Abstract. 

The article discusses the problem of developing a unified approach to the creation of social network users typology. Based on the analysis of the dynamics of the typology criteria, the evolution of approaches from the indicator « frequency of visits» to the «analysis of social action» is shown. The most well-known, most frequently cited schemes in the scientific literature are analyzed, the sets of criteria underlying them are investigated. Due to the inconsistency and often conflict of classification parameters, the lack of a unified terminology, etc. proposed an approach based on a fundamental change in user practices in the context of the network society. Their behavioral strategies determine various communicative types of behavior that allow structuring the space of the user of social networks within the paradigm of network interaction. The first section of the article discusses and compares the most famous and cited typologies of social media users over the past decade and a half. The second part analyzes an attempt to build a universal meta-typology of users, which hardly managed to get rid of the shortcomings of the previous stage. Finally, the third chapter proposes a typology that takes into account the various social actions of users that manifest themselves in different communication strategies.

Keywords: 

Digital civic science, online communities, networked human capital, networked communication, informatics of communities.

PP. 99-111.

DOI: 10.14357/207902792304011 

EDN: OZRJSU

 

References

1. Nielsen J. The 90-9-1 Rule for Participation Inequality in Social Media and Online Communities. 2006 // Nielsen Norman Group at

https://www.nngroup.com/articles/participationinequality/ (Дата доступа 19.06.2023)

2. McQuail D. McQuails’s mass communication theory (4th ed.). London: New Delhi: Sage Publications. 2000.

3. Leshchenko A.M. Social networks as a mechanism for constructing communication in modern society. PhD Thesis. Saint Petersburg: SPSU. 2011. 272 p. (In Russ.).

4. Johnson G.M., Kulpa A. Dimensions of online behavior: Toward a user typology. CyberPsychology & Behavior. 2007. 10(6):773-780.

5. Barnes S.J., Bauer H.H., Neumann M.M., & Huber F. Segmenting cyberspace: a customer typology for the internet. European journal of marketing. 2007. 41(1/2):71-93.

6. Ryabikina Z.I., Bogomolova E.I. The relationship of personal characteristics of the social networks users with the peculiarities of their activity in the network // Scientific journal of KubSAU. 2015. 109(05):1 - 17. (In Russ.).

7. Shchebetenko S.A. Big five personality traits and user activity in the VKontakte social network // Psychology. Psychophysiology. 2013.6(4):73-83. (In Russ).

8. Stankevich M.A., Smirnov I.V., Ignatiev N.A., Kiselnikova N.V., Danina M.M. Analysis of personality traits of social network users based on automatic processing of their profiles // Systems of High Availability. 2018.14 (4):15. (In Russ).

9. Lazutkina E.V. The main forms of information manipulation in Runet social media / Znak: problematic field of media education. 2017.2 (24):221–225. (In Russ).

10. Gorelova G.G., Inozemtsev D.V. Analysis of psychological well-being based on the parameters of the behavioral activity of social networks users // Uchenye zapiski universiteta im. PF Lesgaft. 2020.2(180):489-494. (In Russ).

11. Kmet E.B. Identification of behavioral categories of social network users as a basis for developing a content strategy //Practical Marketing. 2015.7 (221):9-15. (In Russ).

12. Subjectivity and viability of network communities in the discursive space of the Internet / Ed. A.N. Voronin. M.:Publishing house “Institute of Psychology of the Russian Academy of Sciences”. 2021:373. (In Russ)

13. Mishlanov V.A., Chuganskaya A.A., Smirnov I.V., Suvorova M.I., Kuruzov I.A. Development of methods for analyzing behavior scenarios (based on instructive Internet texts) // Medialinguistics. 2020.7(1);16-28. (In Russ.)

14. Latyshev A.V., Talalaev A.A., Fralenko V.P., Khachumov V.M., Khachumov M.V. Methods for assessing personal factors based on visual information published in social networks (review)// World of Science. Pedagogy and psychology. 2019.7(1):17. (In Russ)

15. Muller M., N.S. Shami, D.R. Millen, and J. Feinberg. “We are all lurkers: consuming behaviors among authors and readers in an enterprise file-sharing service”. In proc. 16th ACM international conference on Supporting group work. 2010.201–210.

16. Brandtzaeg P.B., and J. Heim. “A typology of social networking sites users”, International Journal of Web Based Communities 2011.7(1):28–51.

17. Constantinides E., Zinck Stagno M.C. Potential of the social media as instruments of higher education marketing: A segmentation study //Journal of marketing for higher education. 2011.21(1):7-24.

18. Alarcón-del-Amo M.D.C., Lorenzo-Romero C., & Gómez-Borja, M.Á. Classifying and profiling social networking site users: A latent segmentation approach. Cyberpsychology, behavior, and social networking. 2011.14(9):547-553.

19. Budak C., Agrawal D., El Abbadi A. Structural trend analysis for online social networks. In:Proceedings of the VLDB Endowment. 2011.4(10):646-656.

20. Mathioudakis M. and Koudas N. Twitter Monitor: Trend detection over the Twitter stream. In Proceedings of SIGMOD’2010.

21. Bezzubtseva A., and D.I. Ignatov. “A Typology of Collaboration Platform Users”. In Workshop on Experimental Economics in Machine Learning. 2012.9–19.

22. Shao W., Ross M., Grace D. Developing a motivation-based segmentation typology of Facebook users. Marketing Intelligence & Planning. 2015.

23. Belenioti Z.Ch., Andronikidis A., Vassiliadis Ch. Classifying and profiling social media users: an integrated approach. In: Second European Conference on Media & Mass Communication, IAFOR, 13-16 July 2015. Thistle Brighton. United Kingdom.

24. Schwade F., Schubert P. Developing a user typology for the analysis of participation in enterprise collaboration systems. Proceedings of the 52nd Hawaii International Conference on System Sciences. 2019.

25. Selwyn N., Gorard S., Furlong J. Whose Internet is it anyway? Exploring adults (non)use of the internet in everyday life. European Journal of Communication. 2005.20(1).

26. Dervin B. Human studies and user studies: A call for methodological interdisciplinarity. Information Research. 2003.9(1):166. https://informationr.net/ir/9-1/paper166.html (accessed: 06.06.2023).

27. Brandtzæg P.B. Towards a unified Media-User Typology (MUT): A meta-analysis and review of the research literature on media-user typologies. Computers in Human BehaviorVolume 2010. (26):940–956 https://doi.org/10.1016/j. chb.2010.02.008

28. Tishchenko V.I. Digital space of personality. Proceedings of the Institute for System Analysis. 2022.72(4):51-61 (In Russ).

29. Veber M. Economy and society: essays of understanding sociology. Economic sociology. 2016.(5). URL: https://cyberleninka.ru/

article/n/hozyaystvo-i-obschestvo-ocherkiponimayuschey-sotsiologii (accessed: 06.06.2023). (In Russ.)

30. Ellison N.B., Steinfield C., Lampe C. Connection strategies: Social capital implications of Facebook-enabled communication practices. New media & society. 2011.13(6):873-892.

31. Boyd D.M., Ellison N.B. Social network sites: Definition, history, and scholarship //Journal of computer‐mediated Communication. 2007.13(1):210-230.

32. Ramirez Jr.A., Walther J.B., Burgoon J.K., & Sunnafrank M. (2002). Information-seeking strategies, uncertainty, and computer-mediated communication: Toward a conceptual model. Human communication research. 2002.28(2):213-228.