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From Criminal Spheres of Familiarity to Crime Networks

  • Conference paper
Complex Networks VI

Part of the book series: Studies in Computational Intelligence ((SCI,volume 597))

Abstract

We have never lived in a safer world. After peaking around 1985, both violent crime (homicide, robbery, assaut and rape) and property crimes (burglary, larceny and vehicle theft) are on a downward trend; from 1993 and 2012 crime activity has dropped by more than 40% (total number of crimes). Despite the good news, crime is still prevalent in most large cities. FBI reports that in 2013 there were about 3,098 crimes per 100,000 habitants in the USA, with 2,730 of them being property crimes and 367 violent. What most people can agree is that one preventable crime is one crime that should not have taken place. The unveiling of the structure of criminal activity can lead to a better understanding of crime as a whole which in turn can help us provide better protection to our citizens. We demonstrate in this paper that crime follows a very intersting spatial community pattern regardless of the type of crime, criminal activity aggregates in communities of well defined sizes. We believe the results of this paper is a first step towards a theory of crime modeling using network science.

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Author information

Authors and Affiliations

  1. BioComplex Laboratory, Department of Computer Sciences, Florida Institute of Technology, Melbourne, Florida, USA

    M. Oliveira & H. Barbosa-Filho

  2. School of Computing, University of Utah, Salt Lake City, Utah, USA

    T. Yehle

  3. College of Arts and Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

    S. White & R. Menezes

Authors
  1. M. Oliveira
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  2. H. Barbosa-Filho
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  3. T. Yehle
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  4. S. White
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  5. R. Menezes
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Corresponding author

Correspondence to M. Oliveira .

Editor information

Editors and Affiliations

  1. Dip. di Ingegneria Elettrica, Elettronica e Informatica, University of Catania, Catania, Italy

    Giuseppe Mangioni

  2. Dept. of Engineering Mathematics, University of Bristol, Clifton, United Kingdom

    Filippo Simini

  3. New York Hall of Science, New York, New York, USA

    Stephen Miles Uzzo

  4. College of Information Sciences and Technology, Pennsylvania State University, University Park, New York, USA

    Dashun Wang

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© 2015 Springer International Publishing Switzerland

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Oliveira, M., Barbosa-Filho, H., Yehle, T., White, S., Menezes, R. (2015). From Criminal Spheres of Familiarity to Crime Networks. In: Mangioni, G., Simini, F., Uzzo, S., Wang, D. (eds) Complex Networks VI. Studies in Computational Intelligence, vol 597. Springer, Cham. https://doi.org/10.1007/978-3-319-16112-9_22

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  • DOI: https://doi.org/10.1007/978-3-319-16112-9_22

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16111-2

  • Online ISBN: 978-3-319-16112-9

  • eBook Packages: EngineeringEngineering (R0)

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