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Analyzing Dynamic Ideological Communities in Congressional Voting Networks

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Social Informatics (SocInfo 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11185))

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Abstract

We here study the behavior of political party members aiming at identifying how ideological communities are created and evolve over time in diverse (fragmented and non-fragmented) party systems. Using public voting data of both Brazil and the US, we propose a methodology to identify and characterize ideological communities, their member polarization, and how such communities evolve over time, covering a 15-year period. Our results reveal very distinct patterns across the two case studies, in terms of both structural and dynamic properties.

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Notes

  1. 1.

    http://www2.camara.leg.br/transparencia/dados-abertos/dados-abertos-legislativo (In Portuguese).

  2. 2.

    https://projects.propublica.org/api-docs/congress-api/.

  3. 3.

    This threshold was chosen based on Article 55 of the Brazilian Constitution that establishes that a deputy or senator will lose her mandate if she does not attend more than one third of the sessions.

  4. 4.

    Brazilian president Dilma Rousseff was impeached from office and, therefore, Brazil had two Presidents that year.

  5. 5.

    For Brazil: Worker’s Party (PT) and the Brazilian Democratic Movement Party (PMDB). For the US: Democratic (D) and Republican (R).

  6. 6.

    The density of a network is given by the ratio of the total number of existing edges to the maximum possible number of edges in the graph. The clustering coefficient, on the other hand, measures the degree at which the nodes of the graph tend to group together to form triangles, and is defined as the ratio of the number of existing closed triplets to the total number of open and closed triplets. A triplet is three nodes that are connected by either two (open triplet) or three (closed triplet) undirected ties.

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Acknowledgments

This work was partially supported by the FAPEMIG-PRONEX-MASWeb project – Models, Algorithms and Systems for the Web, process number APQ-01400-14, as well as by the National Institute of Science and Technology for the Web (INWEB), CNPq and FAPEMIG.

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Authors and Affiliations

  1. Department of Computer Science, Universidade Federal de Minas Minas Gerais, Belo Horizonte, Brazil

    Carlos Henrique Gomes Ferreira, Breno de Sousa Matos & Jussara M. Almeira

Authors
  1. Carlos Henrique Gomes Ferreira
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  2. Breno de Sousa Matos
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  3. Jussara M. Almeira
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Correspondence to Carlos Henrique Gomes Ferreira .

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Editors and Affiliations

  1. University of Koblenz, Koblenz, Germany

    Steffen Staab

  2. National Research University Higher School of Economics, St. Petersburg, Russia

    Olessia Koltsova

  3. National Research University Higher School of Economics, Moscow, Russia

    Dmitry I. Ignatov

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Gomes Ferreira, C.H., de Sousa Matos, B., Almeira, J.M. (2018). Analyzing Dynamic Ideological Communities in Congressional Voting Networks. In: Staab, S., Koltsova, O., Ignatov, D. (eds) Social Informatics. SocInfo 2018. Lecture Notes in Computer Science(), vol 11185. Springer, Cham. https://doi.org/10.1007/978-3-030-01129-1_16

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  • DOI: https://doi.org/10.1007/978-3-030-01129-1_16

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