Metrics for Personal Profiles of Social Network Users

This paper discusses the technical details of obtaining and processing data to determine a set of characteristics of texts from social networks, genre preferences in movies and music genres for students of Kazan Federal University who have different academic performance (successful, average, not-suc...

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Bibliographic Details
Published in:SHS web of conferences 2020, Vol.79, p.1012
Main Authors: Nikolaev, Konstantin Sergeevich, Gafarov, Fail Mubarakovich, Ustin, Pavel Nikolaevich
Format: Article
Language:English
Subjects:
Social networks
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Summary:This paper discusses the technical details of obtaining and processing data to determine a set of characteristics of texts from social networks, genre preferences in movies and music genres for students of Kazan Federal University who have different academic performance (successful, average, not-successful). The selection of such characteristics is carried out using machine learning methods (Word2Vec, tSNE). The data obtained is used in the development of a functional psychometric model of cognitive behavioral predictors of an individual’s activity within the framework of their educational activities. We also developed a web application for visualizing the obtained data using the Flask engine.
ISSN:2261-2424
2416-5182
2261-2424
DOI:10.1051/shsconf/20207901012