Features of the Digital Behavior of Users with Social Media Addiction | Vestnik Tomskogo gosudarstvennogo universiteta – Tomsk State University Journal. 2021. № 467. DOI: 10.17223/15617793/467/13

Features of the Digital Behavior of Users with Social Media Addiction

The aim of this study was to analyze the features of digital behavior of VKontakte users with varying degrees of severity of social networking addiction. Social networking addiction is a behavior addiction which was found to be related to depression, anxiety, loneliness, ADHD, fear of missing out, and a number of behavioral impairments. The study was conducted on 345 social networks users from Russia. Among them, 95 participants provided a link to their VKontakte profiles for the purposes of further content analysis. Participation in the study was voluntary, no rewards for participation were expected. The severity of social networking addiction was measured with the Bergen Social Media Addiction Scale (BSMAS) modified by C.S. Andreasse and colleagues. The scale contains 6 items related to 6 dependency parameters: Salience, Craving/Tolerance, Mood Modification, Relapse/Loss of Control, Withdrawal, and Conflict/Functional Impairment. The scale was adapted and translated into Russian for the purposes of this study. Data on the features of digital behavior was collected using content analysis. The information was obtained through the VKontakte API - an interface for accessing vk.com databases using HTTP requests. To export the data, a special VK library was used. Having downloaded the list of identifiers of 95 users, we received the following data in a machine-readable format: the number of friends in the profile, the number of subscribers, the type of account (closed/opened), the presence/absence of a completed status. The whole algorithm was implemented in the Python 3 programming language. The profile picture type was defined “manually”. The pictured were divided into two types: photographs that supposedly depict the user (portraits) and other images (drawings and illustrations without a person). To testify the reliability of the adapted scale, Cronbach’s a method was applied. The Shapiro-Wilk test was used to test the normality of distribution of the Bergen Social Media Addiction Scale. Kendall’s correlation coefficient was applied to testify the correlational research hypotheses, while Wilcoxon’s test was applied to testify hypotheses about differences between independent groups of users. The analysis revealed that higher levels of addiction is positively correlated with the number of friends on the profile and the frequency of social media use. We also found that such behavioral characteristics as hiding profile information, using a third-party image as an “avatar”, filling in the “status” column, agreeing to share a link to a profile to participate in the study, as well as the number of subscribers, are not related to the severity of social media addiction. Practical applicability, limitations, and directions for future researches were discussed.

Download file
Counter downloads: 69

Keywords

social media, digital behavior, social media addiction, internet addiction, content analysis

Authors

NameOrganizationE-mail
Alekseev Gleb A.Higher School of Economicsglebsseriousacc@gmail.com
Dyuldenko Aleksandr A.Kriptonite; Higher School of Economics2017126@mail.ru
Всего: 2

References

Kemp S. Digital 2019: Essential insights into how people around the world use the internet, mobile devices, social media, and E-commerce // We are Social. 2019. С. 1-221.
Song H. et al. Does Facebook make you lonely?: A meta analysis // Computers in Human Behavior. 2014. Vol. 36. P. 446-452.
Marino C. et al. A comprehensive meta-analysis on problematic Facebook use // Computers in Human Behavior. 2018. Vol. 83. P. 262-277.
Huang C. Time spent on social network sites and psychological well-being: A meta-analysis // Cyberpsychology, Behavior and Social Networking. 2017. Vol. 20, № 6. P. 346-354.
Regier D.A., Kuhl E.A., Kupfer D.J. The DSMD5: Classification and criteria changes // World psychiatry. 2013. Vol. 12, Is. 2. P. 92-98.
Griffiths M.D. et al. The evolution of Internet addiction: A global perspective // Addictive behaviors. 2016. Vol. 53. P. 193-195.
Yang S.C., Tung C.J. Comparison of Internet addicts and non-addicts in Taiwanese high school // Computers in human behavior. 2007. Vol. 23, Vol. 1. P. 79-96.
Griffiths M.D. Social networking addiction: Emerging themes and issues // Journal of Addiction Research & Therapy. 2013. Vol. 4, № 5.
Young K.S. The research and controversy surrounding internet addiction // CyberPsychology & Behavior. 1999. Vol. 2, Is. 5. P. 381-383.
Griffiths M.A. ‘Components’ model of addiction within a biopsychosocial framework // Journal of Substance use. 2005. Vol. 10, Is. 4. P. 191-197.
Lin L.Y. et al. Association between social media use and depression among US young adults // Depression and anxiety. 2016. Vol. 33, Is. 4. P. 323-331.
Andreassen C.S. et al. The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study // Psychology of Addictive Behaviors. 2016. Vol. 30, Is. 2. P. 252.
Settanni M. et al. The interplay between ADHD symptoms and time perspective in addictive social media use: a study on adolescent Facebook users // Children and Youth Services Review. 2018. Vol. 89. P. 165-170.
Blackwell D. et al. Extraversion, neuroticism, attachment style and fear of missing out as predictors of social media use and addiction // Personality and Individual Differences. 2017. Vol. 116. P. 69-72.
Bozoglan B., Demirer V., Sahin I. Loneliness, self Desteem, and life satisfaction as predictors of Internet addiction : A cross D sectional study among Turkish university students // Scandinavian journal of psychology. 2013. Vol. 54l, Is. 4. P. 313-319.
Hunt M.G. et al. No more FOMO : Limiting social media decreases loneliness and depression // Journal of Social and Clinical Psychology. 2018. Vol. 37, Is. 10. P. 751-768.
Щекотин Е.В., Мягков М.Г., Гойко В.Л., Кашпур В.В., Коварж Г.Ю. Субъективная оценка (не) благополучия населения регионов РФ на основе данных социальных сетей // Мониторинг общественного мнения : Экономические и социальные перемены. 2020. № 1. С. 78116. DOI: 10.14515/monitoring.2020.1.05.
 Features of the Digital Behavior of Users with Social Media Addiction | Vestnik Tomskogo gosudarstvennogo universiteta – Tomsk State University Journal. 2021. № 467. DOI: 10.17223/15617793/467/13

Features of the Digital Behavior of Users with Social Media Addiction | Vestnik Tomskogo gosudarstvennogo universiteta – Tomsk State University Journal. 2021. № 467. DOI: 10.17223/15617793/467/13

Download full-text version
Counter downloads: 478