Analizzare l’argomentazione sui social media
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Data de Publicação: | 2019 |
Tipo de documento: | Artigo |
Idioma: | ita |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/99409 |
Resumo: | UID/FIL/00183/2019 SFRH/BPD/115073/2016 PTDC/FER-FIL/28278/2017 PTDC/MHC-FIL/0521/2014 |
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Analizzare l’argomentazione sui social mediaIl caso dei tweet di Salviniargumentationemotive wordsTwitterSalvinifallaciespresuppositionLanguage and LinguisticsExperimental and Cognitive PsychologyLinguistics and LanguageCognitive NeuroscienceArtificial IntelligenceUID/FIL/00183/2019 SFRH/BPD/115073/2016 PTDC/FER-FIL/28278/2017 PTDC/MHC-FIL/0521/2014Twitter is an instrument used not only for sharing public or personal information, but also for persuading the audience. While specific platforms and software have been developed for analyzing macro-analytical data, and specific studies have focused on the linguistic dimension of the tweets, the argumentative dimension of the latter is unexplored to this date. This paper intends to propose a method grounded on the tools advanced in argumentation theory for capturing, coding, and assessing the different argumentative dimensions of the messages posted on Twitter, focusing on the types of argument communicated, the quality of their premises, and the fallacies committed – including the use of unshared presuppositions and emotive words. This method is applied to a corpus of 843 tweets published by the Italian Minister of the Interior, Mr. Matteo Salvini, from the date of his appointment to the beginning of his campaign for the European elections. The quantitative data provide general indications for detecting the strategies that characterize the argumentative profile of Salvini, which are then analyzed qualitatively.Instituto de Filosofia da NOVA (IFILNOVA)Departamento de Filosofia (DEF)RUNMacagno, Fabrizio2022-03-09T01:31:27Z20192019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article31application/pdfhttp://hdl.handle.net/10362/99409ita1120-9550PURE: 16581046https://doi.org/10.1422/95091info: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:RCAAP2024-03-11T04:46:18Zoai:run.unl.pt:10362/99409Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:39:10.157242Repositório 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 |
Analizzare l’argomentazione sui social media Il caso dei tweet di Salvini |
title |
Analizzare l’argomentazione sui social media |
spellingShingle |
Analizzare l’argomentazione sui social media Macagno, Fabrizio argumentation emotive words Salvini fallacies presupposition Language and Linguistics Experimental and Cognitive Psychology Linguistics and Language Cognitive Neuroscience Artificial Intelligence |
title_short |
Analizzare l’argomentazione sui social media |
title_full |
Analizzare l’argomentazione sui social media |
title_fullStr |
Analizzare l’argomentazione sui social media |
title_full_unstemmed |
Analizzare l’argomentazione sui social media |
title_sort |
Analizzare l’argomentazione sui social media |
author |
Macagno, Fabrizio |
author_facet |
Macagno, Fabrizio |
author_role |
author |
dc.contributor.none.fl_str_mv |
Instituto de Filosofia da NOVA (IFILNOVA) Departamento de Filosofia (DEF) RUN |
dc.contributor.author.fl_str_mv |
Macagno, Fabrizio |
dc.subject.por.fl_str_mv |
argumentation emotive words Salvini fallacies presupposition Language and Linguistics Experimental and Cognitive Psychology Linguistics and Language Cognitive Neuroscience Artificial Intelligence |
topic |
argumentation emotive words Salvini fallacies presupposition Language and Linguistics Experimental and Cognitive Psychology Linguistics and Language Cognitive Neuroscience Artificial Intelligence |
description |
UID/FIL/00183/2019 SFRH/BPD/115073/2016 PTDC/FER-FIL/28278/2017 PTDC/MHC-FIL/0521/2014 |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 2019-01-01T00:00:00Z 2022-03-09T01:31:27Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
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article |
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publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/99409 |
url |
http://hdl.handle.net/10362/99409 |
dc.language.iso.fl_str_mv |
ita |
language |
ita |
dc.relation.none.fl_str_mv |
1120-9550 PURE: 16581046 https://doi.org/10.1422/95091 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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31 application/pdf |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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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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