What are consumers saying online about your products?: mining the text of online reviews to uncover hidden features
| dc.contributor.author | Alzate Barricarte, Miriam | |
| dc.contributor.author | Arce Urriza, Marta | |
| dc.contributor.author | Cebollada Calvo, Javier | |
| dc.contributor.department | Gestión de Empresas | es_ES |
| dc.contributor.department | Enpresen Kudeaketa | eu |
| dc.date.accessioned | 2025-01-22T07:28:51Z | |
| dc.date.available | 2025-01-22T07:28:51Z | |
| dc.date.issued | 2021 | |
| dc.date.updated | 2025-01-22T07:26:06Z | |
| dc.description | Acceso cerrado a este documento. No se encuentra disponible para la consulta pública. Depositado en Academica-e para cumplir con los requisitos de evaluación y acreditación académica del autor/a (sexenios, acreditaciones, etc.). | es_ES |
| dc.description.abstract | Thanks to the growth of the internet and the increasing use of social networks, companies can now access huge volumes of online texts in order to understand consumers¿ preferences and needs. This article illustrates some methods to extrapolate information from such texts. The text-mining analysis covers such issues as word frequency, sentiment analysis, paired words, similarities in textual content and the main topics discussed in online reviews. From a practical point of view, brand managers can use the proposed methods to gain consumer insights into products and brands, to be able to improve and adapt their marketing strategies. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Alzate, M., Arce-Urriza, M., Cebollada, J. (2021) What are consumers saying online about your products?: mining the text of online reviews to uncover hidden features. Journal Of Digital And Social Media Marketing, 9(2), 169-186 | |
| dc.identifier.issn | 2050-0076 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/53033 | |
| dc.language.iso | eng | |
| dc.publisher | Henry Stewart Publications | |
| dc.relation.ispartof | Journal Of Digital And Social Media Marketing, 9(2), 169-186 | |
| dc.rights | © 2021 Henry Stewart Publications | |
| dc.rights.accessRights | info:eu-repo/semantics/closedAccess | |
| dc.subject | eWOM | en |
| dc.subject | Online reviews | en |
| dc.subject | Text mining | en |
| dc.subject | Sentiment analysis | en |
| dc.subject | Topic modelling | en |
| dc.title | What are consumers saying online about your products?: mining the text of online reviews to uncover hidden features | en |
| dc.type | info:eu-repo/semantics/article | |
| dspace.entity.type | Publication | |
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