• Mohammad A. Tayebi
  • Uwe Glässer
Part of the Lecture Notes in Social Networks book series (LNSN)


Crime is a purposive deviant behavior that is an integrated result of different social, economical, and environmental factors (Boba, Crime analysis and crime mapping. Sage, Thousand Oaks, 2013). Crime imposes a substantial cost on society at individual, community, and national levels (McCollister et al, Drug Alcohol Depend 108(1):98–109, 2010). Criminality worldwide makes trillions of dollars yearly, turning crime into one of the world’s “top 20 economies” (, 2012). Based on the most recent report (Easton et al,, 2014), the total cost of crime in Canada during 2012 is estimated as $81.5 billion, approximately 5.7 % of national income. Given such whopping costs, crime reduction and prevention strategies have become a top priority for law enforcement agencies.


Organize Crime Activity Space Social Network Analysis Criminal Group Organize Crime Group 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    R. Boba, Crime Analysis and Crime Mapping (Sage, Thousand Oaks, 2013)Google Scholar
  2. 2.
    P.J. Brantingham, P.L. Brantingham, Environmental Criminology (Sage, Newbury Park, 1981)Google Scholar
  3. 3.
    P.L. Brantingham, M. Ester, R. Frank, U. Glässer, M.A. Tayebi, Co-offending network mining, in Counterterrorism and Open Source Intelligence, ed. by U.K. Wiil (Springer, Vienna, 2011), pp. 73–102CrossRefGoogle Scholar
  4. 4.
    M. Carlo, Inside Criminal Networks (Springer, New York, 2009)Google Scholar
  5. 5.
    Crime one of world’s ‘top 20 economies’ UN says (2012). Retrieved from
  6. 6.
    S. Easton, H. Furness, P. Brantingham, The cost of crime in canada (2014). Retrieved from
  7. 7.
    U. Glässer, M.A. Taybei, P.L. Brantingham, P.J. Brantingham, Estimating possible criminal organizations from co-offending data. Public Safety Canada (2012)Google Scholar
  8. 8.
    K.E. McCollister, M.T. French, H. Fang, The cost of crime to society: new crime-specific estimates for policy and program evaluation. Drug Alcohol Depend. 108 (1), 98–109 (2010)CrossRefGoogle Scholar
  9. 9.
    J.M. McGloin, A.R. Piquero, On the relationship between co-offending network redundancy and offending versatility. J. Res. Crime Delinq. 47 (1), 63–90 (2009)CrossRefGoogle Scholar
  10. 10.
    J.M. McGloin, C.J. Sullivan, A.R. Piquero, S. Bacon, Investigating the stability of co-offending and co-offenders among a sample of youthful offenders. Criminology 46 (1), 155–188 (2008)CrossRefGoogle Scholar
  11. 11.
    A.J. Reiss Jr., Co-offending and criminal careers. Crime Justice 10, 117–170 (1988)CrossRefGoogle Scholar
  12. 12.
    D.K. Rossmo, Geographic Profiling (CRC Press, Boca Raton, 2000)Google Scholar
  13. 13.
    E.H. Sutherland, Principles of Criminology (J. B. Lippincott & Co., Chicago, 1947)Google Scholar
  14. 14.
    M.A. Tayebi, U. Glässer, Organized crime structures in co-offending networks, in The 9th International Conference on Dependable, Autonomic and Secure Computing (DASC 2011) (2011), pp. 846–853Google Scholar
  15. 15.
    M.A. Tayebi, U. Glässer, Crime group evolution in large co-offending networks, in Proceedings of the 4th Annual Illicit Networks Workshop (2012)Google Scholar
  16. 16.
    M.A. Tayebi, U. Glässer, Investigating organized crime groups: a social network analysis perspective, in Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM’12) (2012), pp. 565–572Google Scholar
  17. 17.
    M.A. Tayebi, L. Bakker, U. Glässer, V. Dabbaghian, Locating central actors in co-offending networks, in Proceedings of the 2011 International Conference on Advances in Social Networks Analysis and Mining (ASONAM’11) (2011), pp. 171–179Google Scholar
  18. 18.
    M.A. Tayebi, U. Glässer, P.L. Brantingham, Organized crime detection in co-offending networks, in Proceedings of the 3rd Annual Illicit Networks Workshop (2011)Google Scholar
  19. 19.
    M.A. Tayebi, M. Jamali, M. Ester, U. Glässer, R. Frank, CrimeWalker: a recommendation model for suspect investigation, in Proceedings of the 5th ACM Conference on Recommender Systems (RecSys’11) (2011), pp. 173–180Google Scholar
  20. 20.
    M.A. Tayebi, R. Frank, U. Glässer, Understanding the link between social and spatial distance in the crime world, in Proceedings of the 20nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS’12) (2012), pp. 550–553Google Scholar
  21. 21.
    M.A. Tayebi, M. Ester, U. Glässer, P.L. Brantingham, CrimeTracer: activity space based crime location prediction, in Proceedings of the 2014 International Conference on Advances in Social Networks Analysis and Mining (ASONAM’14) (2014), pp. 472–480Google Scholar
  22. 22.
    M.A. Tayebi, M. Ester, U. Glässer, P.L. Brantingham, Spatially embedded co-offence prediction using supervised learning, in Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’14) (2014), pp. 1789–1798Google Scholar
  23. 23.
    M.A. Tayebi, U. Glässer, P.L. Brantingham, Learning where to inspect: location learning for crime prediction, in Proceedings of the 2015 International Conference on Intelligence and Security Informatics (ISI’15) (2015), pp. 25–30Google Scholar
  24. 24.
    M.A. Tayebi, U. Glässer, M. Ester, P.L. Brantingham, Personalized crime location prediction. Eur. J. Appl. Math. 27, 422–450 (2016)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Mohammad A. Tayebi
    • 1
  • Uwe Glässer
    • 1
  1. 1.Computing ScienceSimon Fraser UniversityBritish ColumbiaCanada

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