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Sentiment Analysis of Portuguese Political Parties Communication

Detalhes bibliográficos
Autor(a) principal: Costa, Carlos J.
Data de Publicação: 2021
Outros Autores: Aparicio, Manuela, Aparicio, Joao
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10362/126515
Resumo: Costa, C. J., Aparicio, M., & Aparicio, J. (2021). Sentiment Analysis of Portuguese Political Parties Communication. In Proceedings of the 39th ACM International Conference on the Design of Communication (SIGDOC '21) (pp. 63-69). Association for Computing Machinery (ACM). https://doi.org/10.1145/3472714.3473624
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network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Sentiment Analysis of Portuguese Political Parties Communicationdocument similaritymachine learningpolitical partiessentiment analysisTwitterComputer Networks and CommunicationsComputer Science ApplicationsSoftwareSDG 11 - Sustainable Cities and CommunitiesSDG 16 - Peace, Justice and Strong InstitutionsCosta, C. J., Aparicio, M., & Aparicio, J. (2021). Sentiment Analysis of Portuguese Political Parties Communication. In Proceedings of the 39th ACM International Conference on the Design of Communication (SIGDOC '21) (pp. 63-69). Association for Computing Machinery (ACM). https://doi.org/10.1145/3472714.3473624Political communication in social media has gained increasing importance in the last years. In this study, we analyze the political parties’ communication on Twitter and understand the sentiment of their communication. First by identifying their communication performance regarding the daily number of tweets, favorite tweets, number of retweets per day and per political party. We present a sentiment analysis by the political party using tweets data. In this study, we propose an explanatory model with the main drivers of retweets. To conduct this study, our approach used data analysis and machine learning techniques methods. Results indicate the main determinants that influence future retweets of political posts globally. Here we present a comparison of the communication content between tweets posts and the political parties’ programs available on their institutional websites. We identify the similarities between tweets and formal programs per party and among all parties. This study contributes to analyze the coherence and effectiveness of the political parties’ communication.ACM - Association for Computing MachineryNOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNCosta, Carlos J.Aparicio, ManuelaAparicio, Joao2021-10-22T03:55:42Z2021-10-122021-10-12T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersion7application/pdfhttp://hdl.handle.net/10362/126515eng978-1-4503-8628-9PURE: 34339974https://doi.org/10.1145/3472714.3473624info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:56:48Zoai:run.unl.pt:10362/126515Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:27:51.430544Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Sentiment Analysis of Portuguese Political Parties Communication
title Sentiment Analysis of Portuguese Political Parties Communication
spellingShingle Sentiment Analysis of Portuguese Political Parties Communication
Costa, Carlos J.
document similarity
machine learning
political parties
sentiment analysis
Twitter
Computer Networks and Communications
Computer Science Applications
Software
SDG 11 - Sustainable Cities and Communities
SDG 16 - Peace, Justice and Strong Institutions
title_short Sentiment Analysis of Portuguese Political Parties Communication
title_full Sentiment Analysis of Portuguese Political Parties Communication
title_fullStr Sentiment Analysis of Portuguese Political Parties Communication
title_full_unstemmed Sentiment Analysis of Portuguese Political Parties Communication
title_sort Sentiment Analysis of Portuguese Political Parties Communication
author Costa, Carlos J.
author_facet Costa, Carlos J.
Aparicio, Manuela
Aparicio, Joao
author_role author
author2 Aparicio, Manuela
Aparicio, Joao
author2_role author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Costa, Carlos J.
Aparicio, Manuela
Aparicio, Joao
dc.subject.por.fl_str_mv document similarity
machine learning
political parties
sentiment analysis
Twitter
Computer Networks and Communications
Computer Science Applications
Software
SDG 11 - Sustainable Cities and Communities
SDG 16 - Peace, Justice and Strong Institutions
topic document similarity
machine learning
political parties
sentiment analysis
Twitter
Computer Networks and Communications
Computer Science Applications
Software
SDG 11 - Sustainable Cities and Communities
SDG 16 - Peace, Justice and Strong Institutions
description Costa, C. J., Aparicio, M., & Aparicio, J. (2021). Sentiment Analysis of Portuguese Political Parties Communication. In Proceedings of the 39th ACM International Conference on the Design of Communication (SIGDOC '21) (pp. 63-69). Association for Computing Machinery (ACM). https://doi.org/10.1145/3472714.3473624
publishDate 2021
dc.date.none.fl_str_mv 2021-10-22T03:55:42Z
2021-10-12
2021-10-12T00:00:00Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/126515
url http://hdl.handle.net/10362/126515
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-1-4503-8628-9
PURE: 34339974
https://doi.org/10.1145/3472714.3473624
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 7
application/pdf
dc.publisher.none.fl_str_mv ACM - Association for Computing Machinery
publisher.none.fl_str_mv ACM - Association for Computing Machinery
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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