Higher Education

, Volume 71, Issue 2, pp 253–268 | Cite as

Following the leader? Network models of “world-class” universities on Twitter

  • Robin Shields


Much research on higher education has discussed the positional competition induced by global rankings and the complementary concept of “world-class” universities. This paper investigates the network of social media communication between globally ranked universities. Specifically, it examines whether universities seek to preserve and reproduce status by selectively forming associations with highly ranked institutions. It uses social network analysis and exponential random graph models to investigate data on interactions through the popular social media website Findings show that social media communications are significantly related to global rankings, but that the size of this effect is quite small. Instead, structural relationships within the network and geographical location appear to have more influence on network structure. These results suggest a need to critically reassess the category of “world-class” universities and the role of global rankings in global higher education.


Higher education Social media Social network analysis ERGM Rankings 

Supplementary material

10734_2015_9900_MOESM1_ESM.pdf (2.2 mb)
Supplementary material 1 (PDF 19 kb)


  1. Altbach, P. G. (2004). The costs and benefits of world-class universities. Academe, 90(1), 20–23.CrossRefGoogle Scholar
  2. Böhm, A., Follari, M., Hewett, A., Jones, S., Kemp, N., Meares, D., et al. (2004). Vision 2020, forecasting international student mobility: A UK Perspective. London: British Council.Google Scholar
  3. Burris, V. (2004). The academic caste system: Prestige hierarchies in PhD exchange networks. American Sociological Review, 69(2), 239–264.CrossRefGoogle Scholar
  4. Castells, M. (1996). The rise of the network society. Oxford: Blackwell Publishers Limited.Google Scholar
  5. Dale, R., & Robertson, S. L. (2002). The varying effects of regional organizations as subjects of globalization of education. Comparative Education Review, 46(2), 10–36. doi: 10.1086/324052 CrossRefGoogle Scholar
  6. De Queiroz, J.-A. (2015) Facs et grandes écoles: le classement des directeurs les plus suivis sur Twitter. Accessed at 5 May 2015.
  7. Desmarais, B. A., & Cranmer, S. J. (2012). Statistical inference for valued-edge networks: The generalized exponential random graph model. PLoS ONE, 7(1), e30136.CrossRefGoogle Scholar
  8. Dunlap, J. C., & Lowenthal, P. R. (2009). Tweeting the night away: Using Twitter to enhance social presence. Journal of Information Systems Education, 20(2), 129–135.Google Scholar
  9. Enders, J. (2004). Higher education, internationalisation, and the nation-state: recent developments and challenges for governance theory. Higher Education, 47(3), 361–382. doi: 10.1023/B:HIGH.0000016461.98676.30 CrossRefGoogle Scholar
  10. Fruchterman, T. M. J., & Reingold, E. M. (1991). Graph drawing by force-directed placement. Software: Practice and Experience, 21(11), 1129–1164. doi: 10.1002/spe.4380211102 Google Scholar
  11. Goldstein, H. (1995). Multilevel statistical models. Chichester: Wiley.Google Scholar
  12. Granovetter, M. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380.CrossRefGoogle Scholar
  13. Grant, C.B. (2013) Losing our chains? Contexts and ethics of university internationalisation. Leadership Foundation for Higher Education Stimulus Paper. ISBN: 978-1-906627-42-3Google Scholar
  14. Guarino, C., Ridgeway, G., Chun, M., & Buddin, R. (2011). Latent variable analysis: A new approach to university ranking. Higher Education in Europe, 30(2), 147–165.CrossRefGoogle Scholar
  15. Handcock, M., Hunter, D., Butts, C., Goodreau, S., Krivitsky, P., & Morris, M. (2013). ERGM: Fit, simulate and diagnose exponential-family models for networks. R package version 3.1.1,
  16. Hayes, A. F., & Cai, L. (2007). Using heteroskedasticity-consistent standard error estimators in OLS regression: An introduction and software implementation. Behaviour Research Methods, 39(4), 709–722.CrossRefGoogle Scholar
  17. Hunter, D. R., Handcock, M. S., Butts, C. T., Goodreau, S. M., & Morris, M. (2008). ERGM: A package to fit, simulate and diagnose exponential-family models for networks. Journal of Statistical Software, 24(3), 1–29.CrossRefGoogle Scholar
  18. Jeremic, V., Bulajic, M., Martic, M., & Radojicic, Z. (2011). A fresh approach to evaluating the academic ranking of world universities. Scientometrics, 87(3), 587–596.CrossRefGoogle Scholar
  19. Junco, R., Heiberger, G., & Loken,. E. (2011). The effect of Twitter on college student engagement and grades. Journal of Computer Assisted Learning, 27(2), 119–132Google Scholar
  20. King, R. (2010). Policy internationalization, national variety and governance: global models and network power in higher education states. Higher Education, 60, 583–594.CrossRefGoogle Scholar
  21. Koskinen, J., & Daraganova, G. (2013). Exponential random graph model fundamentals. In D. Lusher, J. Kokinen, & G. Robins (Eds.), Exponential random graph models for social networks: Theory, methods and applications (pp. 49–76). Cambridge: Cambridge University Press.Google Scholar
  22. Lewis, T., Marginson, S., & Synder, I. (2005). The network university? Technology, culture and organisational complexity in contemporary higher education. Higher Education Quarterly, 59(1), 56–75.CrossRefGoogle Scholar
  23. Lewis, B., & Rush, D. (2013). Experience of developing Twitter-based communities of practice in higher education. Research in Learning Technology, 21, 185–198.CrossRefGoogle Scholar
  24. Liu, N. C., & Cheng, Y. (2005). The academic ranking of world universities. Higher Education in Europe, 30(2), 127–136.CrossRefGoogle Scholar
  25. Marginson, S. (2006). Dynamics of national and global competition in higher education. Higher Education, 52, 1–39.CrossRefGoogle Scholar
  26. Marginson, S. (2008). Global field and global imagining: Bourdieu and worldwide higher education. British Journal of Sociology of Education, 29(3), 303–315.CrossRefGoogle Scholar
  27. Marginson, S. (2010). Global comparisons and the university knowledge economy. In L. M. Portnoi, V. D. Rust, & S. S. Bagley (Eds.), Higher education, policy and the global competition phenomenon (pp. 29–42). New York: Palgrave Macmillan.Google Scholar
  28. Marginson, S., & van der Wende, M. (2007). Globalisation and higher education. Education working paper number 8. EDU/WKP(2007)3. Paris: Organisation for Economic Co-operation and Development.Google Scholar
  29. Marsden, P. V. (2005). Recent developments in network measurement. In S. Wasserman (Ed.), Models and methods in social network analysis (pp. 8–30). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  30. Mohrman, K., Ma, W., & Baker, D. (2008). The research university in transition: The emerging global model. Higher Education Policy, 21, 5–27.CrossRefGoogle Scholar
  31. Moody, J. (2004). The Structure of a social science collaboration network: Disciplinary cohesion from 1963 to 1999. American Sociological Review, 69(2), 213–238.CrossRefGoogle Scholar
  32. Paradeise, C., & Thoenig, J.-C. (2013). Academic institutions in search of quality: Local orders and global standards. Organization Studies, 34(2), 189–218.CrossRefGoogle Scholar
  33. Parr, C. (2014). Top 100 most influential UK and US universities on Twitter. Accessed at on 11 May 2015.
  34. Pempek, T. A., Yermolayeva, Y. A., & Calvert, S. L. (2009). College students’ social networking experiences on Facebook. Journal of Applied Developmental Psychology, 30(3), 227–238.CrossRefGoogle Scholar
  35. Ramirez, F. O. (2010). Accounting for excellence: Transforming universities into organizational actors. In L. M. Portnoi, V. D. Rust, & S. S. Bagley (Eds.), Higher education, policy and the global competition phenomenon (pp. 43–58). New York: Palgrave Macmillan.Google Scholar
  36. Ramirez, F. O., & Tiplic, D. (2014). In pursuit of excellence? Discursive patterns in European higher education research. Higher Education, 67(4), 439–455. doi: 10.1007/s10734-013-9681-1 CrossRefGoogle Scholar
  37. Rinaldo, S. B., Tapp, S., & Laverie, D. A. (2011). Learning by tweeting: Using Twitter as a pedagogical tool. Journal of Marketing Education, 33(2), 193–203.CrossRefGoogle Scholar
  38. Robertson, S. L. (2012). World-class higher education (for whom?). Prospects, 42(3), 237–245.CrossRefGoogle Scholar
  39. Robins, G., & Lusher, D. (2013a). What are exponential random graph models? In D. Lusher, J. Kokinen, & G. Robins (Eds.), Exponential random graph models for social networks: Theory, methods and applications (pp. 9–15). Cambridge: Cambridge University Press.Google Scholar
  40. Robins, G., & Lusher, D. (2013b). Illustrations: Simulation, estimation and goodness of fit. In D. Lusher, J. Kokinen, & G. Robins (Eds.), Exponential random graph models for social networks: Theory, methods and applications (pp. 167–185). Cambridge: Cambridge University Press.Google Scholar
  41. Robins, G., Pattison, P., Kalish, Y., & Lusher, D. (2007). An introduction to exponential random graph models (p*) for social networks. Social Networks, 29(2), 173–191.CrossRefGoogle Scholar
  42. Royal Society. (2011). Knowledge, networks and nations: Global scientific collaboration in the 21st century. ISBN: 978-0-85403-890-9.Google Scholar
  43. Snijders, T. (2011). Statistical models for social networks. Annual Review of Sociology, 37, 131–153.CrossRefGoogle Scholar
  44. Tapper, T., & Filippakou, O. (2009). The world-class league tables and the sustaining of international reputations in higher education. Journal of Higher Education Policy and Management, 31(1), 55–66.CrossRefGoogle Scholar
  45. Taylor, P., & Braddock, R. (2007). International university ranking systems and the idea of university excellence. Journal of Higher Education Policy and Management, 29(3), 245–260.CrossRefGoogle Scholar
  46. R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
  47. Wallace, J. R. (2012). Imap: Interactive Mapping. R package version 1.32.
  48. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.University of BathBathUK

Personalised recommendations