ISSN 2079-6617 (Print)
ISSN 2309-9828 (Online)
Ru | En
Russian Psychological Society
The Faculty of Psychology. Lomonosov Moscow State University.
Main RSS Search

MainArticlesVolumes

Shaigerova L.A., Shilko R.S., Vakhantseva O.V., Zinchenko Yu.P. (2019). Outlook of using social network analysis to study ethnocultural identity in adolescents in online communities. National Psychological Journal, [Natsional’nyy psikhologicheskiy zhurnal], (12) 3, 4–16.

Abstract

Background. The life of modern adolescents is inseparable from online communities that are not only means of communication and source of information, but they also mediate the development of interpersonal and intergroup attitudes, the process of socialization and shape identity. The study of the processes in online communities helps to determine the influence of digital society on the formation of ethnocultural identity and the risks of its negative transformations, the emergence and spread of negative attitudes, xenophobia, and intergroup hostility. Social Network Analysis (SNA), widely used in a number of disciplines but still rarely used in psychological research, may provide new opportunities to explore these processes in online communities.

Objective. The research was aimed at examining the possibilities of applying social network analysis to the study of ethnocultural identity of Russian adolescents.

Design. By creating a code in the language R (R 3.6.1 + R Studio 1.2.1335), the analysis of the relations of a number of communities of the social network «Vkontakte», whose content is relevant to various aspects of ethnocultural (ethnic, cultural, religious, regional, national) identity was performed. In these communities Moscow and St. Petersburg dwellers aged 14 to 18 years were identified and sampled (78,784 Moscow-based users and 210,815 St. Petersburg-based users). Based on the results, social graphs were constructed and the analysis of relations between communities in the two cities of Russia was carried out.

Results. The general tendencies and differences between the links of online communities, the content of which is relevant to various aspects of ethnocultural identity in the cities of Russia under consideration, are revealed. For the target category, Moscow-based and St. Petersburg-based user-adolescents, the online communities were considered to be most relevant between those with ethnic content. The differences relate to connexions between large community called «Russia» and other studied online communities. There is no connexion between all other communities from Moscow with community «Russia» while adolescents-users from St. Petersburg actively participate in the community «Russia», especially those who are in communities whose content is devoted to ethnic and cultural issues.

Conclusion. The results show the existing outlooks for the social networks analysis, which allows to cover a wide range of users of online communities, for the study of ethnocultural identity of adolescents in the digital society. Obtained by analyzing social networking data derived from user activity in Internet communities, reflect the regularities, identified through an earlier social-psychological study involving adolescents who live in the same area. The socio-cultural context mediates online identity and offline identity in a similar way, which is confirmed by the revealed differences in the connections of online communities in different subjects of the Russian Federation. Despite the long-term social network analysis in sociology and other sciences, psychology is using this method as exploratory tool. In relation to the study of ethnocultural identity and related phenomena SNA requires additional development based on the interdisciplinary interaction of various sciences and areas and the necessary comparison of the results with the results obtained by other methods.

Received: 09/16/2019
Accepted: 09/21/2019
Pages: 4-16
DOI: 10.11621/npj.2019.0302

By: ; ; ; ;

Sections: Psychology of virtual reality;

PDF: /pdf/npj-no35-2019/npj_no35_2019_004-016.pdf

Keywords: social network analysis (SNA); social graphs; adolescents; ethno­cultural identity; regions of Russian Federation; social mining;

Available Online 20.10.2019

Acknowledgements

The research was supported by the Russian Science Foundation (project No 15-18-00109).

Fig 1. Relations between communities of the VKontakte network in Moscow (relative)


Fig 2. Relations between communities of the VKontakte network in St.-Petersburg (relative)

Table 1. Samples by thematic component

Main content of communities (aspect of ethnocultural identity)

Community

Regional

My Moscow,

My Moscow. I love my city

St. Petersburg is my city! | Piter | SPB

Religious

Islam,

I love Islam

I'm a Christian,

I believe † Orthodoxy

Cultural

Moscow: History of Moscow,

Saint Petersburg | History of Pieter

Ethnical

I’M RUSSIAN

I AM RUSSIAN

Civilian

RUSSIA


Table 2. Community activity in Moscow and St. Petersburg based on the recent 300 posts

Community

Activity Indicators

Community size (total), prns

Community size (adolescents), prns

Posts per day, N

Likes Median, N

Comments Median, N

My Moscow

214612

4865

0.29

117

1

My Moscow. I love my city

268156

22802

0.43

2

0

St. Petersburg is my city!

575554

13107

0.07

1019

8

Islam

438618

33747

2.78

321.5

3.5

I’m Christian

29898

2469

0.1

332

0

I love Islam

519514

28840

1.47

460.5

0

I believe + Orthodoxy

1782079

51426

14.29

1792.5

0

Moscow: History of Moscow

84902

3903

0.52

88

1

Saint Petersburg | History of Piter

113660

4877

0,52

91.5

3

I’M RUSSIAN

282367

11608

10

104

1

I AM RUSSIAN

84264

868

0,68

46.5

2.5

RUSSIA

761065

284889

5,26

1595.5

31


References:

Alhajj R., & Rokne J. (Eds.) (2018). Encyclopedia of Social Network Analysis and Mining. Second Edition. New York: Springer. doi: 10.1007/978-1-4939-7131-2

Barbier, Geoffrey & Liu, Huan. (2011). Data Mining in Social Media. doi: 10.1007/978-1-4419-8462-3_12.

Barak, A., & Suler, J. (2012). Reflections on the psychology and social science of cyberspace In A. Barak (Ed.) Psychological aspects of cyberspace. Theory, research, applications. Cambridge, UK: Cambridge University Press, 1–12. doi: 10.1017/CBO9780511813740.002

Barassi, V. (2017). Digital citizens? Data traces and family life. Contemporary Social Science, 12(1–2), 84–95. doi: 10.1080/21582041.2017.1338353

Bennett, C., Ryall, J., Spalteholz, L., Gooch, A. (2007). The aesthetics of graph visualization. In S. N. Spencer (Ed.), Proceedings of computational aesthetics in graphics, visualization, and imaging. New York, NY: Association for Computing Machinery, 57–64.

Bhui, K., & Ibrahim, Y. (2013). Marketing the “radical”: Symbolic communication and persuasive technologies in jihadist websites. Transcultural Psychiatry, 50(2), 216–234. doi: 10.1177/1363461513479329

Bouvier G. (2012). How Facebook users select identity categories for self-presentation. Journal of Multicultural Discourses, 7(1), 37–57. doi: 10.1080/17447143.2011.652781

Bouvier, G. (2015). What is a discourse approach to Twitter, Facebook, YouTube and other social media: connecting with other academic fields? Journal of Multicultural Discourses, 10(2), 149–162. doi: 10.1080/17447143.2015.1042381

Butts, C.T. (2008). Social network analysis: A methodological introduction. Asian Journal of Socail Psychology, 11, 13–41. doi: 10.1111/j.1467-839X.2007.00241.x

Butts, C.T., & Pixley, J.E. (2004). A structural approach to the representation of life history data. Journal of Mathematical Sociology, 28(2), 81–124. doi: 10.1080/00222500490448208

Can, U., & Alatas, B. (2019). A new direction in social network analysis: Online social network analysis problems and applications. Physica A: Statistical Mechanics and its Applications, 535, 122372. doi: 10.1016/j.physa.2019.122372.

Cheung, M.W.-L., & Jak S. (2016). Analyzing Big Data in Psychology: A Split/Analyze/Meta-Analyze Approach. Frontiers in Psychology, 8, 738. doi: 10.3389/fpsyg.2016.00738

Dubrovina I.V. (2018). Psychological issues of education of kindergarten children and school children in the information society. National Psychological Journal, 11(1), 6-16. doi: 10.11621/npj.2018.0101

Emelin V.A. (2018). Cyberculture and network libertarianism. National Psychological Journal, 11(3), 3-11. doi: 10.11621/npj.2018.0301

Freeman, L.C. The Development of Social Network Analysis. Vancouver: Empirical Press, 2004.

Goriunova, O. (2019). The Digital Subject: People as Data as Persons. Theory, Culture & Society. DOI: 10.1177/0263276419840409

Hogan, M., & Strasburger, V.C. (2018). Social Media and New Technology: A Primer. Clinical Pediatrics, 57(10), 1204–1215. doi: 10.1177/0009922818769424

Jackson, L.A., & Wang, J.-L. (2013). Cultural differences in social networking site use: A comparative study of China and the United States. Computers in Human Behavior, 29, 910921. doi: 10.1016/j.chb.2012.11.024

Jacomy, M., Venturini, T., & Heymann, S., Bastian, M. (2014). ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software. PLoS One, 9, e98679. doi: 10.1371/journal.pone.0098679

Karpov D.V. (2017). The Theory of Earls. St. Petersburg, Retrieved from: https://logic.pdmi.ras.ru/~dvk/graphs_dk.pdf. (accessed: 02.09.2019).

Kim, J., Lee, J.-E.R. (2011). The Facebook paths to happiness: Effects of the number of Facebook friends and self-presentation on subjective well-being. Cyberpsychology, Behavior, and Social Networking, 14, 359364. doi: 10.1089/cyber.2010.0374

Kirmayer, L.J., Raikhel, E., & Rahimi, S. (2013). Cultures of the Internet: Identity, community and mental health. Transcultural Psychiatry, 50(2), 165–191. doi: 10.1177/1363461513490626

Kolesnikov V.N., Melnik Yu.I., & Teplova L.I. (2019). Internet activity and problem use of the Internet in youth. National Psychological Journal, 33(1), 34–46. doi: 10.11621/npj.2019.0104

Kurnosova, E. (2019). Social networks in numbers. Retrieved from https://mediascope.net/upload/iblock/f97/18.04.2019_Mediascope_Екатерина%20Курносова_РИФ+КИБ%202019.pdf. (accessed: 02.09.2019).

Lee, G., Lee, J., & Kwon, S. (2011). Use of social-networking sites and subjective well-being: A study in South Korea. Cyberpsychology, Behavior and Social Networking, 14, 151155doi: 10.1089/cyber.2009.0382

Makri, K., & Schlegelmilch, B.B. (2017). Time orientation and engagement with social networking sites: A cross-cultural study in Austria, China and Uruguay. Journal of Business Research, 80, 155163. doi: 10.1016/j.jbusres.2017.05.016

McGrath, C., Blythe, J., & Krackhardt, D. (2014). Visualizing multiple levels and dimensions of social network properties. In: W. Huang (Ed.), Handbook of human centric visualization. New York, NY: Springer, 513–525. doi: 10.1007/978-1-4614-7485-2_20

Mcguire H.A., Markus M.J., Kionga-Kamau P.M., & Smith B.N. (2013). Social network analysis. Google Patents.

Molchanov S.V., Almazova O.V., & Poskrebisheva N.N. (2018). Cognitive methods of processing social information on the Internet in adolescence. National Psychological Journal, 11(3), 57–68. doi: 10.11621/npj.2018.0306

Montgomery, K.C., Chester, J., & Milosevic, T. (2017). Children’s privacy in the big data era: Research opportunities. Pediatrics, 140(2), 117–121. doi:  10.1542/peds.2016-17580

Most Popular Social Networks Worldwide as of 2019, ranked by number of active users (in millions). Retrieved from: https://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users. (accessed: 02.09.2019).

Nestik, T.A. (2017). Development of digital technologies and the future of psychology (in Russian). [Vestnik Moskovskogo Regional’nogo gosudarstvennogo universiteta]. Series "Psychological science, 3, 6–15. doi: 10.18384/2310-7235-2017-3-6-15

Park Y.J., Chung J.E., & Shin D.H. (2018). The Structuration of Digital Ecosystem, Privacy, and Big Data Intelligence. American Behavioral Scientists, 62(10), 1319–1337. doi: 10.1177/0002764218787863

Sampasa-Kanyinga, H., & Lewis, R.F. (2015). Frequent use of social networking sites is associated with poor psychological functioning among children and adolescents. Cyberpsychology, Behavior, and Social Networking, 18, 380385. doi: 10.1089/cyber.2015.0055

Schneider F., Feldmann A., Krishnamurthy B., & Willinger W. (2009). Understanding online social network usage from a network perspective. Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement. Chicago, Illinois, USA. doi: 10.1145/1644893.1644899

Shilko, R., Shaigerova, L., Dolgikh, A., Vakhantseva, O., Almazova, O., Zinchenko Yu. (2019). Connection between the amount of time spent by Russian teenagers on the Internet and their psychological well-being. European Psychiatry, 56(S1), 208–208.

Sobkin V.S., & Fedotova A.V. (2018). Adolescent in social networks: on the issue of social psychological well-being. National Psychological Journal, 11(3), 23–30. doi: 10.11621/npj.2018.0303

Soldatova G.U.  (2017). Digital generation, or the Main humanitarian challenge for adults in the 21st century. [Akademicheskiy vestnik. Nauchno-prakticheskiy zhurnal Akademii sotsial'nogo upravleniya], 3(25), 3–6.

Soldatova G.U., & Olkina O. (2016). 100 friends. Circle of communication of teenagers in social networks. [Deti v informatsionom obschestve], 24, 24–33.

Soldatova G.U., & Teslavskaya O.I. (2018). Interpersonal relations of Russian adolescents in social networks. National Psychological Journal, 11(3), 12–22. doi: 10.11621/npj.2018.0302

Starkey, L., Eppel, E.A., & Sylvester, A. (2018). How do 10-yearold New Zealanders participate in a digital world? Information, Communication & Society. doi:10.1080/1369118X.2018.1472795

Tang L., & Liu H. (2010). Graph mining applications to social network analysis. Managing and Mining Graph Data. Advances in Database Systems, 40. doi: 10.1007/978-1-4419-6045-0_16.

The Top 20 Valuable Facebook Statistics – Updated 2019. Retrieved from: https://zephoria.com/top-15-valuable-facebook-statistics. (accessed: 02.09.2019).

Valkenburg, P.M., Peter, J. (2008). Adolescents’ identity experiments on the internet: Consequences for social competence and self-concept unity. Communication Research, 35(2), 208–231. doi: 10 1177/0093650207313164

van der Merwe, P. (2017). Adolescent identities in the cyberworld. Journal of Psychology in Africa, 27(2), 203–207. doi: 10.1080/14330237.2017.1303129

van Kokswijk, J. (2008). Granting personality to a virtual identity. International Journal of Humanities and Social Science, 2(4), 207–215.

Vanman, E.J., Baker, R., Tobin, S.J. (2018). The burden of online friends: the effects of giving up Facebook on stress and well-being. The Journal of Social Psychology, 158(4), 496–507. doi: 10.1080/00224545.2018.1453467

Yousefi Nooraie, R., E.M. Sale, J., Marin, A., Ross, L.E. (2018). Social Network Analysis: An Example of Fusion Between Quantitative and Qualitative Methods. Journal of Mixed Methods Research. doi: 10.1177/1558689818804060.

Zinchenko Yu.P. (Ed.) (2017). Russian identity. Psychological well-being. Social stability. Monograph. Moscow, Izdatel’stvo Moskovskogo Universiteta. 520.

Zinchenko Y.P., Shaigerova L.A., & Shilko R.S. Methodological problems of studying the ethno-cultural identity of children and teenagers in the digital society (In press).

Zinchenko Yu.P., Shaigerova L.A., Shilko R.S., Dolgikh A.G., & Vakhantseva O.V. (2018). Study of the identity of adolescents brought up in a modern Russian family: the possibility of in-depth analysis of data (data mining). In Eds. O.A. Karabanova, & N.N. Vasyagina, [Psikhologicheskie problemy sovremennoy sem'i: sbornik materialov VIII Mezhdunarodnoy nauchno-prakticheskoy konferentsii 3-6 oktyabrya 2018 goda]. Yekaterinburg: Ural’skiy gosudarstvennyy pedagogicheskiy universitet, 14–25.

For citing this article:

Shaigerova L.A., Shilko R.S., Vakhantseva O.V., Zinchenko Yu.P. (2019). Outlook of using social network analysis to study ethnocultural identity in adolescents in online communities. National Psychological Journal, [Natsional’nyy psikhologicheskiy zhurnal], (12) 3, 4–16.

About Editorial Board Volumes Authors For Authors Indexing Contacts
CC BY-NC

National Psychological Journal, 2006 - 2020