How to measure political polarization in text-as-data? A scoping review of computational social science approaches

Detalhes bibliográficos
Autor(a) principal: Pereira, C. T.
Data de Publicação: 2024
Outros Autores: Da Silva, R., Rosa, C. P. Da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/31198
Resumo: The rise of political polarization within western societies has been portrayed by events such as the United States Capitol riot or the United Kingdom’s exit from the European Union. In this context, we argue that computational social science (CSS) methods offer a scalable and language- independent fashion to measure political polarization, enabling the processing of big data. In this vein, this article offers the first scoping review of the application of CSS methods to analyzing political polarization through text as data. We propose a categorization framework and reflect on the advantages and disadvantages of the different models used in the literature. Additionally, we underline the importance of filling research gaps, such as considering the temporal characteristic of political polarization, using a mathematical approach to analyze the use cases, and avoiding location and platform bias. We also provide recommendations for future research.
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spelling How to measure political polarization in text-as-data? A scoping review of computational social science approachesPolitical polarizationComputational social science (CSS) methodsText analysisDiscourseTwitterThe rise of political polarization within western societies has been portrayed by events such as the United States Capitol riot or the United Kingdom’s exit from the European Union. In this context, we argue that computational social science (CSS) methods offer a scalable and language- independent fashion to measure political polarization, enabling the processing of big data. In this vein, this article offers the first scoping review of the application of CSS methods to analyzing political polarization through text as data. We propose a categorization framework and reflect on the advantages and disadvantages of the different models used in the literature. Additionally, we underline the importance of filling research gaps, such as considering the temporal characteristic of political polarization, using a mathematical approach to analyze the use cases, and avoiding location and platform bias. We also provide recommendations for future research.Taylor and Francis2025-02-12T00:00:00Z2024-01-01T00:00:00Z20242024-02-28T12:19:27Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/31198eng1933-168110.1080/19331681.2024.2318404Pereira, C. T.Da Silva, R.Rosa, C. P. Dainfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-03T01:16:50Zoai:repositorio.iscte-iul.pt:10071/31198Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:12:13.552463Repositório 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 How to measure political polarization in text-as-data? A scoping review of computational social science approaches
title How to measure political polarization in text-as-data? A scoping review of computational social science approaches
spellingShingle How to measure political polarization in text-as-data? A scoping review of computational social science approaches
Pereira, C. T.
Political polarization
Computational social science (CSS) methods
Text analysis
Discourse
Twitter
title_short How to measure political polarization in text-as-data? A scoping review of computational social science approaches
title_full How to measure political polarization in text-as-data? A scoping review of computational social science approaches
title_fullStr How to measure political polarization in text-as-data? A scoping review of computational social science approaches
title_full_unstemmed How to measure political polarization in text-as-data? A scoping review of computational social science approaches
title_sort How to measure political polarization in text-as-data? A scoping review of computational social science approaches
author Pereira, C. T.
author_facet Pereira, C. T.
Da Silva, R.
Rosa, C. P. Da
author_role author
author2 Da Silva, R.
Rosa, C. P. Da
author2_role author
author
dc.contributor.author.fl_str_mv Pereira, C. T.
Da Silva, R.
Rosa, C. P. Da
dc.subject.por.fl_str_mv Political polarization
Computational social science (CSS) methods
Text analysis
Discourse
Twitter
topic Political polarization
Computational social science (CSS) methods
Text analysis
Discourse
Twitter
description The rise of political polarization within western societies has been portrayed by events such as the United States Capitol riot or the United Kingdom’s exit from the European Union. In this context, we argue that computational social science (CSS) methods offer a scalable and language- independent fashion to measure political polarization, enabling the processing of big data. In this vein, this article offers the first scoping review of the application of CSS methods to analyzing political polarization through text as data. We propose a categorization framework and reflect on the advantages and disadvantages of the different models used in the literature. Additionally, we underline the importance of filling research gaps, such as considering the temporal characteristic of political polarization, using a mathematical approach to analyze the use cases, and avoiding location and platform bias. We also provide recommendations for future research.
publishDate 2024
dc.date.none.fl_str_mv 2024-01-01T00:00:00Z
2024
2024-02-28T12:19:27Z
2025-02-12T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10071/31198
url http://hdl.handle.net/10071/31198
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language eng
dc.relation.none.fl_str_mv 1933-1681
10.1080/19331681.2024.2318404
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dc.publisher.none.fl_str_mv Taylor and Francis
publisher.none.fl_str_mv Taylor and Francis
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
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instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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