Evolution of the political opinion landscape during electoral periods
- Autores
- Mussi Reyero, Tomás; Beiro, Mariano Gastón; Alvarez Hamelin, José Ignacio; Hernández, Laura; Kotzinos, Dimitris
- Año de publicación
- 2021
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- We present a study of the evolution of the political landscape during the 2015 and 2019 presidential elections in Argentina, based on data obtained from the micro-blogging platform Twitter. We build a semantic network based on the hashtags used by all the users following at least one of the main candidates. With this network we can detect the topics that are discussed in the society. At a difference with most studies of opinion on social media, we do not choose the topics a priori, they emerge from the community structure of the semantic network instead. We assign to each user a dynamical topic vector which measures the evolution of her/his opinion in this space and allows us to monitor the similarities and differences among groups of supporters of different candidates. Our results show that the method is able to detect the dynamics of formation of opinion on different topics and, in particular, it can capture the reshaping of the political opinion landscape which has led to the inversion of result between the two rounds of 2015 election.
Fil: Mussi Reyero, Tomás. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina
Fil: Beiro, Mariano Gastón. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long". Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long"; Argentina
Fil: Alvarez Hamelin, José Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long". Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long"; Argentina
Fil: Hernández, Laura. No especifíca;
Fil: Kotzinos, Dimitris. No especifíca; - Materia
-
ELECTIONS
OPINION MODELLING
SOCIAL MEDIA
TWITTER DATA - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/173671
Ver los metadatos del registro completo
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Evolution of the political opinion landscape during electoral periodsMussi Reyero, TomásBeiro, Mariano GastónAlvarez Hamelin, José IgnacioHernández, LauraKotzinos, DimitrisELECTIONSOPINION MODELLINGSOCIAL MEDIATWITTER DATAhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2We present a study of the evolution of the political landscape during the 2015 and 2019 presidential elections in Argentina, based on data obtained from the micro-blogging platform Twitter. We build a semantic network based on the hashtags used by all the users following at least one of the main candidates. With this network we can detect the topics that are discussed in the society. At a difference with most studies of opinion on social media, we do not choose the topics a priori, they emerge from the community structure of the semantic network instead. We assign to each user a dynamical topic vector which measures the evolution of her/his opinion in this space and allows us to monitor the similarities and differences among groups of supporters of different candidates. Our results show that the method is able to detect the dynamics of formation of opinion on different topics and, in particular, it can capture the reshaping of the political opinion landscape which has led to the inversion of result between the two rounds of 2015 election.Fil: Mussi Reyero, Tomás. Universidad de Buenos Aires. Facultad de Ingeniería; ArgentinaFil: Beiro, Mariano Gastón. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long". Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long"; ArgentinaFil: Alvarez Hamelin, José Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long". Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long"; ArgentinaFil: Hernández, Laura. No especifíca;Fil: Kotzinos, Dimitris. No especifíca;Springer2021-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/173671Mussi Reyero, Tomás; Beiro, Mariano Gastón; Alvarez Hamelin, José Ignacio; Hernández, Laura; Kotzinos, Dimitris; Evolution of the political opinion landscape during electoral periods; Springer; EPJ Data Science; 10; 1; 6-2021; 1-152193-1127CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-021-00285-8info:eu-repo/semantics/altIdentifier/doi/10.1140/epjds/s13688-021-00285-8info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:40:51Zoai:ri.conicet.gov.ar:11336/173671instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:40:51.922CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Evolution of the political opinion landscape during electoral periods |
title |
Evolution of the political opinion landscape during electoral periods |
spellingShingle |
Evolution of the political opinion landscape during electoral periods Mussi Reyero, Tomás ELECTIONS OPINION MODELLING SOCIAL MEDIA TWITTER DATA |
title_short |
Evolution of the political opinion landscape during electoral periods |
title_full |
Evolution of the political opinion landscape during electoral periods |
title_fullStr |
Evolution of the political opinion landscape during electoral periods |
title_full_unstemmed |
Evolution of the political opinion landscape during electoral periods |
title_sort |
Evolution of the political opinion landscape during electoral periods |
dc.creator.none.fl_str_mv |
Mussi Reyero, Tomás Beiro, Mariano Gastón Alvarez Hamelin, José Ignacio Hernández, Laura Kotzinos, Dimitris |
author |
Mussi Reyero, Tomás |
author_facet |
Mussi Reyero, Tomás Beiro, Mariano Gastón Alvarez Hamelin, José Ignacio Hernández, Laura Kotzinos, Dimitris |
author_role |
author |
author2 |
Beiro, Mariano Gastón Alvarez Hamelin, José Ignacio Hernández, Laura Kotzinos, Dimitris |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
ELECTIONS OPINION MODELLING SOCIAL MEDIA TWITTER DATA |
topic |
ELECTIONS OPINION MODELLING SOCIAL MEDIA TWITTER DATA |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/2.2 https://purl.org/becyt/ford/2 |
dc.description.none.fl_txt_mv |
We present a study of the evolution of the political landscape during the 2015 and 2019 presidential elections in Argentina, based on data obtained from the micro-blogging platform Twitter. We build a semantic network based on the hashtags used by all the users following at least one of the main candidates. With this network we can detect the topics that are discussed in the society. At a difference with most studies of opinion on social media, we do not choose the topics a priori, they emerge from the community structure of the semantic network instead. We assign to each user a dynamical topic vector which measures the evolution of her/his opinion in this space and allows us to monitor the similarities and differences among groups of supporters of different candidates. Our results show that the method is able to detect the dynamics of formation of opinion on different topics and, in particular, it can capture the reshaping of the political opinion landscape which has led to the inversion of result between the two rounds of 2015 election. Fil: Mussi Reyero, Tomás. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina Fil: Beiro, Mariano Gastón. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long". Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long"; Argentina Fil: Alvarez Hamelin, José Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long". Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long"; Argentina Fil: Hernández, Laura. No especifíca; Fil: Kotzinos, Dimitris. No especifíca; |
description |
We present a study of the evolution of the political landscape during the 2015 and 2019 presidential elections in Argentina, based on data obtained from the micro-blogging platform Twitter. We build a semantic network based on the hashtags used by all the users following at least one of the main candidates. With this network we can detect the topics that are discussed in the society. At a difference with most studies of opinion on social media, we do not choose the topics a priori, they emerge from the community structure of the semantic network instead. We assign to each user a dynamical topic vector which measures the evolution of her/his opinion in this space and allows us to monitor the similarities and differences among groups of supporters of different candidates. Our results show that the method is able to detect the dynamics of formation of opinion on different topics and, in particular, it can capture the reshaping of the political opinion landscape which has led to the inversion of result between the two rounds of 2015 election. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/173671 Mussi Reyero, Tomás; Beiro, Mariano Gastón; Alvarez Hamelin, José Ignacio; Hernández, Laura; Kotzinos, Dimitris; Evolution of the political opinion landscape during electoral periods; Springer; EPJ Data Science; 10; 1; 6-2021; 1-15 2193-1127 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/173671 |
identifier_str_mv |
Mussi Reyero, Tomás; Beiro, Mariano Gastón; Alvarez Hamelin, José Ignacio; Hernández, Laura; Kotzinos, Dimitris; Evolution of the political opinion landscape during electoral periods; Springer; EPJ Data Science; 10; 1; 6-2021; 1-15 2193-1127 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-021-00285-8 info:eu-repo/semantics/altIdentifier/doi/10.1140/epjds/s13688-021-00285-8 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/2.5/ar/ |
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openAccess |
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https://creativecommons.org/licenses/by/2.5/ar/ |
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application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
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reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
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