Homophily Evolution in Online Networks: Who Is a Good Friend and When?

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 661)


Homophily is considered by network scientists as one of the major mechanisms of social network formation. However, the role of dynamic homophily in the network growth process has not been investigated in detail yet. In this paper, we estimate the role of homophily by various attributes at different stages of online network formation process. We consider the process of online friendship formation in the Vkontakte social networking site among first-year students at a Russian university. We reveal that at the beginning of the network formation a similarity in gender and score in entrance exams plays the key role, while by the end of network establishment period the role of the same group affiliation becomes more important. We explain the results with the tendency of students to follow different strategies to control the information flow in their social environment.


Network growth Network evolution Homophily Online networks Student networks 



The authors thank Olessia Koltsova, Sergey Koltsov, and Vladimir Filippov for the opportunity to use Vkminer application. We would like to thank Benjamin Lind for the discussion and feedback on this work. The financial support of the 5–100 Government Program and Basic Research Program at the National Research University Higher School of Economics (HSE) is greatly appreciated.


  1. 1.
    Block, P., Grund, T.: Multidimensional homophily in friendship networks. Netw. Sci. 2, 189–212 (2014)CrossRefGoogle Scholar
  2. 2.
    Lazarsfeld, P.F., et al.: Friendship as a social process: a substantive and methodological analysis. Freedom Control Mod. Soc. 18(1), 18–66 (1954)Google Scholar
  3. 3.
    McPherson, M., Smith-Lovin, L., Cook, J.M.: Birds of a feather: Homophily in social networks. Ann. Rev. Sociol. 27, 415–444 (2001)CrossRefGoogle Scholar
  4. 4.
    Adamic, L.A., Glance, N.: The political blogosphere and the 2004 US election: divided they blog. In: Proceedings of the 3rd International Workshop on Link Discovery, pp. 36–43. ACM (2005)Google Scholar
  5. 5.
    Lauw, H.W., Shafer, J.C., Agrawal, R., Ntoulas, A.: Homophily in the digital world: a livejournal case study. IEEE Internet Comput. 14, 15–23 (2010)CrossRefGoogle Scholar
  6. 6.
    Moody, J.: Race, school integration, and friendship segregation in America1. Am. J. Sociol. 107, 679–716 (2001)CrossRefGoogle Scholar
  7. 7.
    Goodreau, S.M., Kitts, J.A., Morris, M.: Birds of a feather, or friend of a friend? using exponential random graph models to investigate adolescent social networks*. Demography 46, 103–125 (2009)CrossRefGoogle Scholar
  8. 8.
    Lewis, K., Kaufman, J., Gonzalez, M., Wimmer, A., Christakis, N.: Tastes, ties, and time: a new social network dataset using facebook. com. Soc. Netw. 30, 330–342 (2008)CrossRefGoogle Scholar
  9. 9.
    Lewis, K., Gonzalez, M., Kaufman, J.: Social selection and peer influence in an online social network. Proc. Nat. Acad. Sci. 109, 68–72 (2012)CrossRefGoogle Scholar
  10. 10.
    Mayer, A., Puller, S.L.: The old boy (and girl) network: social network formation on university campuses. J. Public Econ. 92, 329–347 (2008)CrossRefGoogle Scholar
  11. 11.
    Vaquero, L.M., Cebrian, M.: The rich club phenomenon in the classroom. Scientific reports 3 (2013)Google Scholar
  12. 12.
    Venables, W.N., Smith, D.M.: The R development core team. A Programming Environment for Data Analysis and Graphics, An Introduction to R. Notes on R (2005)Google Scholar
  13. 13.
    Dokuka, S., Valeeva, D., Yudkevich, M.: Formation and evolution mechanisms in online network of students: the Vkontakte case. In: Khachay, M.Y., Konstantinova, N., Panchenko, A., Ignatov, D.I., Labunets, V.G. (eds.) AIST 2015. CCIS, vol. 542, pp. 263–274. Springer, Heidelberg (2015). doi: 10.1007/978-3-319-26123-2_26 CrossRefGoogle Scholar
  14. 14.
    Newman, M.E.: Assortative mixing in networks. Phys. Rev. Lett. 89, 208701 (2002)CrossRefGoogle Scholar
  15. 15.
    Anderson, B.S., Butts, C., Carley, K.: The interaction of size and density with graph-level indices. Soc. Netw. 21, 239–267 (1999)CrossRefGoogle Scholar
  16. 16.
    Newman, M.E.: Mixing patterns in networks. Phys. Rev. E 67, 026126 (2003)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Burt, R.S.: Structural holes and good ideas. Am. J. Sociol. 110, 349–399 (2004)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Center for Institutional StudiesHigher School of EconomicsMoscowRussia

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