Результаты исследований: Материалы конференций › материалы › Рецензирование
Deep Machine Learning Techniques in the Problem of Estimating the Expression of Psychological Characteristics of a Social Media User. / Хлобыстова, Анастасия Олеговна; Бушмелев, Федор Витальевич; Абрамов, Максим Викторович; Лившиц, Лев Павлович.
2023. 315-324 Работа представлена на Artificial Intelligence in Engineering and Science 2022, Ульяновск, Российская Федерация.Результаты исследований: Материалы конференций › материалы › Рецензирование
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TY - CONF
T1 - Deep Machine Learning Techniques in the Problem of Estimating the Expression of Psychological Characteristics of a Social Media User
AU - Хлобыстова, Анастасия Олеговна
AU - Бушмелев, Федор Витальевич
AU - Абрамов, Максим Викторович
AU - Лившиц, Лев Павлович
PY - 2023
Y1 - 2023
N2 - The problem solved in this article is to predict the expression of personality traits of a user, which can be obtained from the Life Style Index questionnaire, through the analysis of the graphical content published in his social media account. The proposed approach is to identify faces in photos from users’ accounts and use them to assess the expression of types of psychological defense. The proposed solution aims at testing the hypothesis that the presence of a face in the images and its position can contain the features sought. The essence of the proposed method consists in transfer training of a related model of a deep neural network for determination of emotions on pairs of faces contained in a digital image, and expressiveness of indicators of psychological defense mechanics. The accuracy of the predictions obtained with the new model when compared to the baseline is more than 2 times higher. Theoretical and practical significance lies in the fact that a new approach is formed, different from the known by the data involved in the analysis, and a neural network model is built, which allows to estimate the severity of psychological defenses of the user on the images published by him in social media, which indirectly in the future will allow to build estimates of the user protection from social engineering attacks.
AB - The problem solved in this article is to predict the expression of personality traits of a user, which can be obtained from the Life Style Index questionnaire, through the analysis of the graphical content published in his social media account. The proposed approach is to identify faces in photos from users’ accounts and use them to assess the expression of types of psychological defense. The proposed solution aims at testing the hypothesis that the presence of a face in the images and its position can contain the features sought. The essence of the proposed method consists in transfer training of a related model of a deep neural network for determination of emotions on pairs of faces contained in a digital image, and expressiveness of indicators of psychological defense mechanics. The accuracy of the predictions obtained with the new model when compared to the baseline is more than 2 times higher. Theoretical and practical significance lies in the fact that a new approach is formed, different from the known by the data involved in the analysis, and a neural network model is built, which allows to estimate the severity of psychological defenses of the user on the images published by him in social media, which indirectly in the future will allow to build estimates of the user protection from social engineering attacks.
KW - Artificial intelligence
KW - Image processing
KW - Information security
KW - Machine learning
KW - Personality traits
KW - Social engineering attacks
KW - Social media
KW - Transfer learning
UR - https://www.mendeley.com/catalogue/81a2e74b-aa21-349b-8d89-b14a2feb0ef6/
U2 - 10.1007/978-3-031-22938-1_22
DO - 10.1007/978-3-031-22938-1_22
M3 - Paper
SP - 315
EP - 324
Y2 - 15 November 2022 through 18 November 2022
ER -
ID: 99659622