First Results on Using Transformer for Extroversion Personality Trait Recognition

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dc.contributor.authorGoncalves, Alan
dc.contributor.authorCarvalho, Marco A.G.
dc.contributor.authorRamos, Josue J.G.
dc.contributor.authorPaiva, Pedro V.V.
dc.contributor.editorSkala, Václav
dc.date.accessioned2024-07-21T09:33:29Z
dc.date.available2024-07-21T09:33:29Z
dc.date.issued2024
dc.description.abstract-translatedPersonality traits are characteristics that can describe a person’s behavior, also reflecting their thoughts and feel ings. There are those who support the idea that traits can be strong predictors of leadership, implying emotional stability of the individual. Knowing the importance of the subject, areas such as psychology and neuropsychol ogy have been studying and analyzing personality, aiming to better understand such patterns that guide behavior. A model widely accepted to categorize personality traits is known as Big Five and uses the acronym OCEAN: Openness, Conscientiousness, Extroversion, Agreeableness and Neuroticism. On the other hand, new approaches that emerged from the field of computer vision allow to analyzing personality from visual data, making this new area of research quite attractive for researchers. This work presents an initial study of the use of the Transformer architecture to analyze personality traits, with a specific focus on extroversion, using digital videos of human faces. A literature review was carried out focusing on the application of computational techniques in this issue involving deep learning and Transformers. We also accomplished an experiment analysing Extroversion personality trait, as a starting point for our studies, using the ChaLearn dataset. An AUC (Area under the ROC Curve) value of 71.04% was obtained, with fine adjustment of parameters in the transformer, demonstrating the robustness of the proposed architectureen
dc.description.sponsorshipThis study was financed in part by the Coordination of Improvement of Higher Education Personnel - Brazil (CAPES) - Finance Code 001. The authors are grateful to the Renato Archer IT Center (CTI) Campinas, for its infrastructure support.en
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.citationJournal of WSCG. 2024, vol. 32, no. 1-2, p. 111-118.en
dc.identifier.doihttps://www.doi.org/10.24132/JWSCG.2024.12
dc.identifier.issn1213 – 6972
dc.identifier.issn1213 – 6980 (CD-ROM)
dc.identifier.issn1213 – 6964 (on-line)
dc.identifier.urihttp://hdl.handle.net/11025/57350
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.rights© Václav Skala - UNION Agencyen
dc.rights.accessopenAccessen
dc.subjectrozpoznání osobnostních rysůcs
dc.subjectmodel OCEANcs
dc.subjectovlivňování výpočetní technikycs
dc.subjectzpracování videacs
dc.subject.translatedpersonality trait recognitionen
dc.subject.translatedOCEAN modelen
dc.subject.translatedaffect computingen
dc.subject.translatedvideo processingen
dc.titleFirst Results on Using Transformer for Extroversion Personality Trait Recognitionen
dc.typečlánekcs
dc.typearticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersion

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Volume 32, number 1-2 (2024)