Artificial Intelligence and Decision Making
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Artificial Intelligence and Decision Making, 2019, Issue 4, Pages 29–36
DOI: https://doi.org/10.14357/20718594190404
(Mi iipr186)
 

Data mining

Predicting personal traits from VKontakte images

N. A. Ignatieva, M. A. Stankevichb, N. V. Kisel'nikovac, O. G. Grigorievb

a Peoples' Friendship University of Russia named after Patrice Lumumba, Moscow, Russia
b Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow, Russia
c RAE Psychological Institute, Moscow, Russia
Abstract: The psychometric analysis of information from the Internet is one of the fastest growing trends in modern research. Using social networks, one can identify psychological characteristics and mental disorders. In this paper, we solve the problem of identifying personal qualities – predictors of depression among users of the social network VKontakte, analyzing the images published by them. We describe our methods and approaches for solving this problem and present the results of experimental verification on Vkontakte data. Our study shows that you can use object detection methods to create effective features for predicting personality traits.
Keywords: personality traits, social media, image recognition, machine learning.
Funding agency Grant number
Ministry of Science and Higher Education of the Russian Federation 05.604.21.0226
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: N. A. Ignatiev, M. A. Stankevich, N. V. Kisel'nikova, O. G. Grigoriev, “Predicting personal traits from VKontakte images”, Artificial Intelligence and Decision Making, 2019, no. 4, 29–36
Citation in format AMSBIB
\Bibitem{IgnStaKis19}
\by N.~A.~Ignatiev, M.~A.~Stankevich, N.~V.~Kisel'nikova, O.~G.~Grigoriev
\paper Predicting personal traits from VKontakte images
\jour Artificial Intelligence and Decision Making
\yr 2019
\issue 4
\pages 29--36
\mathnet{http://mi.mathnet.ru/iipr186}
\crossref{https://doi.org/10.14357/20718594190404}
\elib{https://elibrary.ru/item.asp?id=41800538}
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  • https://www.mathnet.ru/eng/iipr/y2019/i4/p29
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