A business context aware decision-making approach for selecting the most appropriate sentiment analysis technique in e-marketing situations
dc.contributor.author | Bueno García, Itzcoatl | |
dc.contributor.author | Carrasco González, Ramón Alberto | |
dc.contributor.author | Ureña, Raquel | |
dc.contributor.author | Herrera-Viedma, Enrique | |
dc.date.accessioned | 2025-01-14T09:37:41Z | |
dc.date.available | 2025-01-14T09:37:41Z | |
dc.date.issued | 2022 | |
dc.description.abstract | In the era of social media, consumers interact and exchange information, subjective opin ions, feelings or thoughts about a given issue, a product or a service, via Web 2.0 technolo gies. As a result, electronic Word of Mouth, eWOM, has gained increasing influence on the formation of user opinions. Therefore, extracting and analyzing eWOM statements by means of Sentiment Analysis techniques is currently a hot topic that could potentially pro vide companies with key information about their customers. However, among all the avail able techniques, choosing the most appropriate one according to the analysis criteria is a real challenge. In this contribution, we first study the main desirable criteria for a senti ment analysis approach and classify the different existing approaches based on these cri teria to try and provide a solution to this issue. We then propose a Multi-criteria Decision-Making methodology that selects the most suitable technique for each business case by taking their particular criteria into account. | |
dc.description.department | Depto. de Estadística y Ciencia de los Datos | |
dc.description.faculty | Fac. de Estudios Estadísticos | |
dc.description.refereed | TRUE | |
dc.description.status | pub | |
dc.identifier.citation | Bueno, I., Carrasco, R. A., Ureña, R., & Herrera-Viedma, E. (2022). A business context aware decision-making approach for selecting the most appropriate sentiment analysis technique in e-marketing situations. Information Sciences, 589, 300–320. https://doi.org/10.1016/J.INS.2021.12.080 | |
dc.identifier.doi | 10.1016/j.ins.2021.12.080 | |
dc.identifier.officialurl | https://doi.org/10.1016/j.ins.2021.12.080 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14352/114165 | |
dc.journal.title | Information Sciences | |
dc.language.iso | eng | |
dc.page.final | 320 | |
dc.page.initial | 300 | |
dc.publisher | Elsevier | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
dc.rights.accessRights | open access | |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject.cdu | 519.862.6 | |
dc.subject.cdu | 658.8:004.738.5 | |
dc.subject.cdu | 339:077 | |
dc.subject.keyword | Sentiment analysis | |
dc.subject.keyword | AHP | |
dc.subject.keyword | Multi-Criteria Decision-Making | |
dc.subject.keyword | Auto machine learning | |
dc.subject.ucm | Econometría (Estadística) | |
dc.subject.ucm | Marketing | |
dc.subject.unesco | 5302 Econometría | |
dc.subject.unesco | 5311.05 Marketing (Comercialización) | |
dc.title | A business context aware decision-making approach for selecting the most appropriate sentiment analysis technique in e-marketing situations | |
dc.type | journal article | |
dc.type.hasVersion | VoR | |
dc.volume.number | 589 | |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | 25aa3e94-be75-4c29-a45b-52918a67e41e | |
relation.isAuthorOfPublication | 658b3e73-df89-4013-b006-45ea9db05e25 | |
relation.isAuthorOfPublication.latestForDiscovery | 25aa3e94-be75-4c29-a45b-52918a67e41e |
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