Text mining social media for competitive analysis
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://scielo.pt/scielo.php?script=sci_arttext&pid=S2182-84582015000100010 |
Resumo: | Social media are utilised widely. Companies increasingly use social media to communicate and interact with customers. Much information is thereby generated and is available to everybody, including competitors. Firms need to analyse what their customers say and interact with them. Using text mining tools, companies can know where they are in relation to their competitors and control the behaviour of these. Transforming text into data and data into knowledge can be vital to make the right decisions and improving the competitive strategy of companies. This study used a text mining tool to analyse the primary social media sites, including Twitter, Facebook, LinkedIn, YouTube and others, with a focus on a sample of hotels. The dimensions analysed were sentiments, passion and reach. A dependence was found between several variables obtained through text mining and financial performance. The results indicate that analysis of social media using these techniques can be a method to improve financial performance. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Text mining social media for competitive analysisCompetitive intelligencesocial mediatext mininghotel industryfinancial performanceSocial media are utilised widely. Companies increasingly use social media to communicate and interact with customers. Much information is thereby generated and is available to everybody, including competitors. Firms need to analyse what their customers say and interact with them. Using text mining tools, companies can know where they are in relation to their competitors and control the behaviour of these. Transforming text into data and data into knowledge can be vital to make the right decisions and improving the competitive strategy of companies. This study used a text mining tool to analyse the primary social media sites, including Twitter, Facebook, LinkedIn, YouTube and others, with a focus on a sample of hotels. The dimensions analysed were sentiments, passion and reach. A dependence was found between several variables obtained through text mining and financial performance. The results indicate that analysis of social media using these techniques can be a method to improve financial performance.Escola Superior de Gestão, Hotelaria e Turismo da Universidade do Algarve2015-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articletext/htmlhttp://scielo.pt/scielo.php?script=sci_arttext&pid=S2182-84582015000100010Tourism & Management Studies v.11 n.1 2015reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttp://scielo.pt/scielo.php?script=sci_arttext&pid=S2182-84582015000100010Gémar,GermánJiménez-Quintero,José Antonioinfo:eu-repo/semantics/openAccess2024-02-06T17:29:01Zoai:scielo:S2182-84582015000100010Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:33:05.883059Repositório 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 |
Text mining social media for competitive analysis |
title |
Text mining social media for competitive analysis |
spellingShingle |
Text mining social media for competitive analysis Gémar,Germán Competitive intelligence social media text mining hotel industry financial performance |
title_short |
Text mining social media for competitive analysis |
title_full |
Text mining social media for competitive analysis |
title_fullStr |
Text mining social media for competitive analysis |
title_full_unstemmed |
Text mining social media for competitive analysis |
title_sort |
Text mining social media for competitive analysis |
author |
Gémar,Germán |
author_facet |
Gémar,Germán Jiménez-Quintero,José Antonio |
author_role |
author |
author2 |
Jiménez-Quintero,José Antonio |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Gémar,Germán Jiménez-Quintero,José Antonio |
dc.subject.por.fl_str_mv |
Competitive intelligence social media text mining hotel industry financial performance |
topic |
Competitive intelligence social media text mining hotel industry financial performance |
description |
Social media are utilised widely. Companies increasingly use social media to communicate and interact with customers. Much information is thereby generated and is available to everybody, including competitors. Firms need to analyse what their customers say and interact with them. Using text mining tools, companies can know where they are in relation to their competitors and control the behaviour of these. Transforming text into data and data into knowledge can be vital to make the right decisions and improving the competitive strategy of companies. This study used a text mining tool to analyse the primary social media sites, including Twitter, Facebook, LinkedIn, YouTube and others, with a focus on a sample of hotels. The dimensions analysed were sentiments, passion and reach. A dependence was found between several variables obtained through text mining and financial performance. The results indicate that analysis of social media using these techniques can be a method to improve financial performance. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-01-01 |
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://scielo.pt/scielo.php?script=sci_arttext&pid=S2182-84582015000100010 |
url |
http://scielo.pt/scielo.php?script=sci_arttext&pid=S2182-84582015000100010 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://scielo.pt/scielo.php?script=sci_arttext&pid=S2182-84582015000100010 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Escola Superior de Gestão, Hotelaria e Turismo da Universidade do Algarve |
publisher.none.fl_str_mv |
Escola Superior de Gestão, Hotelaria e Turismo da Universidade do Algarve |
dc.source.none.fl_str_mv |
Tourism & Management Studies v.11 n.1 2015 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 |
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1799137391226650624 |