QOE Analysis for Mobile Network Services using Twitter Opinion Extraction
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | INFOCOMP: Jornal de Ciência da Computação |
Texto Completo: | https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/2205 |
Resumo: | Mobile communication networks have been evolving over time to meet the expectations of consumers who are increasingly accustomed to the facilities offered by the services provided by such networks. Studies on QoE (quality of experience) are presented to analyze the satisfaction of a final consumer about a given product or service. Thus, this research sought new QoE indicators in an automated way for mobile communications operators that operate in Brazil. Thus, an application was created that sought to mine opinions emitted in tweets from the social network Twitter and score them according to the MOS (Mean Opinion Score). In its results it was possible to observe a tendency of the carriers' customers to use Twitter more to complain than to express opinions of satisfaction. The research observed a scarcity of research that uses a methodology analogous to the one employed, so it believes it can contribute to new research proposals that seek automation in the generation of QoE |
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QOE Analysis for Mobile Network Services using Twitter Opinion ExtractionMobile communication networks have been evolving over time to meet the expectations of consumers who are increasingly accustomed to the facilities offered by the services provided by such networks. Studies on QoE (quality of experience) are presented to analyze the satisfaction of a final consumer about a given product or service. Thus, this research sought new QoE indicators in an automated way for mobile communications operators that operate in Brazil. Thus, an application was created that sought to mine opinions emitted in tweets from the social network Twitter and score them according to the MOS (Mean Opinion Score). In its results it was possible to observe a tendency of the carriers' customers to use Twitter more to complain than to express opinions of satisfaction. The research observed a scarcity of research that uses a methodology analogous to the one employed, so it believes it can contribute to new research proposals that seek automation in the generation of QoEEditora da UFLA2022-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/2205INFOCOMP Journal of Computer Science; Vol. 21 No. 1 (2022): June 20221982-33631807-4545reponame:INFOCOMP: Jornal de Ciência da Computaçãoinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/2205/575Copyright (c) 2022 Marcelo Santos, Renata Lopesinfo:eu-repo/semantics/openAccessSantos, MarceloLopes, Renata2022-06-01T13:53:39Zoai:infocomp.dcc.ufla.br:article/2205Revistahttps://infocomp.dcc.ufla.br/index.php/infocompPUBhttps://infocomp.dcc.ufla.br/index.php/infocomp/oaiinfocomp@dcc.ufla.br||apfreire@dcc.ufla.br1982-33631807-4545opendoar:2024-05-21T19:54:47.862018INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)true |
dc.title.none.fl_str_mv |
QOE Analysis for Mobile Network Services using Twitter Opinion Extraction |
title |
QOE Analysis for Mobile Network Services using Twitter Opinion Extraction |
spellingShingle |
QOE Analysis for Mobile Network Services using Twitter Opinion Extraction Santos, Marcelo |
title_short |
QOE Analysis for Mobile Network Services using Twitter Opinion Extraction |
title_full |
QOE Analysis for Mobile Network Services using Twitter Opinion Extraction |
title_fullStr |
QOE Analysis for Mobile Network Services using Twitter Opinion Extraction |
title_full_unstemmed |
QOE Analysis for Mobile Network Services using Twitter Opinion Extraction |
title_sort |
QOE Analysis for Mobile Network Services using Twitter Opinion Extraction |
author |
Santos, Marcelo |
author_facet |
Santos, Marcelo Lopes, Renata |
author_role |
author |
author2 |
Lopes, Renata |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Santos, Marcelo Lopes, Renata |
description |
Mobile communication networks have been evolving over time to meet the expectations of consumers who are increasingly accustomed to the facilities offered by the services provided by such networks. Studies on QoE (quality of experience) are presented to analyze the satisfaction of a final consumer about a given product or service. Thus, this research sought new QoE indicators in an automated way for mobile communications operators that operate in Brazil. Thus, an application was created that sought to mine opinions emitted in tweets from the social network Twitter and score them according to the MOS (Mean Opinion Score). In its results it was possible to observe a tendency of the carriers' customers to use Twitter more to complain than to express opinions of satisfaction. The research observed a scarcity of research that uses a methodology analogous to the one employed, so it believes it can contribute to new research proposals that seek automation in the generation of QoE |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/2205 |
url |
https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/2205 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/2205/575 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2022 Marcelo Santos, Renata Lopes info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2022 Marcelo Santos, Renata Lopes |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Editora da UFLA |
publisher.none.fl_str_mv |
Editora da UFLA |
dc.source.none.fl_str_mv |
INFOCOMP Journal of Computer Science; Vol. 21 No. 1 (2022): June 2022 1982-3363 1807-4545 reponame:INFOCOMP: Jornal de Ciência da Computação instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
INFOCOMP: Jornal de Ciência da Computação |
collection |
INFOCOMP: Jornal de Ciência da Computação |
repository.name.fl_str_mv |
INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
infocomp@dcc.ufla.br||apfreire@dcc.ufla.br |
_version_ |
1799874742689202176 |