eWOM for public institutions: application to the case of the Portuguese Army
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/23751 |
Resumo: | Social media platforms provide easy access to the public opinion (called electronic word-of-mouth), which can be collected and analyzed to extract knowledge about the reputation of an organization. Monitoring this reputation in the public sector may bring several benefits for its institutions, especially in supporting decision-making and developing marketing campaigns. Thus, to offer a solution aimed at the needs of this sector, the goal of this research was to develop a methodology capable of extracting relevant information about eWOM in social media, using text mining and natural language processing techniques. Our goal was achieved through a methodology capable of handling the small amount of information regarding public state organizations in social media. Additionally, our work was validated using the context of the Portuguese Army and revealed the potential to provide indicators of institutional reputation. Our results present one of the first cases of the application of this type of techniques to an Army organization and to understand its negative reputation among the population. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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eWOM for public institutions: application to the case of the Portuguese ArmyeWOMPublic sectorReputationSocial mediaVoluntary serviceSocial media platforms provide easy access to the public opinion (called electronic word-of-mouth), which can be collected and analyzed to extract knowledge about the reputation of an organization. Monitoring this reputation in the public sector may bring several benefits for its institutions, especially in supporting decision-making and developing marketing campaigns. Thus, to offer a solution aimed at the needs of this sector, the goal of this research was to develop a methodology capable of extracting relevant information about eWOM in social media, using text mining and natural language processing techniques. Our goal was achieved through a methodology capable of handling the small amount of information regarding public state organizations in social media. Additionally, our work was validated using the context of the Portuguese Army and revealed the potential to provide indicators of institutional reputation. Our results present one of the first cases of the application of this type of techniques to an Army organization and to understand its negative reputation among the population.Springer2022-11-08T00:00:00Z2021-01-01T00:00:00Z20212021-12-15T13:04:45Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/23751eng1869-545010.1007/s13278-021-00837-wAzinhaes, J.Batista, F.Ferreira, J.info: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:RCAAP2023-11-09T18:01:50Zoai:repositorio.iscte-iul.pt:10071/23751Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:33:11.421886Repositório 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 |
eWOM for public institutions: application to the case of the Portuguese Army |
title |
eWOM for public institutions: application to the case of the Portuguese Army |
spellingShingle |
eWOM for public institutions: application to the case of the Portuguese Army Azinhaes, J. eWOM Public sector Reputation Social media Voluntary service |
title_short |
eWOM for public institutions: application to the case of the Portuguese Army |
title_full |
eWOM for public institutions: application to the case of the Portuguese Army |
title_fullStr |
eWOM for public institutions: application to the case of the Portuguese Army |
title_full_unstemmed |
eWOM for public institutions: application to the case of the Portuguese Army |
title_sort |
eWOM for public institutions: application to the case of the Portuguese Army |
author |
Azinhaes, J. |
author_facet |
Azinhaes, J. Batista, F. Ferreira, J. |
author_role |
author |
author2 |
Batista, F. Ferreira, J. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Azinhaes, J. Batista, F. Ferreira, J. |
dc.subject.por.fl_str_mv |
eWOM Public sector Reputation Social media Voluntary service |
topic |
eWOM Public sector Reputation Social media Voluntary service |
description |
Social media platforms provide easy access to the public opinion (called electronic word-of-mouth), which can be collected and analyzed to extract knowledge about the reputation of an organization. Monitoring this reputation in the public sector may bring several benefits for its institutions, especially in supporting decision-making and developing marketing campaigns. Thus, to offer a solution aimed at the needs of this sector, the goal of this research was to develop a methodology capable of extracting relevant information about eWOM in social media, using text mining and natural language processing techniques. Our goal was achieved through a methodology capable of handling the small amount of information regarding public state organizations in social media. Additionally, our work was validated using the context of the Portuguese Army and revealed the potential to provide indicators of institutional reputation. Our results present one of the first cases of the application of this type of techniques to an Army organization and to understand its negative reputation among the population. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01T00:00:00Z 2021 2021-12-15T13:04:45Z 2022-11-08T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/23751 |
url |
http://hdl.handle.net/10071/23751 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1869-5450 10.1007/s13278-021-00837-w |
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.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
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) |
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 |
repository.mail.fl_str_mv |
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1799134893000622080 |