Multivariate Data Analysis and Social Media: a Contribution to Infodemic Management Optimization Strategy

Detalhes bibliográficos
Autor(a) principal: Hribar, Susanah Bernardo da Silva Diniz
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/10362/149114
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management
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spelling Multivariate Data Analysis and Social Media: a Contribution to Infodemic Management Optimization StrategyCovid-19InfodemiologyInfoveillanceInfodemichealth literacyDissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and ManagementAn infodemic is a huge flow of inaccurate and wrong information that may spread through social media, during an epidemic, potentially causing confusion and a damaging effect on peoples’ behavior and health. It also makes the intervention of public health agents more difficult. An infodemic can intensify outbreaks as it makes it hard for people to find trustworthy sources and reliable guidance when they need it. The study's main objective was to characterize the individual engagement performance of social media posts published before and during the Covid19 pandemic (before and after vaccination) on Facebook’s pages of selected national health organizations in order to identify a typology of agencies. Publicly available data on 39525 posts from 17 health agencies Facebook’s pages between 01/01/2019 and 31/05/2022 was retrieved and analysed with univariate and bivariate exploratory data analysis, text analysis methods and multivariate exploratory data analysis methods such as principal components analysis and hierarchical cluster analysis. Results showed that globally the Covid19 pandemic led to a relevant increase in the number of posts published on the health agencies’ Facebook pages under study and also led to a large increase on the respective audiences’ interactions. However, there was a decrease in the engagement on the pandemic period after start of the vaccination, compared to the period of the actual pandemic. Furthermore, we identified 3 types of agencies: agencies with predominance performance in total interactions, agencies with higher and lower performance in relative engagement, and finally, agencies with an opposing performance between the pandemic period and the period of mass vaccination. In short, with the Covid-19 pandemic, the public looked for more information through Facebook. Nonetheless, there might be a link between the differences in performance from these pages and different infodemics strategies. Despite some limitations, our study provides valuable insights to health agencies and the public in general, as the infodemic management should not end after the crisis but should be an ongoing investment and may represent one of the best ways to make a more effective and competent health promotion.Nicolau, Leonor Bacelar Valente da CostaRUNHribar, Susanah Bernardo da Silva Diniz2023-02-13T18:56:55Z2023-01-242023-01-24T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/149114TID:203221842enginfo: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:RCAAP2024-03-11T05:30:51Zoai:run.unl.pt:10362/149114Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:53:37.232604Repositório 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 Multivariate Data Analysis and Social Media: a Contribution to Infodemic Management Optimization Strategy
title Multivariate Data Analysis and Social Media: a Contribution to Infodemic Management Optimization Strategy
spellingShingle Multivariate Data Analysis and Social Media: a Contribution to Infodemic Management Optimization Strategy
Hribar, Susanah Bernardo da Silva Diniz
Covid-19
Infodemiology
Infoveillance
Infodemic
health literacy
title_short Multivariate Data Analysis and Social Media: a Contribution to Infodemic Management Optimization Strategy
title_full Multivariate Data Analysis and Social Media: a Contribution to Infodemic Management Optimization Strategy
title_fullStr Multivariate Data Analysis and Social Media: a Contribution to Infodemic Management Optimization Strategy
title_full_unstemmed Multivariate Data Analysis and Social Media: a Contribution to Infodemic Management Optimization Strategy
title_sort Multivariate Data Analysis and Social Media: a Contribution to Infodemic Management Optimization Strategy
author Hribar, Susanah Bernardo da Silva Diniz
author_facet Hribar, Susanah Bernardo da Silva Diniz
author_role author
dc.contributor.none.fl_str_mv Nicolau, Leonor Bacelar Valente da Costa
RUN
dc.contributor.author.fl_str_mv Hribar, Susanah Bernardo da Silva Diniz
dc.subject.por.fl_str_mv Covid-19
Infodemiology
Infoveillance
Infodemic
health literacy
topic Covid-19
Infodemiology
Infoveillance
Infodemic
health literacy
description Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management
publishDate 2023
dc.date.none.fl_str_mv 2023-02-13T18:56:55Z
2023-01-24
2023-01-24T00:00:00Z
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/10362/149114
TID:203221842
url http://hdl.handle.net/10362/149114
identifier_str_mv TID:203221842
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv 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
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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