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Improving trust in online reviews: a machine learning approach to detecting artificial intelligence-generated reviews

2025-06-24Artigo científico Acesso aberto
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datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg16:Paz, Justiça e Instituições Eficazes
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
dc.contributor.authorAna Marta Santos
dc.contributor.authorAntonio, Nuno
dc.date.accessioned2026-03-26T10:09:56Z
dc.date.available2026-03-26T10:09:56Z
dc.date.issued2025-06-24
dc.description.abstractIn the hotel industry, social reputation is critical. Consumers increasingly rely on online reviews for accommodation decisions, making Artificial Intelligence (AI) generated fraudulent reviews a significant threat. Distinguishing between genuine and AI-generated reviews is essential for hotels to maintain credibility. This study creates a unique dataset of AI-generated reviews and combines vectorization methods with text-based features to build a Machine Learning model for identifying nongenuine reviews. Results show that incorporating text-based features significantly improves detection accuracy, and simpler vectorization methods can be effective for simpler datasets. This study contributes to academia by providing a novel methodology and publicly available dataset for further research, and to the hotel industry by enhancing credibility and consumer trust through better review filtering.eng
dc.identifier.doi10.1007/s40558-025-00329-z
dc.identifier.eissn1943-4294
dc.identifier.issn1098-3058
dc.identifier.urihttp://hdl.handle.net/10400.1/28550
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer
dc.relationInformation Management Research Center
dc.relation.ispartofInformation Technology & Tourism
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectFraudulent reviews
dc.subjectAI-generated
dc.subjectNatural language processing
dc.subjectMachine learning
dc.subjectVectorization methods
dc.titleImproving trust in online reviews: a machine learning approach to detecting artificial intelligence-generated reviewseng
dc.typejournal article
dspace.entity.typePublication
oaire.awardNumberUIDB/04152/2020
oaire.awardTitleInformation Management Research Center
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT
oaire.citation.endPage766
oaire.citation.issue3
oaire.citation.startPage739
oaire.citation.titleInformation Technology and Tourism
oaire.citation.volume27
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameAntonio
person.givenNameNuno
person.identifier.ciencia-id6818-7822-D24E
person.identifier.orcid0000-0002-4801-2487
person.identifier.ridM-1102-2015
person.identifier.scopus-author-id57193796752
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
relation.isAuthorOfPublicationa8c814d0-4336-489f-88ad-5f2cdbdeedb0
relation.isAuthorOfPublication.latestForDiscoverya8c814d0-4336-489f-88ad-5f2cdbdeedb0
relation.isProjectOfPublication26b45b04-11c7-4fd2-8cda-5dabb80d1a1a
relation.isProjectOfPublication.latestForDiscovery26b45b04-11c7-4fd2-8cda-5dabb80d1a1a

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