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A study on LIWC categories for opinion mining in Spanish reviews

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dc.contributor.authorSalas Zárate, María del Pilar
dc.contributor.authorLópez López, Estanislao
dc.contributor.authorValencia García, Rafael
dc.contributor.authorAussenac Gilles, Natalie
dc.contributor.authorAlmela, Ángela
dc.contributor.authorAlor Hernández, Giner
dc.contributor.departmentFilología Inglesa
dc.date.accessioned2026-02-19T09:05:48Z
dc.date.available2026-02-19T09:05:48Z
dc.date.copyright© The Author(s) 2014
dc.date.issued2014-08-26
dc.description.abstractWith the exponential growth of social media, that is, blogs and social networks, organizations and individual persons are increasingly using the number of reviews of these media for decision-making about a product or service. Opinion mining detects whether the emotions of an opinion expressed by a user on Web platforms in natural language are positive or negative. This paper presents extensive experiments to study the effectiveness of the classification of Spanish opinions in five categories: highly positive, highly negative, positive, negative and neutral, using the combination of the psychological and linguistic features of LIWC (Linguistic Inquiry and Word Count). LIWC is a text analysis software that enables the extraction of different psychological and linguistic features from natural language text. For this study, two corpora have been used, one about movies and one about technological products. Furthermore, we conducted a comparative assessment of the performance of various classification techniques, J48, SMO and BayesNet, using precision, recall and F-measure metrics. The findings revealed that the positive and negative categories provide better results than the other categories. Finally, experiments on both corpora indicated that SMO produces better results than BayesNet and J48 algorithms, obtaining an F-measure of 90.4 and 87.2% in each domain.
dc.formatapplication/pdf
dc.identifier.citationJournal of Information Science, 2014, Vol. 40, Issue 6, pp. 749 - 760
dc.identifier.doihttps://doi.org/10.1177/016555151454784
dc.identifier.eissn1741-6485
dc.identifier.issn0165-5515
dc.identifier.urihttp://hdl.handle.net/10201/208021
dc.languageeng
dc.publisherSAGE Publications
dc.relationThis work was partially supported by the Spanish Ministry of Economy and Competitiveness and the European Commission (FEDER/ERDF) through project SeCloud (TIN2010-18650). María del Pilar Salas Forate was supported by the National Council of Science and Technology (CONACYT), the Public Education Secretary (SEP) and the Mexican government. Additionally, this work was supported by the University Paul Sabatier under its visiting professors programme.
dc.relation.publisherversionhttps://journals.sagepub.com/doi/10.1177/0165551514547842
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectOpinion mining
dc.subjectNatural language processing
dc.subjectLIWC
dc.subjectMachine learning
dc.subjectSentiment analysis
dc.subject.odsObjetivo 4: Educación
dc.titleA study on LIWC categories for opinion mining in Spanish reviews
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dspace.entity.typePublicationes
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relation.isAuthorOfPublicationa3124e18-690d-4cfc-80a4-98e6b667d928
relation.isAuthorOfPublication.latestForDiscoveryab591422-699c-4535-8e8f-fd09f0e90ec2
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