Skip to main content

Advertisement

SpringerLink
Log in

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

  • Published:
Higher Education Aims and scope Submit manuscript

Abstract

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 Twitter.com. 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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Altbach, P. G. (2004). The costs and benefits of world-class universities. Academe, 90(1), 20–23.

    Article  Google Scholar 

  • 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 

  • Burris, V. (2004). The academic caste system: Prestige hierarchies in PhD exchange networks. American Sociological Review, 69(2), 239–264.

    Article  Google Scholar 

  • Castells, M. (1996). The rise of the network society. Oxford: Blackwell Publishers Limited.

    Google Scholar 

  • 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

    Article  Google Scholar 

  • De Queiroz, J.-A. (2015) Facs et grandes écoles: le classement des directeurs les plus suivis sur Twitter. Accessed at http://etudiant.lefigaro.fr/les-news/actu/detail/article/enseignement-superieur-qui-est-le-directeur-le-plus-suivi-sur-twitter-10731/pm. 5 May 2015.

  • Desmarais, B. A., & Cranmer, S. J. (2012). Statistical inference for valued-edge networks: The generalized exponential random graph model. PLoS ONE, 7(1), e30136.

    Article  Google Scholar 

  • 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 

  • 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

    Article  Google Scholar 

  • 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 

  • Goldstein, H. (1995). Multilevel statistical models. Chichester: Wiley.

    Google Scholar 

  • Granovetter, M. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380.

    Article  Google Scholar 

  • Grant, C.B. (2013) Losing our chains? Contexts and ethics of university internationalisation. Leadership Foundation for Higher Education Stimulus Paper. ISBN: 978-1-906627-42-3

  • 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.

    Article  Google Scholar 

  • 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, CRAN.R-project.org/package=ergm.

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Junco, R., Heiberger, G., & Loken,. E. (2011). The effect of Twitter on college student engagement and grades. Journal of Computer Assisted Learning, 27(2), 119–132

  • King, R. (2010). Policy internationalization, national variety and governance: global models and network power in higher education states. Higher Education, 60, 583–594.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  Google Scholar 

  • Lewis, B., & Rush, D. (2013). Experience of developing Twitter-based communities of practice in higher education. Research in Learning Technology, 21, 185–198.

    Article  Google Scholar 

  • Liu, N. C., & Cheng, Y. (2005). The academic ranking of world universities. Higher Education in Europe, 30(2), 127–136.

    Article  Google Scholar 

  • Marginson, S. (2006). Dynamics of national and global competition in higher education. Higher Education, 52, 1–39.

    Article  Google Scholar 

  • Marginson, S. (2008). Global field and global imagining: Bourdieu and worldwide higher education. British Journal of Sociology of Education, 29(3), 303–315.

    Article  Google Scholar 

  • 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 

  • 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.

  • 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.

    Chapter  Google Scholar 

  • Mohrman, K., Ma, W., & Baker, D. (2008). The research university in transition: The emerging global model. Higher Education Policy, 21, 5–27.

    Article  Google Scholar 

  • Moody, J. (2004). The Structure of a social science collaboration network: Disciplinary cohesion from 1963 to 1999. American Sociological Review, 69(2), 213–238.

    Article  Google Scholar 

  • Paradeise, C., & Thoenig, J.-C. (2013). Academic institutions in search of quality: Local orders and global standards. Organization Studies, 34(2), 189–218.

    Article  Google Scholar 

  • Parr, C. (2014). Top 100 most influential UK and US universities on Twitter. Accessed at http://www.timeshighereducation.co.uk/2013373.article on 11 May 2015.

  • 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.

    Article  Google Scholar 

  • 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 

  • 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

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Robertson, S. L. (2012). World-class higher education (for whom?). Prospects, 42(3), 237–245.

    Article  Google Scholar 

  • 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 

  • 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 

  • 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.

    Article  Google Scholar 

  • Royal Society. (2011). Knowledge, networks and nations: Global scientific collaboration in the 21st century. ISBN: 978-0-85403-890-9.

  • Snijders, T. (2011). Statistical models for social networks. Annual Review of Sociology, 37, 131–153.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/

  • Wallace, J. R. (2012). Imap: Interactive Mapping. R package version 1.32. http://CRAN.R-project.org/package=Imap

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Bath, Bath, UK

    Robin Shields

Authors
  1. Robin Shields
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Robin Shields.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 19 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shields, R. Following the leader? Network models of “world-class” universities on Twitter. High Educ 71, 253–268 (2016). https://doi.org/10.1007/s10734-015-9900-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10734-015-9900-z

Keywords

Search

Navigation