A data-driven network approach for characterization of political parties’ ideology dynamics
dc.contributor.author | Faustino, J | |
dc.contributor.author | Barbosa, H | |
dc.contributor.author | Ribeiro, E | |
dc.contributor.author | Menezes, R | |
dc.date.accessioned | 2019-10-30T16:21:20Z | |
dc.date.issued | 2019-07-16 | |
dc.description.abstract | Political ideology is a major social phenomena that plays a crucial role in the formation and dynamics of ideologically-aligned social groups. This alignment gives rise to some of the most powerful social structures in modern democracies, the political parties. Due to the influence and importance of political parties in society, estimating their ideology is an active topic in political science research. However ideology is a very subjective phenomena and existing quantitative methods for ideology estimation are susceptible to a variety estimation issues, specially when applied in multi-partisan systems. In this work, we developed a data-driven network model for political ideology estimation based on partisan relationships established from party-switching politicians. The model is applied to the Brazilian case and yields results consistent with existing literature in the Brazilian political scenario while addressing data scarcity issues in existing methodologies. | en_GB |
dc.description.sponsorship | Science Without Borders program (CAPES, Brazil) | en_GB |
dc.description.sponsorship | National Science Foundation (NSF) | en_GB |
dc.description.sponsorship | Army Research Office | en_GB |
dc.identifier.citation | Vol. 4, article 48 | en_GB |
dc.identifier.doi | 10.1007/s41109-019-0161-0 | |
dc.identifier.grantnumber | 99999.001043/2014-05 | en_GB |
dc.identifier.grantnumber | CNS 09-23050 | en_GB |
dc.identifier.grantnumber | W911NF-17-1-0127-P00001 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/39406 | |
dc.language.iso | en | en_GB |
dc.publisher | SpringerOpen | en_GB |
dc.rights | © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. | en_GB |
dc.subject | Ideology estimation | en_GB |
dc.subject | Political parties | en_GB |
dc.subject | Social networks | en_GB |
dc.subject | Group dynamics | en_GB |
dc.title | A data-driven network approach for characterization of political parties’ ideology dynamics | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2019-10-30T16:21:20Z | |
dc.identifier.issn | 2364-8228 | |
dc.description | This is the final published version. Available from SpringerOpen via the DOI in this record. | en_GB |
dc.description | All datasets used in this work are freely available at http://www.tse.jus.br/eleicoes/estatisticas/(in Portuguese). Intermediary files and code are available upon request to the corresponding author. | en_GB |
dc.identifier.journal | Applied Network Science | en_GB |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2019-06-19 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2019-07-16 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2019-10-30T16:17:32Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2019-10-30T16:21:23Z | |
refterms.panel | B | en_GB |
refterms.depositException | publishedGoldOA |
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