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Mining the text of online consumer reviews to analyze brand image and brand positioning

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dc.contributor.authorAlzate Barricarte, Miriam
dc.contributor.authorArce Urriza, Marta
dc.contributor.authorCebollada Calvo, Javier
dc.contributor.departmentGestión de Empresases_ES
dc.contributor.departmentEnpresen Kudeaketaeu
dc.date.accessioned2022-08-04T08:17:43Z
dc.date.available2022-08-04T08:17:43Z
dc.date.issued2022
dc.date.updated2022-08-04T07:23:46Z
dc.description.abstractThe growth of the Internet has led to massive availability of online consumer reviews. So far, papers studying online reviews have mainly analysed how non-textual features, such as ratings and volume, influence different types of consumer behavior, such as information adoption decisions or product choices. However, little attention has been paid to examining the textual aspects of online reviews in order to study brand image and brand positioning. The text analysis of online reviews inevitably raises the concept of 'text mining'; that is, the process of extracting useful and meaningful information from unstructured text. This research proposes an unified, structured and easy-to-implement procedure for the text analysis of online reviews with the ultimate goal of studying brand image and brand positioning. The text mining analysis is based on a lexicon-based approach, the Linguistic Inquiry and Word Count (Pennebaker et al., 2007), which provides the researcher with insights into emotional and psychological brand associations.en
dc.description.sponsorshipThis work was supported by the Spanish Ministry of Economy, Industry and Competitivity [grant number: ECO2015-65393-R] and by the Government of Spain Ministry of Science, Innovation and Universities Grant numbers: PID2019-108554RB-I00.en
dc.format.mimetypeapplication/pdfen
dc.identifier.citationAlzate, M.; Arce-Urriza, M.; Cebollada, J.. (2022). Mining the text of online consumer reviews to analyze brand image and brand positioning. Journal of Reatlaing Consumer Services. 67, .en
dc.identifier.doi10.1016/j.jretconser.2022.102989
dc.identifier.issn0969-6989
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/43696
dc.language.isoengen
dc.publisherElsevieren
dc.relation.ispartofJournal of Reatlaing Consumer Services, 2022, Vol. 67en
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//ECO2015-65393-R/ES/en
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108554RB-I00/ES/en
dc.relation.publisherversionhttps://doi.org/10.1016/j.jretconser.2022.102989
dc.rights© 2022 The Authors. This is an open access article under the CC BY license http://creativecommons.org/licenses/by/4.0/en
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectBrand positioningen
dc.subjecteWOMen
dc.subjectOnline reviewsen
dc.subjectText miningen
dc.titleMining the text of online consumer reviews to analyze brand image and brand positioningen
dc.typeinfo:eu-repo/semantics/article
dc.type.versionVersión publicada / Argitaratu den bertsioaes
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dspace.entity.typePublication
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relation.isAuthorOfPublicationb85da891-c838-4554-992f-e730c841c150
relation.isAuthorOfPublication.latestForDiscovery60018b21-fd72-4cad-b2ca-b5a6149e6310

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