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
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/173671
Acceder
id CONICETDig_0942ddc351c163b7fffb3d2ede5b296a
oai_identifier_str oai:ri.conicet.gov.ar:11336/173671
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling 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 Técnicas2025-10-22T12:13:21Zoai: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:34982025-10-22 12:13:21.814CONICET 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/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846782535125696512
score 12.982451

Publicaciones similares