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Predicting Corruption Convictions Among Brazilian Representatives Through a Voting-History Based Network

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Corruption Networks

Part of the book series: Understanding Complex Systems ((UCS))

Abstract

While analyzing voting data concerning almost 30 years of legislative work from Brazilian representatives, we have noticed the formation of some sort of “corruption neighborhoods” in the resulting congresspeople network, indicating the possible existence of an (until then) unsuspected relationship between voting history and convictions of corruption or other financial crimes among legislators. This finding has motivated us to develop a predictive model for assessing the chances of a representative for being convicted of corruption or other financial crimes in the future, solely based on how similar are his past votes and the voting record of already convicted congresspeople. In this study, we present the main results obtained from this investigation.

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Acknowledgements

This work is supported in part by the Sao Paulo State Research Foundation (FAPESP) under grant numbers 2015/50122-0, the C4AI under grant number FAPESP/IBM/USP: 2019/07665-4, the Brazilian National Council for Scientific and Technological Development (CNPq) under grant number 303199/2019-9 and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

Author information

Authors and Affiliations

  1. Institute of Mathematics and Computer Science, University of Sao Paulo, Sao Carlos, Brazil

    Tiago Colliri

  2. Faculty of Philosophy, Science, and Letters, University of Sao Paulo, Ribeirao Preto, Brazil

    Liang Zhao

Authors
  1. Tiago Colliri
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  2. Liang Zhao
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Corresponding author

Correspondence to Tiago Colliri .

Editor information

Editors and Affiliations

  1. Department of Economics and International Trade, Universidad Jorge Tadeo Lozano, Bogotá, Colombia

    Oscar M. Granados

  2. Institute of Legal Research, National Autonomous University of Mexico, Mexico City, Mexico

    José R. Nicolás-Carlock

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Colliri, T., Zhao, L. (2021). Predicting Corruption Convictions Among Brazilian Representatives Through a Voting-History Based Network. In: Granados, O.M., Nicolás-Carlock, J.R. (eds) Corruption Networks. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-81484-7_4

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