Using Candidates’ Tweets to Predict an election outcome. The United States 2022 Midterm elections study

Detalhes bibliográficos
Autor(a) principal: Afonso, Francisco Rodrigo Fernandes
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/159896
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing Intelligence
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spelling Using Candidates’ Tweets to Predict an election outcome. The United States 2022 Midterm elections studyMachine LearningPredictive ModellingTopic AnalysisPolitical CommunicationSocial Media Political MarketingTwitterDomínio/Área Científica::Ciências Naturais::Ciências da Computação e da InformaçãoDissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing IntelligenceUnderstanding social media’s role in political communication is crucial in the evolving media landscape. Motivated by the transformative impact of social media on political engagement and discourse, this research fills an under-explored academic gap, studying the effects of geographic focus—local versus national—in candidates’ tweets on U.S. Senate election outcomes. It reveals a modest but significant correlation between the nature of political discourse and election competitiveness. Interestingly, strict adherence to party-centric topics did not significantly influence electoral success. The study assessed the performance of regression and classification models in forecasting election outcomes, with classification models demonstrating superior results. Both models provide a new benchmark for future studies in political communication on social media. These findings bear considerable implications for political practitioners, indicating that election success is not merely guaranteed by echoing party centric issues or predominantly adopting a national communication scope.Rita, Paulo Miguel Rasquinho FerreiraAntónio, Nuno Miguel da ConceiçãoRUNAfonso, Francisco Rodrigo Fernandes2023-10-242026-10-24T00:00:00Z2023-10-24T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/159896TID:203385675enginfo: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:RCAAP2024-03-11T05:42:24Zoai:run.unl.pt:10362/159896Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:57:45.763463Repositório 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 Using Candidates’ Tweets to Predict an election outcome. The United States 2022 Midterm elections study
title Using Candidates’ Tweets to Predict an election outcome. The United States 2022 Midterm elections study
spellingShingle Using Candidates’ Tweets to Predict an election outcome. The United States 2022 Midterm elections study
Afonso, Francisco Rodrigo Fernandes
Machine Learning
Predictive Modelling
Topic Analysis
Political Communication
Social Media Political Marketing
Twitter
Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação
title_short Using Candidates’ Tweets to Predict an election outcome. The United States 2022 Midterm elections study
title_full Using Candidates’ Tweets to Predict an election outcome. The United States 2022 Midterm elections study
title_fullStr Using Candidates’ Tweets to Predict an election outcome. The United States 2022 Midterm elections study
title_full_unstemmed Using Candidates’ Tweets to Predict an election outcome. The United States 2022 Midterm elections study
title_sort Using Candidates’ Tweets to Predict an election outcome. The United States 2022 Midterm elections study
author Afonso, Francisco Rodrigo Fernandes
author_facet Afonso, Francisco Rodrigo Fernandes
author_role author
dc.contributor.none.fl_str_mv Rita, Paulo Miguel Rasquinho Ferreira
António, Nuno Miguel da Conceição
RUN
dc.contributor.author.fl_str_mv Afonso, Francisco Rodrigo Fernandes
dc.subject.por.fl_str_mv Machine Learning
Predictive Modelling
Topic Analysis
Political Communication
Social Media Political Marketing
Twitter
Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação
topic Machine Learning
Predictive Modelling
Topic Analysis
Political Communication
Social Media Political Marketing
Twitter
Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação
description Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing Intelligence
publishDate 2023
dc.date.none.fl_str_mv 2023-10-24
2023-10-24T00:00:00Z
2026-10-24T00:00:00Z
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/10362/159896
TID:203385675
url http://hdl.handle.net/10362/159896
identifier_str_mv TID:203385675
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/embargoedAccess
eu_rights_str_mv embargoedAccess
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
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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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
repository.mail.fl_str_mv
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