Discourse polarization index: Analysis of top-down and ground-up political discourses in Portugal
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/26231 |
Resumo: | An increasing number of events across the world have been a warning for democracy stability in established democratic countries. Events such as Hungary’s prime minister Viktor Orbán publicity doubting that liberal democracies could remain globally competitive, and the increasing voting share of anti-establishment parties in European member states are consequences of the political polarization phenomenon which endangers our democracy. To understand if we are becoming more polarized, literature has been focusing on measuring political polarization through surveys and voting data, without consistent evidence for any trend. Although the theoretical definition of political polarization has found stability in the literature, the different forms of measuring it have not. The measurement of political polarization needs to be more robust and extended to mass society besides elite society, enabling a comparison between the two, and within the real life and the digital. This dissertation answers this need, measuring political polarization, using text-as-data and computational social science methods, in an effective way independent of manual tasks, language, survey or pooling, polarization’s actors, and environments. It uses an empirical framework applied to parliamentary discourses and Twitter data to create a Discourse Polarization Index (DPI) which enables the assessment of the evolution of political polarization in discourse, considering its state and process. Portugal is used as use case, showing an increase in political polarization from 2015 to 2021, for the elite and the mass society, with similar behaviour between the two groups. A semantic validation is done, and research future steps are given. |
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Discourse polarization index: Analysis of top-down and ground-up political discourses in PortugalPolitical polarizationComputational social scienceNatural language processingMedia sociais -- Social mediaTwitterParlamento -- ParliamentText as dataCiências sociais computacionaisPolarização politicaAnálise de textoAn increasing number of events across the world have been a warning for democracy stability in established democratic countries. Events such as Hungary’s prime minister Viktor Orbán publicity doubting that liberal democracies could remain globally competitive, and the increasing voting share of anti-establishment parties in European member states are consequences of the political polarization phenomenon which endangers our democracy. To understand if we are becoming more polarized, literature has been focusing on measuring political polarization through surveys and voting data, without consistent evidence for any trend. Although the theoretical definition of political polarization has found stability in the literature, the different forms of measuring it have not. The measurement of political polarization needs to be more robust and extended to mass society besides elite society, enabling a comparison between the two, and within the real life and the digital. This dissertation answers this need, measuring political polarization, using text-as-data and computational social science methods, in an effective way independent of manual tasks, language, survey or pooling, polarization’s actors, and environments. It uses an empirical framework applied to parliamentary discourses and Twitter data to create a Discourse Polarization Index (DPI) which enables the assessment of the evolution of political polarization in discourse, considering its state and process. Portugal is used as use case, showing an increase in political polarization from 2015 to 2021, for the elite and the mass society, with similar behaviour between the two groups. A semantic validation is done, and research future steps are given.Diversos acontecimentos mundiais põem em causa a estabilidade democrática nos países democráticos. Destacando-se o comentário do primeiro-ministro húngaro, Viktor Orban, que declarou que as democracias atuais podem não ser competitivas globalmente, justificando a inclinação por uma autocracia, assim como o número crescente de partidos antissistema na Europa ocidental. Ambos os eventos são consequência da polarização política, um fenómeno que tem vindo a pôr em risco as democracias ocidentais. Para perceber a tendência, a literatura tem-se focado na medição quantitativa da polarização política através de questionários e sondagens, sem nenhuma tendência identificada. A quantificação da polarização política precisa de ser mais robusta e estudar também a polarização da massa publica, para além da elite, sendo possível assim a comparação da polarização entre os dois grupos, mas também entre os ambientes em que interagem, na vida real ou no digital. Esta dissertação responde a essa necessidade, medindo a polarização política, usando texto e métodos de ciências sociais computacionais, independente da língua, dos questionários, das sondagens e de tarefas manuais. A dissertação usa um modelo matemático empírico aplicado ao discurso parlamentar e a dados retirados do Twitter para criar o Índice de Polarização no Discurso. Este índice permite avaliar a evolução da polarização no discurso, considerando as suas características de estado e processo. Portugal é usado como caso de estudo, mostrando um aumento da polarização política entre 2015 e 2021, para a elite e massa pública, com comportamentos semelhantes. É efetuada uma validação semântica e são dadas recomendações para próximos passos de investigação.2022-10-10T13:52:40Z2022-09-28T00:00:00Z2022-09-282022-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10071/26231TID:203072057engPereira, Catarina Trindadeinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:45:33Zoai:repositorio.iscte-iul.pt:10071/26231Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:21:47.071562Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Discourse polarization index: Analysis of top-down and ground-up political discourses in Portugal |
title |
Discourse polarization index: Analysis of top-down and ground-up political discourses in Portugal |
spellingShingle |
Discourse polarization index: Analysis of top-down and ground-up political discourses in Portugal Pereira, Catarina Trindade Political polarization Computational social science Natural language processing Media sociais -- Social media Parlamento -- Parliament Text as data Ciências sociais computacionais Polarização politica Análise de texto |
title_short |
Discourse polarization index: Analysis of top-down and ground-up political discourses in Portugal |
title_full |
Discourse polarization index: Analysis of top-down and ground-up political discourses in Portugal |
title_fullStr |
Discourse polarization index: Analysis of top-down and ground-up political discourses in Portugal |
title_full_unstemmed |
Discourse polarization index: Analysis of top-down and ground-up political discourses in Portugal |
title_sort |
Discourse polarization index: Analysis of top-down and ground-up political discourses in Portugal |
author |
Pereira, Catarina Trindade |
author_facet |
Pereira, Catarina Trindade |
author_role |
author |
dc.contributor.author.fl_str_mv |
Pereira, Catarina Trindade |
dc.subject.por.fl_str_mv |
Political polarization Computational social science Natural language processing Media sociais -- Social media Parlamento -- Parliament Text as data Ciências sociais computacionais Polarização politica Análise de texto |
topic |
Political polarization Computational social science Natural language processing Media sociais -- Social media Parlamento -- Parliament Text as data Ciências sociais computacionais Polarização politica Análise de texto |
description |
An increasing number of events across the world have been a warning for democracy stability in established democratic countries. Events such as Hungary’s prime minister Viktor Orbán publicity doubting that liberal democracies could remain globally competitive, and the increasing voting share of anti-establishment parties in European member states are consequences of the political polarization phenomenon which endangers our democracy. To understand if we are becoming more polarized, literature has been focusing on measuring political polarization through surveys and voting data, without consistent evidence for any trend. Although the theoretical definition of political polarization has found stability in the literature, the different forms of measuring it have not. The measurement of political polarization needs to be more robust and extended to mass society besides elite society, enabling a comparison between the two, and within the real life and the digital. This dissertation answers this need, measuring political polarization, using text-as-data and computational social science methods, in an effective way independent of manual tasks, language, survey or pooling, polarization’s actors, and environments. It uses an empirical framework applied to parliamentary discourses and Twitter data to create a Discourse Polarization Index (DPI) which enables the assessment of the evolution of political polarization in discourse, considering its state and process. Portugal is used as use case, showing an increase in political polarization from 2015 to 2021, for the elite and the mass society, with similar behaviour between the two groups. A semantic validation is done, and research future steps are given. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-10-10T13:52:40Z 2022-09-28T00:00:00Z 2022-09-28 2022-09 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/26231 TID:203072057 |
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http://hdl.handle.net/10071/26231 |
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TID:203072057 |
dc.language.iso.fl_str_mv |
eng |
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eng |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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