© 2016

Social Network Analysis in Predictive Policing

Concepts, Models and Methods


Part of the Lecture Notes in Social Networks book series (LNSN)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Mohammad A. Tayebi, Uwe Glässer
    Pages 1-6
  3. Mohammad A. Tayebi, Uwe Glässer
    Pages 7-14
  4. Mohammad A. Tayebi, Uwe Glässer
    Pages 15-38
  5. Mohammad A. Tayebi, Uwe Glässer
    Pages 39-62
  6. Mohammad A. Tayebi, Uwe Glässer
    Pages 63-75
  7. Mohammad A. Tayebi, Uwe Glässer
    Pages 77-97
  8. Mohammad A. Tayebi, Uwe Glässer
    Pages 99-126
  9. Mohammad A. Tayebi, Uwe Glässer
    Pages 127-130
  10. Back Matter
    Pages 131-133

About this book


This book focuses on applications of social network analysis in predictive policing. Data science is used to identify potential criminal activity by analyzing the relationships between offenders to fully understand criminal collaboration patterns. Co-offending networks—networks of offenders who have committed crimes together—have long been recognized by law enforcement and intelligence agencies as a major factor in the design of crime prevention and intervention strategies. Despite the importance of co-offending network analysis for public safety, computational methods for analyzing large-scale criminal networks are rather premature. This book extensively and systematically studies co-offending network analysis as effective tool for predictive policing. The formal representation of criminological concepts presented here allow computer scientists to think about algorithmic and computational solutions to problems long discussed in the criminology literature. For each of the studied problems, we start with well-founded concepts and theories in criminology, then propose a computational method and finally provide a thorough experimental evaluation, along with a discussion of the results. In this way, the reader will be able to study the complete process of solving real-world multidisciplinary problems.


criminal network analysis predictive policing computational criminology co-offending network co-offence prediction crime location prediction

Authors and affiliations

  1. 1.Computing ScienceSimon Fraser UniversityBritish ColumbiaCanada
  2. 2.Computing ScienceSimon Fraser UniversityBritish ColumbiaCanada

About the authors

Dr. Uwe Glässer is a Professor of Computing Science and Dean pro tem of the Faculty of Applied Sciences, Simon Fraser University, BC, Canada. His work focuses on applied computer science, spanning three fields: industrial applications of formal methods, software technology for intelligent systems, computational criminology and security informatics. His work focuses on facilitating the human interactions that are critical in interdisciplinary research by providing the technologies and technical support to promote effective interactions.

Dr. Mohammad A. Tayebi is a Postdoc at the School of Computing Science, Simon Fraser University, BC, Canada.  His general research interests are in the areas of data mining and social network analysis with focus on social computing and computational criminology fields.

Bibliographic information

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