Advertisement

Is Cross-Network Segregation a Factor of Political Behavior and Political Identification in the Russian Student Community?

  • Denis Martyanov
  • Galina LukyanovaEmail author
  • Oleg Lagutin
Conference paper
  • 206 Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 1038)

Abstract

Online segregation is among the most commonly discussed phenomenon. This paper calls into question the need to focus on the dangers of echo chambers, filter bubbles; furthermore, it proposes to identify latent factors of the Internet segmentation and specify communication in homophilic communities. Thus, the current study aims to detect the mutual influence of social network choice and political behavior among Russian students. The study is based on empirical data obtained by a survey conducted in 2018 in St. Petersburg. Our research has revealed that students are a heterogeneous group. The identified four factors described as “Web-services for full-grown people,” “Mobile services,” “Closed silo of content,” “Audiovisual services” disclose hidden relationships between quite different online services and political identification of students.

Keywords

Social networks Cyberspace fragmentation Political behavior Political identity Cross-network segregation 

Notes

Acknowledgments

For the empirical part, we utilized facilities provided by the Center for Sociological and Internet Research at Saint-Petersburg State University (project 106-9131 “The factors of absenteeism development among students in a Russian metropolis (as in the example of St. Petersburg)”). The theoretical part of the reported study was funded by RFBR and EISR according to the research project № 19-011-31551 “Manageability and discourse of virtual communities in the context of post-factual politics”.

References

  1. 1.
    Bodrunova, S., Litvinenko, A.: Fragmentation of society and media hybridisation in today’s Russia: how Facebook voices collective demands. J. Soc. Policy Stud. 14(1), 113–124 (2016)Google Scholar
  2. 2.
    Boutyline, A., Willer, R.: The social structure of political echo chambers: variation in ideological homophily in online networks. Polit. Psychol. 38, 551–569 (2017).  https://doi.org/10.1111/pops.12337CrossRefGoogle Scholar
  3. 3.
    Bruns, A.: Gatewatching and News Curation: Journalism, Social Media, and the Public Sphere. Peter Lang, New York (2018).  https://doi.org/10.3726/b13293CrossRefGoogle Scholar
  4. 4.
    Cattaruzza, A., Danet, D., Taillat, S., Laudrain, A.: Sovereignty in cyberspace: balkanization or democratization. In: 2016 International Conference on Cyber Conflict (CyCon U.S.), pp. 1–9. IEEE, Washington, D.C. (2016).  https://doi.org/10.1109/cyconus.2016.7836628
  5. 5.
    Chugunov, A., Filatova, O., Misnikov, Y.: Citizens’ deliberation online as will-formation: the impact of media identity on policy discourse outcomes in Russia. In: Tambouris, E., et al. (eds.) ePart 2016. LNCS, vol. 9821, pp. 67–82. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-45074-2_6CrossRefGoogle Scholar
  6. 6.
    Conover, M.D., Ratkiewicz, J., Francisco, M., Goncalves, B., Menczer, F., Flammini, A.: Political polarization on Twitter. In: Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, pp. 89–96 (2011)Google Scholar
  7. 7.
    Dutton, W.H., Reisdorf, B., Dubois, E., Blank, G.: Search and politics: the uses and impacts of search in Britain, France, Germany, Italy, Poland, Spain, and the United States. Quello Center Working Paper No. 5-1-17 (2017).  https://doi.org/10.2139/ssrn.2960697
  8. 8.
    Duvanova, D., Nikolaev, A., Nikolsko-Rzhevskyy, A., Semenov, A.: Violent conflict and online segregation: an analysis of social network communication across Ukraine’s regions. J. Comp. Econ. 44(1), 163–181 (2016).  https://doi.org/10.1016/j.jce.2015.10.003CrossRefGoogle Scholar
  9. 9.
    Gentzkow, M., Shapiro, J.M.: Ideological segregation online and offline. Q. J. Econ. 126(4), 1799–1839 (2011).  https://doi.org/10.1093/qje/qjr044CrossRefGoogle Scholar
  10. 10.
    Gitlin, T.: Public sphere or public sphericules? In: Liebes, T., Curran, J. (eds.) Media, Ritual and Identity, pp. 168–174. Routledge, London (1998)Google Scholar
  11. 11.
    Goggins, S., Petakovic, E.: Connecting theory to social technology platforms: a framework for measuring influence in context. Am. Behav. Sci. 58(10), 1376–1392 (2014).  https://doi.org/10.1177/0002764214527093CrossRefGoogle Scholar
  12. 12.
    Gruzd, A., Wellman, B.: Networked influence in social media: introduction to the special issue. Am. Behav. Sci. 58(10), 1251–1259 (2014).  https://doi.org/10.1177/0002764214527087CrossRefGoogle Scholar
  13. 13.
    Kobayashi, T., Ikeda, K.: Selective exposure in political web browsing. Inf. Commun. Soc. 12(6), 929–953 (2009).  https://doi.org/10.1080/13691180802158490CrossRefGoogle Scholar
  14. 14.
    Latane, B.: Dynamic social impact: the creation of culture by communication. J. Commun. 46(4), 13–25 (1996).  https://doi.org/10.1111/j.1460-2466.1996.tb01501.xCrossRefGoogle Scholar
  15. 15.
    Martyanov, D., Bykov, I.: Ideological segregation in the Russian cyberspace: evidences from St. Petersburg. In: Alexandrov, D.A., Boukhanovsky, A.V., Chugunov, A.V., Kabanov, Y., Koltsova, O. (eds.) DTGS 2017. CCIS, vol. 745, pp. 259–269. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-69784-0_22CrossRefGoogle Scholar
  16. 16.
    Newell, E., et al.: User migration in online social networks: a case study on Reddit during a period of community unrest. In: Proceedings of the Tenth International AAAI Conference on Web and Social Media (ICWSM 2016), pp. 279–288 (2016)Google Scholar
  17. 17.
    Nie, Y., Jia, Y., Li, S., Zhu, X., Li, A., Zhou, B.: Identifying users across social networks based on dynamic core interests. Neurocomputing 210, 107–115 (2016).  https://doi.org/10.1016/j.neucom.2015.10.147CrossRefGoogle Scholar
  18. 18.
    Pariser, E.: The Filter Bubble: What the Internet is Hiding from You. The Penguin Press, New York (2011)Google Scholar
  19. 19.
    Shu, K., Wang, S., Tang, J., Zafarani, R., Liu, H.: User identity linkage across online social networks: a review. ACM SIGKDD Explor. Newsl. 18(2), 5–17 (2017).  https://doi.org/10.1145/3068777CrossRefGoogle Scholar
  20. 20.
    Sunstein, C.R.: Republic.com 2.0. Princeton University Press, Princeton (2009)Google Scholar
  21. 21.
    Tan, S., Guan, Z., Cai, D., Qin, X., Bu, J., Chen, C.: Mapping users across networks by manifold alignment on hypergraph. In: Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, pp. 159–165 (2014)Google Scholar
  22. 22.
    Van Alstyne, M., Brynjolfsson, E.: Global village or Cyber-Balkans? Modeling and measuring the integration of electronic communities. Manage. Sci. 51(6), 851–868 (2005).  https://doi.org/10.1287/mnsc.1050.0363CrossRefzbMATHGoogle Scholar
  23. 23.
    Wieringa, M.A., van Geenen, D., Schäfer, M.T., Gorzeman, L.: Political topic-communities and their framing practices in the Dutch Twittersphere. Internet Policy Rev. 7(2) (2018).  https://doi.org/10.14763/2018.2.793
  24. 24.
    Williams, D.: The impact of time online: social capital and Cyberbalkanization. CyberPsychol. Behav. 10(3), 398–406 (2007).  https://doi.org/10.1089/cpb.2006.9939CrossRefGoogle Scholar
  25. 25.
    Yun, G.W., Park, S.Y., Holody, K., Yoon, K.S., Xie, S.: Selective moderation, selective responding, and balkanization of the blogosphere: a field experiment. Media Psychol. 16(3), 295–317 (2013).  https://doi.org/10.1080/15213269.2012.759462CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.St. Petersburg State UniversitySt. PetersburgRussia

Personalised recommendations