Profiling

Project Title
Development of a model for profiling the online behavior of adolescents and emerging adults in social networks and social media.

Project Goals
Analysis of the "online behavior" phenomenon and systematization of indicators of deviant online behavior of adolescents and young adults (including cyber-risky patterns) in social networks and social media.

Research objectives
1. Theoretical and methodological analysis and systematization of the terminology related to the virtual reality and cyber interaction. Description of the "online behavior" phenomenon, analysis of the ways of online self-presentation and online behavior patterns of adolescents and young adults in social networks and social media.
2. Indication of social and cyber-social risks and vulnerability factors affecting the formation of the behavior of adolescents and young adults (including deviant and cyber-risky) online behavior.
3. Description of methods and approaches to analyze and interpret text messages and other types of multimedia content.
4. Description of data analysis methods and methods of designing information systems for predicting risks of online behavior, as well as analyzing of the existing software that allows to monitor open information resources in order to predict deviant online behavior, including cyber-risky patterns.
5. Identification and description of indicators of deviant (including cyber-risky) online behavior of adolescents and young adults in social networks and social media.

Research site
Russian social networks, particularly “VKontakte”.

Research arrngement
Phase 1 (from February to December, 2019). Analysis of indicators of deviant (including cyber-risky) online behavior of adolescents and young adults in social networks and social media.
Stage 2 (from January to December, 2020). Elaboration of a model for profiling the online behavior of adolescents and young adults in social networks on the basis of the indicators of deviant (including cyber-risky) online behavior.
Stage 3 (from January to December, 2021). Designing of algorithms for psychological and psychosocial assistance to adolescents and young adults with deviant (including cyber-risky) online behavior in social networks and social media.

Study sample
Phase 1 (from February to December, 2019).
Pilot focus groups
1. The specifics of understanding normative behavior in social networks: 328 people (students of six faculties of Moscow State University of Psychology and Education in the first, second and third year of university, aged from 17 to 24 years).
2. Attitude towards cyberbullying among adolescents: 45 students of the 8th grade aged 13-15 years.
3. The tendency to aggression in adolescents and its signs (markers) in social media accounts: 70 adolescents (35 boys and 35 girls), pupils of the 8th grade (45 participants) and 9th grade (30 participants) aged 14 to 16 years.
4. Specificity of suicidal behavior of the underage in social networks and social media: 44 accounts (personal pages) in the Russian social network "Vkontakte" that belong to adolescents aged from 15 to 17 years; among them - 11 user accounts of non-committers (control group) and 33 user accounts of those, who committed suicide.
5. Individual characteristics and personal traits of people who commit sexual crimes against the underage using Internet: 44 indictments were brought against persons convicted under the 135th article of the Criminal Code of the Russian Federation, including the plot of criminal cases, correspondence materials, conclusions of forensic experts, psychiatrists, psychologists. The age of the victims ranges from 7 to 15 years. The age of the convicts is from 18 to 56, their education is no less than secondary level.
6. Specificity and psychological characteristics of the media content of the anime network subculture: 150 posts from two publics (one is in the social network Vkontakte and another - a specific channel in the «Telegram» messenger) which are united by a common anime topic.

Research methods
Theoretical analysis (including conceptual and categorical analysis), content analysis, focus groups, questionnaires, methods of mathematical statistics (prototypical analysis, Spearman's rank correlation coefficient, cluster analysis, T-test, Mann-Whitney test, Chi-Squared Test).

Research group members

Nikolay Dvoryanchikov

Elena Dozortseva

Irina Bovina

Elena Shpagina

Natalia Bogdanovich

Varvara Delibalt

Anastasia Kazina

Nikita Lavreshkin

T. Ruzyak

Elena Startseva

Larisa Larina

K. Efimochkina

Lev Kuravsky

Pavel Dumin

G. Yuriev

Olga Rubtsova

Tatiana Poskakalova

Antonina Drozdovskaya


 
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