Identifying Influential Twitter Users in the 2011 Egyptian Revolution

  • Lucas A. Overbey
  • Christopher Paribello
  • Terresa Jackson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7812)


Recent international events surrounding contentious political environments have uncovered a new utility for social media. Communities now use resources such as Facebook and Twitter to quickly spread information and project influence amongst potentially geographically disparate people. In this work, we investigate Twitter activity in Egypt during the 2011 protests and revolution, and introduce a model to automatically ascertain key individuals within these networks. The model takes advantage of a more sparse network on Twitter than the traditional follower/following network by leveraging direct communications. Furthermore, we employ a measure of alpha centrality, which incorporates both directionality of network connections and a measure of external importance. The model is applied to topic-based communities within Twitter rather than previously introduced measures of influence that focus on the cascading spread of single messages or broad, topic-invariant measures. Results indicate a model successful at automatically identifying users that are active and influential within a given community, agreeing well with heuristics and comparable to other influence models but with particular advantages such as tunability and robustness to incomplete data.


social media influence social network analysis contentious politics 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Merton, R.: Patterns of influence: local and cosmopolitan influentials. In: Merton, R. (ed.) Social Theory and Social Structure, pp. 441–474. Free Press, New York (1968)Google Scholar
  2. 2.
    Roch, C.: The dual roots of opinion leadership. Journal of Politics 67 (2005)Google Scholar
  3. 3.
    Rogers, E.: Diffusion of Innovations. Free Press, New York (1995)Google Scholar
  4. 4.
    Berk, R.: An introduction to sample selection bias in sociological data. American Sociological Review 48(3), 386–398 (1983)CrossRefGoogle Scholar
  5. 5.
    Starbird, K., Palen, L. (How) will the revolution be retweeted? information diffusion and the 2011 egyptian uprising. In: CSCW 2012 (February 2012)Google Scholar
  6. 6.
  7. 7.
    Gladwell, M.: Why the revolution will not be tweeted. The New Yorker (2010)Google Scholar
  8. 8.
    Nunns, A., Idle, N.: Tweets from Tahrir: Egypt’s Revolution as it Unfolded, in the Words of the People Who Made it. OR Books (2011)Google Scholar
  9. 9.
    Cha, M., Haddadi, H., Benevenuto, F., Gummadi, K.: Twitter frees iran: An evaluation of twitter’s role in public diplomacy and information operations. In: Communications and Policy Forum. Network Insight Institute (2009)Google Scholar
  10. 10.
    Watts, D., Dodds, P.: Influentials, networks, and public opinion formation. Journal of Consumer Research 34(4), 441–458 (2007)CrossRefGoogle Scholar
  11. 11.
    Agarwal, N., Liu, H., Tang, L., Yu, P.: Identifying the influential bloggers in a community. In: WSDM 2008. ACM (February 2008)Google Scholar
  12. 12.
    Bakshy, E., Hofman, J., Mason, W., Watts, D.: Everyone’s an influencer: quantifying influence on twitter. In: WSDM 2011. ACM (February 2011)Google Scholar
  13. 13.
    Ghosh, R., Lerman, K., Surachawala, T., Voevodski, T., Teng, S.: Non-conservative diffusion and its application to social network analysis (2011),
  14. 14.
    Bonacich, P., Lloyd, P.: Eigenvector-like measures of centrality for asymmetric relations. Social Networks 23, 191–201 (2001)CrossRefGoogle Scholar
  15. 15.
    Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press (1994)Google Scholar
  16. 16.
    Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems 30, 107–117 (1998)CrossRefGoogle Scholar
  17. 17.
    Huberman, B., Romero, D., Wu, F.: Social networks that matter: Twitter under the microscope. First Monday 14, 1–5 (2009)Google Scholar
  18. 18.
    Starbird, K., Palen, L.: Pass it on? retweeting in mass emergency. In: ISCRAM 2010 (May 2010)Google Scholar
  19. 19.
    Boyd, D., Golder, S., Lotan, G.: Tweet, tweet, retweet: Conversational aspects of retweeting on twitter. In: HCSS, pp. 1–10. The University of Hawaii at Manoa (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Lucas A. Overbey
    • 1
  • Christopher Paribello
    • 2
  • Terresa Jackson
    • 1
  1. 1.SPAWAR Systems Center AtlanticNorth CharlestonUSA
  2. 2.MathWorksNatickUSA

Personalised recommendations