing today. Unpublished manuscript, Harvard Executive Sessions, OctoberGoogle Scholar
  7. Brown DE, Kerchner SH (2000) Spatial-temporal point process models for criminal events. Paper presented at the National Institute of Justice Annual Crime Mapping Conference. Washington, DC. Included in Brown DE (2002) Final report: predictive models for law enforcement. U.S. Department of Justice, Washington, DCGoogle Scholar
  8. Bursik RJ, Grasmick HG (1993) Neighborhoods and crime: the dimensions of effective community control. Lexington Books, LanhamGoogle Scholar
  9. Caplan JM, Kennedy LW, Miller J (2011) Risk terrain modeling: brokering criminological theory and GIS methods for crime forecasting. Justice Quarterly 28(2):360–381Google Scholar
  10. Cohen LE, Felson M (1979) Social change and crime rate trends: a routine activity approach. Am Sociol Rev 44(4):588–605Google Scholar
  11. Fox JS, Huddleston H, Gerber M, Brown DE (2012) Investigating a Bayesian hierarchical framework for feature-space modeling of criminal site-selection problems. Paper presented at the Midwest artificial intelligence and cognitive science conference 2012, Cincinnati, 21–22 Apr 2012. Retrieved 29 May 2012, from http://ceur-ws.org/Vol-841/submission_31.pdf
  12. Goldstein H (1990) Problem-oriented policing. McGraw Hill, New YorkGoogle Scholar
  13. Groff ER, La Vigne NG (2002) Forecasting the future of predictive crime mapping. Crime Prevention Studies 13:29–57Google Scholar
  14. Gorr W, Olligschlaeger A (2002) Crime hot spot forecasting: modeling and comparative evaluation. Final report. U.S. Department of justice. National Institute of Justice. Washington, D.CGoogle Scholar
  15. Harris C (2008) Richmond, Virginia, police department helps lower crime rates with crime prediction software. Retrieved 10 Dec 2009, from http://www.govtech.com/gt/print_article.php?id=575229
  16. Johnson SD, Bowers KJ, Birks DJ, Pease K (2009) Predictive mapping of crime by ProMap: accuracy, units of analysis, and the environmental backcloth. In: Weisburd D, Bernasco W, Gerben JN, Bruinsma J (eds) Putting crime in its place. Springer, New YorkGoogle Scholar
  17. Lewis M (2004) Moneyball: the art of winning an unfair game. W.W. Norton, New YorkGoogle Scholar
  18. Liu H, Brown DE (2000) A new point process transition density model for space-time event prediction. In: Brown DE (ed) (2002). Final report. Predictive models for law enforcement. U.S. Department of justice. Washington, DCGoogle Scholar
  19. McCue C, Parker A (2003) Connecting the dots: data mining and predictive analytics in law enforcement and intelligence analysis. Police Chief 10(10):115–124Google Scholar
  20. Mohler GO, Short MB, Brantingham PJ, Schoenberg FP, Tita GE (2011) Self-exciting point process modeling of crime. J Am Stat Assoc 106(493):100–108Google Scholar
  21. Pearsall B (2009) Predictive policing: the future of law enforcement? NIJ J/Issue No. 266, at 16 (National Institute of Justice)Google Scholar
  22. Radcliffe J (2008) Intelligence-led policing. Willan, LondonGoogle Scholar
  23. Sampson RJ, Groves W (1989) Community structure and crime: testing social disorganization theory. Am J Sociol 94(4):774–802Google Scholar
  24. Sherman LW, Gartin P, Buerger M (1989) Hot spots of predatory crime. Criminology 27(1):27–56Google Scholar
  25. Swatt M (2003) Short-term forecasting of crime for small geographic areas. Unpublished PhD dissertation, University of Nebraska at Omaha, 216 ppGoogle Scholar
  26. Townsley M, Homel R, Chasling J (2003) Infectious burglaries: A test of near repeat hypothesis. Brit J Criminol 43:615–633Google Scholar
  27. Uchida CD (2009) Predictive policing in Los Angeles: planning and development. A white paper published by Justice & Security Strategies, Inc., DecemberGoogle Scholar
  28. Weisburd D (2012) Bringing social context back into the equation. Criminol Public Policy 11(2):317Google Scholar
  29. Williams G (2011) Data mining with rattle and R: the art of excating data for knowledge discovery. Springer, New YorkGoogle Scholar
  30. Wilson R, Smith SC, Markovic JD, LeBeau JL (2009) Geospatial technical working group: meeting report on predictive policing. US Department of Justice, National Institute of JusticeGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Justice and Security Strategies, Inc.Silver SpringUSA