Social Network Analysis in Predictive Policing

Concepts, Models and Methods

Nonfiction, Computers, Database Management, Social & Cultural Studies, Social Science, Crimes & Criminals, Criminology, General Computing
Cover of the book Social Network Analysis in Predictive Policing by Mohammad A. Tayebi, Uwe Glässer, Springer International Publishing
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Author: Mohammad A. Tayebi, Uwe Glässer ISBN: 9783319414928
Publisher: Springer International Publishing Publication: October 11, 2016
Imprint: Springer Language: English
Author: Mohammad A. Tayebi, Uwe Glässer
ISBN: 9783319414928
Publisher: Springer International Publishing
Publication: October 11, 2016
Imprint: Springer
Language: English

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.

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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.

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