IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v591y2022ics0378437121009614.html
   My bibliography  Save this article

Electorate involvement disorder: Universal relationship between the amplitude and electorate size in second round of Brazilian Presidential Election

Author

Listed:
  • Cardoso, M.
  • Silva, L.M.C.
  • Neli, R.R.
  • Souza, W.E.

Abstract

The voter’s opinion is not expressed exclusively in the vote for one of the candidates, it may be implicit among abstentions or invalid votes, which are blank and null votes. In this study, we investigated the electorate participation in second rounds of Brazilian presidential elections, by consider the list, per ballot box, of the proportions of the three possible “forms of voter participation” in the election result: abstaining from voting, voting blank or null, or voting for one of the candidates, which called here of the electorate involvement. We used the entropy concept of Statistical Mechanics relating these proportions as a measure of the “disorder” of the electoral involvement. We found a generalized logarithmic model, parameter free, for the entropy amplitude per city as a function of the electorate size, showing that the range of the electorate involvement disorder is maintained over all election years and tends to grow more slowly in the larger electorates.

Suggested Citation

  • Cardoso, M. & Silva, L.M.C. & Neli, R.R. & Souza, W.E., 2022. "Electorate involvement disorder: Universal relationship between the amplitude and electorate size in second round of Brazilian Presidential Election," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    • Handle: RePEc:eee:phsmap:v:591:y:2022:i:c:s0378437121009614
    DOI: 10.1016/j.physa.2021.126778
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437121009614
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2021.126778?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. M. C. González & A. O. Sousa & H. J. Herrmann, 2004. "Opinion Formation On A Deterministic Pseudo-Fractal Network," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 15(01), pages 45-57.
    2. Eszter Bokányi & Zoltán Szállási & Gábor Vattay, 2018. "Universal scaling laws in metro area election results," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-11, February.
    3. Christian Borghesi & Jean-Claude Raynal & Jean-Philippe Bouchaud, 2012. "Election Turnout Statistics in Many Countries: Similarities, Differences, and a Diffusive Field Model for Decision-Making," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-12, May.
    4. Alves, L.G.A. & Ribeiro, H.V. & Lenzi, E.K. & Mendes, R.S., 2014. "Empirical analysis on the connection between power-law distributions and allometries for urban indicators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 409(C), pages 175-182.
    5. C. Borghesi & J.-P. Bouchaud, 2010. "Spatial correlations in vote statistics: a diffusive field model for decision-making," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 75(3), pages 395-404, June.
    6. Hygor Piaget M Melo & Saulo D S Reis & André A Moreira & Hernán A Makse & José S Andrade Jr., 2018. "The price of a vote: Diseconomy in proportional elections," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-13, August.
    7. Araripe, L.E. & Costa Filho, R.N., 2009. "Role of parties in the vote distribution of proportional elections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4167-4170.
    8. Costa Filho, R.N. & Almeida, M.P. & Moreira, J.E. & Andrade, J.S., 2003. "Brazilian elections: voting for a scaling democracy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 322(C), pages 698-700.
    9. Luis E. Araripe & Raimundo N. Costa Filho & Hans J. Herrmann & José S. Andrade, 2006. "Plurality Voting: The Statistical Laws Of Democracy In Brazil," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 17(12), pages 1809-1813.
    10. Alves, Luiz G.A. & Ribeiro, Haroldo V. & Mendes, Renio S., 2013. "Scaling laws in the dynamics of crime growth rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(11), pages 2672-2679.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cardoso, M. & Souza, J.T.G. & Neli, R.R. & Souza, W.E., 2023. "Scaling laws from Brazilian state election results point out that, the candidate’s chance to win increases by investing more campaign efforts in smaller electorates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    2. Deeb, Omar El, 2023. "Entropic spatial auto-correlation of voter uncertainty and voter transitions in parliamentary elections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cardoso, M. & Mendes, R.S. & Souza, J.T.G. & Ribeiro, H.V., 2020. "Gender difference in candidature processes for Brazilian elections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    2. Cardoso, M. & Souza, J.T.G. & Neli, R.R. & Souza, W.E., 2023. "Scaling laws from Brazilian state election results point out that, the candidate’s chance to win increases by investing more campaign efforts in smaller electorates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    3. Volker Hösel & Johannes Müller & Aurelien Tellier, 2019. "Universality of neutral models: decision process in politics," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-8, December.
    4. H Hernández-Saldaña, 2013. "Results on Three Predictions for July 2012 Federal Elections in Mexico Based on Past Regularities," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-8, December.
    5. Hygor Piaget M Melo & Saulo D S Reis & André A Moreira & Hernán A Makse & José S Andrade Jr., 2018. "The price of a vote: Diseconomy in proportional elections," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-13, August.
    6. Hygor P M Melo & Nuno A M Araújo & José S Andrade Jr., 2019. "Fundraising and vote distribution: A non-equilibrium statistical approach," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-9, October.
    7. Braha, Dan & de Aguiar, Marcus A. M., 2018. "Voting contagion: Modeling and analysis of a century of U.S. presidential elections," SocArXiv mzxnr, Center for Open Science.
    8. Alves, Luiz G.A. & Ribeiro, Haroldo V. & Rodrigues, Francisco A., 2018. "Crime prediction through urban metrics and statistical learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 435-443.
    9. Luiz G A Alves & Renio S Mendes & Ervin K Lenzi & Haroldo V Ribeiro, 2015. "Scale-Adjusted Metrics for Predicting the Evolution of Urban Indicators and Quantifying the Performance of Cities," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-17, September.
    10. Galesic, Mirta & Stein, D.L., 2019. "Statistical physics models of belief dynamics: Theory and empirical tests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 275-294.
    11. Aleksejus Kononovicius, 2017. "Empirical Analysis and Agent-Based Modeling of the Lithuanian Parliamentary Elections," Complexity, Hindawi, vol. 2017, pages 1-15, November.
    12. Jean-Philippe Bouchaud, 2012. "Crises and collective socio-economic phenomena: simple models and challenges," Papers 1209.0453, arXiv.org, revised Dec 2012.
    13. Joao Meirelles & Camilo Rodrigues Neto & Fernando Fagundes Ferreira & Fabiano Lemes Ribeiro & Claudia Rebeca Binder, 2018. "Evolution of urban scaling: Evidence from Brazil," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-15, October.
    14. Crokidakis, Nuno & Galam, Serge, 2022. "After 2018 Bolsonaro victory, is a 2022 remake feasible?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    15. Deeb, Omar El, 2023. "Entropic spatial auto-correlation of voter uncertainty and voter transitions in parliamentary elections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
    16. Tiwari, Mukesh & Yang, Xiguang & Sen, Surajit, 2021. "Modeling the nonlinear effects of opinion kinematics in elections: A simple Ising model with random field based study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    17. Maulana, Ardian & Situngkir, Hokky, 2015. "Korelasi Bebas-skala dalam Studi Geo-politik Pemilihan [Scale-free correlation within Geopolitics of Election Studies]," MPRA Paper 66351, University Library of Munich, Germany.
    18. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    19. Bansal, Komal & Mathur, Trilok & Agarwal, Shivi, 2023. "Fractional-order crime propagation model with non-linear transmission rate," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    20. Hoferer, Moritz & Böttcher, Lucas & Herrmann, Hans J. & Gersbach, Hans, 2020. "The impact of technologies in political campaigns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:591:y:2022:i:c:s0378437121009614. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.