Diversity Analysis Exposes Unexpected Key Roles in Multiplex Crime Networks

  • A. S. O. ToledoEmail author
  • Laura C. Carpi
  • A. P. F. Atman
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)


The study of criminal networks seeks new approaches and answers to meet the growing demand of society. In this paper, we present an innovative analysis of crime occurrences in the State of Minas Gerais, Brazil, collected from a Public Security Intelligence database, from the point of view of statistical physics and complex networks. We built the network of these individuals by considering the hierarchy, type of crime and relationships reported within criminal organizations. When modeling the crime database as a complex network, it was possible to identify criminal groups of individuals, and better understand the structure of criminal organizations. We apply multiplex and node diversity analysis to map the criminal structure in layers according to the type of crime. Surprisingly, some key elements pointed out by this analysis had not yet been identified previously, as major actors. This work represents a significant improvement in the methodology and data mining of the criminal database of the state of Minas Gerais and can be applied to any similar database.


Crime network Diversity Multiplex network Computational modeling 


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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  • A. S. O. Toledo
    • 1
    • 2
    Email author
  • Laura C. Carpi
    • 1
  • A. P. F. Atman
    • 1
    • 3
  1. 1.Programa de Pós-Graduação em Modelagem Matemática e ComputacionalCentro Federal de Educação Tecnológica de Minas GeraisBelo HorizonteBrazil
  2. 2.Instituto Brasileiro de Segurança PúblicaSao PauloBrazil
  3. 3.Instituto Nacional de Ciência e Tecnologia de Sistemas ComplexosRio de JaneiroBrazil

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