Personality prediction via multi-task transformer architecture combined with image aesthetics.
Social media has found its path into the daily lives of people. There are several ways that users communicate in which liking and sharing images stands out. Each image shared by a user can be analyzed from aesthetic and personality traits views. In recent studies, it has been proved that personality...
| Publicado en: | Digital Scholarship in the Humanities Vol. 39; no. 3; pp. 836 - 849 |
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| Autores principales: | , , , |
| Formato: | Artículo |
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Oxford University Press / USA
Sep2024
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=179512341&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 179512341 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 2055768X JEO9 jtl: Digital Scholarship in the Humanities issn: 2055768X maglogo: N pubinfo: dt: Sep2024 vid: 39 iid: 3 pid: 622 pub: Oxford University Press / USA artinfo: ui: 179512341 10.1093/llc/fqae034 ppf: 836 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.6MB tig: atl: Personality prediction via multi-task transformer architecture combined with image aesthetics. aug: au: Bajestani, Shahryar Salmani Khalilzadeh, Mohammad Mahdi Azarnoosh, Mahdi Kobravi, Hamid Reza affil: Department of Biomedical Engineering, Mashhad Branch, Islamic Azad University , Mashhad, Iran su: Transformer models Personality Databases Statistical correlation Social media sug: subj: Transformer models Personality Databases Statistical correlation Social media keyword: Big-5 image aesthetic assessment multi-task deep learning personality prediction Swin Transformer ab: Social media has found its path into the daily lives of people. There are several ways that users communicate in which liking and sharing images stands out. Each image shared by a user can be analyzed from aesthetic and personality traits views. In recent studies, it has been proved that personality traits impact personalized image aesthetics assessment. In this article, the same pattern was studied from a different perspective. So, we evaluated the impact of image aesthetics on personality traits to check if there is any relation between them in this form. Hence, in a two-stage architecture, we have leveraged image aesthetics to predict the personality traits of users. The first stage includes a multi-task deep learning paradigm that consists of an encoder/decoder in which the core of the network is a Swin Transformer. The second stage combines image aesthetics and personality traits with an attention mechanism for personality trait prediction. The results showed that the proposed method had achieved an average Spearman Rank Order Correlation Coefficient (SROCC) of 0.776 in image aesthetic on the Flickr-AES database and an average SROCC of 0.6730 on the PsychoFlickr database, which outperformed related SOTA (State of the Art) studies. The average accuracy performance of the first stage was boosted by 7.02 per cent in the second stage, considering the influence of image aesthetics on personality trait prediction. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 EADH: The European Association for Digital Humanities. item: Digital Scholarship in the Humanities holder: Oxford University Press / USA dt: @attributes: year: 2024 holdings: @attributes: islocal: N |
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