DOI: 10.18413/2518-1092-2023-8-4-0-6

DEVELOPMENT OF MACHINE LEARNING METHODS AND A LIBRARY OF INTERPRETABLE PREDICTIVE MODELING OF HUMAN BEHAVIOR DURING HIS ONLINE PROFILING

Ivan Zakharovich Smirnov
Anatoly Andreevich Medvedev
Timur Ruslanovich Samigulin
Alena Alekseevna Komarova
Artyom Igorevich Timoshchuk-Bondar
Mikhail Vitalievich Sinko
Anastasia Alexandrov Laushkina
Olga Olegovna Goffman
Oleg Olegovich Basov

The study of individual psychological characteristics of people is important in the areas of education, management and administration, ensuring the safety of individuals and communities. There are various tools for solving the problem of determining and analyzing personal characteristics, but they have a number of limitations. We present a solution that extracts and uses machine learning to analyze human facial and speech features from video footage, applicable to the study of eight different individual psychological characteristics in an online digital profiling task. The user is invited to use the developed Expert library to obtain new characteristics by applying and combining existing ML modules to solve a wide class of problems.

Keywords: machine learning, open source, multimodal analysis, verbal and non-verbal signs.

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Smirnov I.Z., Medvedev A.A., Samigulin T.R., Komarova A.A., Timoshchuk-Bondar A.I., Sinko M.V., Laushkina A.A., Goffman O.O., Basov O.O. Development of machine learning methods and a library of interpretable predictive modeling of human behavior in the process of online profiling // Research result. Information technologies. – Т. 8, №4, 2023. – P. 59-69. DOI: 10.18413/2518-1092-2023-8-4-0-6

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