enhanced personality detection system through user's digital footprints.
One of the most important aspects of any person's life is personality, which affects one's speech, decision, well-being, feeling and mental health. Personality detection is usually based on data collected by a questionnaire that comprises some critical problems such as the lack of direct access to t...
| Publicado en: | Digital Scholarship in the Humanities Vol. 36; no. 3; pp. 641 - 662 |
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| Autores principales: | , |
| Formato: | Artículo |
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Oxford University Press / USA
Sep2021
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| 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=153797198&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 153797198 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 2055768X JEO9 jtl: Digital Scholarship in the Humanities issn: 2055768X maglogo: N pubinfo: dt: Sep2021 vid: 36 iid: 3 pid: 622 pub: Oxford University Press / USA artinfo: ui: 153797198 10.1093/llc/fqaa070 ppf: 641 ppct: 21 formats: fmt: – @attributes: type: T – @attributes: type: P size: 899KB tig: atl: enhanced personality detection system through user's digital footprints. aug: au: Mobasher, Mohammad Farzi, Saeed affil: Department of Software Engineering, K. N. Toosi University of Technology , Tehran, Iran su: Digital footprint Personality Machine learning Information modeling Social networks Microblogs Ecological impact sug: subj: Digital footprint Personality Machine learning Information modeling Social networks Microblogs Ecological impact ab: One of the most important aspects of any person's life is personality, which affects one's speech, decision, well-being, feeling and mental health. Personality detection is usually based on data collected by a questionnaire that comprises some critical problems such as the lack of direct access to the individuals and explicit personal information. However nowadays, one of the valuable resources for such studies is social networks. The footprint and tracking of users on social networks have provided valuable information for personality recognition. Specifically, this research introduces an intelligence personality recognition system based on modeling user behavior using sophisticated features, i.e. Statistical, Emotional, and Linguistic. Furthermore, a dataset called KNTU_Personality based on the MBTI personality model with the profile information and tweets has been collected. The experimental study follows two scenarios with complementing objectives. First the sensitivity analysis is performed respecting to setting parameters, introduced features and different learning algorithms. Next the proposed system has been compared with well-known personality detection systems. The results demonstrate the superiorities of the proposed system regarding its counterparts in terms of F-Score, Precision, Recall and Accuracy. 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: 2021 holdings: @attributes: islocal: N |
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