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Social Simulation and Analysis of the Dynamics of Criminal Hot Spots

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Abstract

Within the field of Criminology, the spatio-temporal dynamics of crime are an important subject of study. In this area, typical questions are how the behaviour of offenders, targets, and guardians can be explained and predicted, as well as the emergence and displacement of criminal hot spots. In this article we present a combination of software tools that can be used as an experimental environment to address such questions. In particular, these tools comprise an agent-based simulation model, a verification tool, and a visualisation tool. The agent-based simulation model specifically focuses on the interplay between hot spots and reputation. Using this environment, a large number of simulation runs have been performed, of which results have been formally analysed. Based on these results, we argue that the presented environment offers a valuable approach to analyse the dynamics of criminal hot spots.

Suggested Citation

  • Tibor Bosse & Charlotte Gerritsen, 2010. "Social Simulation and Analysis of the Dynamics of Criminal Hot Spots," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(2), pages 1-5.
    • Handle: RePEc:jas:jasssj:2009-12-2
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    References listed on IDEAS

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    1. George Tsebelis, 1990. "Penalty has no Impact on Crime:," Rationality and Society, , vol. 2(3), pages 255-286, July.
    2. Paul Davidsson, 2002. "Agent Based Social Simulation: a Computer Science View," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(1), pages 1-7.
    3. Tsebelis, George, 1989. "The Abuse of Probability in Political Analysis: The Robinson Crusoe Fallacy," American Political Science Review, Cambridge University Press, vol. 83(1), pages 77-91, March.
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    1. Davide Secchi & Raffaello Seri, 2017. "Controlling for false negatives in agent-based models: a review of power analysis in organizational research," Computational and Mathematical Organization Theory, Springer, vol. 23(1), pages 94-121, March.
    2. James Hogg & Maria Fonoberova & Igor Mezić & Ryan Mohr, 2019. "Koopman Mode Analysis of agent-based models of logistics processes," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-37, September.
    3. Maria Fonoberova & Vladimir A. Fonoberov & Igor Mezic & Jadranka Mezic & P. Jeffrey Brantingham, 2012. "Nonlinear Dynamics of Crime and Violence in Urban Settings," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(1), pages 1-2.

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