Diversity Analysis Exposes Unexpected Key Roles in Multiplex Crime Networks

Abstract

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.