Please use this identifier to cite or link to this item: https://repositorio.esg.br/handle/123456789/1484
metadata.dc.type: Artigo
Title: Multi-criteria decision support to criminology by graph theory and composition of probabilistic preferences
Authors: Gavião, Luiz Octávio
Sant’Anna, Annibal Parracho
Garcia, Pauli Adriano de Almada
Silva, Lucio Camara e
Kostin, Sergio
Lima, Gilson Brito Alves
Keywords: Criminalidade;Redes sociais;Métodos multicritérios;Probabilidade
Issue Date: 2021
Publisher: Brazilian Operations Research Society
Abstract: This study associates graph theory and a multi-criteria decision aid technique, presenting a different process for doing the investigation of criminal networks. In the criminal subject, privacy concerns limit identification. For this reason, the database composed of 110 actors, involving criminals and peripheral characters to the network, was identified by numbers, without names and penalties. The discrimination of critical actors in criminal networks can help law enforcement officers to conduct a more detailed investigation for their disruption. Communication between drug traffickers was transformed into different centrality indices for each actor in their social network. Centralities and actors compose a decision matrix, analyzed by the Composition of Probabilistic Preferences to identify the most relevant actors in the criminal network. Results indicated that the five actors highlighted in the real investigation have a clear distinction of importance in the network, which in a way have been ratified.
URI: https://repositorio.esg.br/handle/123456789/1484
Appears in Collections:Coleção de Artigos (Segurança Pública)

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