Inferring trust using personality aspects extracted from texts

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dc.contributor.authorGranatyr, Jonesen_NZ
dc.contributor.authorGomes, Heitor Muriloen_NZ
dc.contributor.authorDIas, João Miguelen_NZ
dc.contributor.authorPaiva, Ana Mariaen_NZ
dc.contributor.authorNunes, Maria Augusta Silveira Nettoen_NZ
dc.contributor.authorScalabrin, Edson Emílioen_NZ
dc.contributor.authorSpak, Fábioen_NZ
dc.coverage.spatialBari, Italyen_NZ
dc.date.accessioned2021-03-25T01:21:33Z
dc.date.available2021-03-25T01:21:33Z
dc.date.issued2019en_NZ
dc.description.abstractTrust mechanisms are considered the logical protection of software systems, preventing malicious people from taking advantage or cheating others. Although these concepts are widely used, most applications in this field do not consider affective aspects to aid in trust computation. Researchers of Psychology, Neurology, Anthropology, and Computer Science argue that affective aspects are essential to human's decision-making processes. So far, there is a lack of understanding about how these aspects impact user's trust, particularly when they are inserted in an evaluation system. In this paper, we propose a trust model that accounts for personality using three personality models: Big Five, Needs, and Values. We tested our approach by extracting personality aspects from texts provided by two online human-fed evaluation systems and correlating them to reputation values. The empirical experiments show statistically significant better results in comparison to non-personality-wise approaches.en_NZ
dc.format.mimetypeapplication/pdf
dc.identifier.citationGranatyr, J., Gomes, H. M., DIas, J. M., Paiva, A. M., Nunes, M. A. S. N., Scalabrin, E. E., & Spak, F. (2019). Inferring trust using personality aspects extracted from texts. In Proceeding of IEEE International Conference on Systems, Man and Cybernetics (SMC 2019) (pp. 3840–3846). Washington, DC, USA: IEEE. https://doi.org/10.1109/SMC.2019.8914641en
dc.identifier.doi10.1109/SMC.2019.8914641en_NZ
dc.identifier.isbn9781728145693en_NZ
dc.identifier.issn1062-922Xen_NZ
dc.identifier.urihttps://hdl.handle.net/10289/14199
dc.language.isoen
dc.publisherIEEEen_NZ
dc.relation.isPartOfProceeding of IEEE International Conference on Systems, Man and Cybernetics (SMC 2019)en_NZ
dc.rightsThis is an author’s accepted version of an article published in the Proceeding of IEEE International Conference on Systems, Man and Cybernetics (SMC 2019). © 2019 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
dc.sourceSMC 2019en_NZ
dc.subjectcomputer scienceen_NZ
dc.subjectcomputational modelingen_NZ
dc.subjectnumerical modelsen_NZ
dc.subjecttoolsen_NZ
dc.subjectdecision makingen_NZ
dc.subjectcorrelationen_NZ
dc.subjectdata miningen_NZ
dc.subjectdata modelsen_NZ
dc.titleInferring trust using personality aspects extracted from textsen_NZ
dc.typeConference Contribution
pubs.begin-page3840
pubs.elements-id256853
pubs.end-page3846
pubs.finish-date2019-10-09en_NZ
pubs.organisational-group/Waikato
pubs.organisational-group/Waikato/DHECS
pubs.organisational-group/Waikato/DHECS/SCMS
pubs.place-of-publicationWashington, DC, USA
pubs.publication-statusPublisheden_NZ
pubs.start-date2019-10-06en_NZ
pubs.user.infoGomes, Heitor (hgomes@waikato.ac.nz)
uow.verification.statusverified
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