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Masking domain-specific information for cross-domain deception detection

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Masking domain-specific information for cross-domain deception detection

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dc.contributor.author Sánchez-Junquera, Javier es_ES
dc.contributor.author Villaseñor-Pineda, Luis es_ES
dc.contributor.author Montes-y-Gómez, Manuel es_ES
dc.contributor.author Rosso, Paolo es_ES
dc.contributor.author Stamatatos, Efstathios es_ES
dc.date.accessioned 2021-11-05T12:27:29Z
dc.date.available 2021-11-05T12:27:29Z
dc.date.issued 2020-07 es_ES
dc.identifier.issn 0167-8655 es_ES
dc.identifier.uri http://hdl.handle.net/10251/176093
dc.description.abstract [EN] The facilities provided by social media and computer-mediated communication make easy the dissemination of deceptive behavior, after which different entities or people could be affected. The deception detection by supervised learning has been widely studied; however, the scenario in which there is one domain of interest and the labeled data is in another domain has received poor attention. This paper presents, to our knowledge, the first domain adaptation approach for cross-domain deception detection in texts. Our proposal consists in modifying original texts from the source and target domains in a form in which common content and style information is maintained, but domain-specific information is masked. In order to adequately select domain-specific terms to be masked, the proposed method uses unlabeled instances from both domains. Our experiments demonstrate that the masking technique is a good idea for detecting deception in cross-domain scenarios; and the performance could be further improved if unlabeled information from the target domain is considered. es_ES
dc.description.sponsorship The work of Javier Sanchez-Junquera and Paolo Rosso was funded by the MISMIS-FAKEnHATE Spanish MICINN research project (PGC2018-096212-B-C31). This work was parrtially supported also by CONACyT under grants CB-2015-01-257383, the Thematic Networks program, and the scholarship CONACyT-Mexico 613411. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Pattern Recognition Letters es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Deception detection es_ES
dc.subject Domain adaptation es_ES
dc.subject Masking information es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Masking domain-specific information for cross-domain deception detection es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.patrec.2020.04.020 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/CONACYT//613411/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/CONACYT//CB-2015-01-257383/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//PGC2018-096212-B-C31-AR//DESINFORMACION Y AGRESIVIDAD EN SOCIAL MEDIA: AGREGANDO INFORMACION Y ANALIZANDO EL LENGUAJE./ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Sánchez-Junquera, J.; Villaseñor-Pineda, L.; Montes-Y-Gómez, M.; Rosso, P.; Stamatatos, E. (2020). Masking domain-specific information for cross-domain deception detection. Pattern Recognition Letters. 135:122-130. https://doi.org/10.1016/j.patrec.2020.04.020 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.patrec.2020.04.020 es_ES
dc.description.upvformatpinicio 122 es_ES
dc.description.upvformatpfin 130 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 135 es_ES
dc.relation.pasarela S\419052 es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES
dc.contributor.funder Consejo Nacional de Ciencia y Tecnología, México es_ES


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