Bloggers’ Responses to the Snowden Affair: Combining Automated and Manual Methods in the Analysis of News Blogging

  • Dag ElgesemEmail author
  • Ingo Feinerer
  • Lubos Steskal


The Snowden affair gave rise to a huge public debate about not only the legitimacy of the secret surveillance programs he revealed but also about Snowden himself and about the accuracy of the information he leaked. In this paper we present an analysis of how the affair was discussed in the English language blogosphere, based on a corpus of 15,000 blog posts written about Snowden and published from June 2013 to June 2014, as a sub-corpus of a larger corpus of 100,000 blog posts on the topic of surveillance, written during the period 2006–2014. Automated tools are used to identify the topics that characterize the blogging about surveillance and the posts about the Snowden affair. Through an in-depth analysis of the blog posts that commented on Snowden’s revelations of the PRISM program for surveillance of social media users, we chart how bloggers responded to Snowden and his role in this disclosure, whether they found the information credible, and the extent to which they expressed criticism of the surveillance practices. The analysis is used as a basis for discussing the role of blogs in the civic engagement during the first phase of the Snowden affair.


Blog research Blogs Cluster analysis Social media Surveillance Topic analysis Trust 



This research was supported by a grant from the Research Council of Norway’s VERDIKT program (NTAP, project 213401). We are very grateful to Knut Hofland and Andrew Salway for their role in creating the corpus analyzed here.


  1. Bacharach, M. and D. Gambetta (2001). Trust in Signs, in K. Cook (eds): Trust in Society. New York: Russell Sage.Google Scholar
  2. Blei, D. M. and John D. Lafferty (2009). Topic models. A. N. Srivastava and M. Sahami (eds): Text mining: classification, clustering, and applications. London: Chapman and Hall, pp. 71–89.Google Scholar
  3. Blei, David M., A. Y. Ng, and M. I. Jordan (2003). Latent dirichlet allocation. Journal of machine Learning research, vol. 3, pp. 993–1022.zbMATHGoogle Scholar
  4. Branum, J. and J. Charteris-Black (2015). The Edward Snowden Affair: A corpus study of the British press. Discourse and Communication, vol. 9, no. 2, pp. 1–22CrossRefGoogle Scholar
  5. Bruns, A. (eds) (2005). Gatewatching. Collaborative Online News Production. New York: Peter Lang.Google Scholar
  6. Bruns, A. (2007). Methodologies for Mapping the Political Blogosphere: An Exploration Using the IssueCrawler Research Tool. First Monday. Accessed 23 June 2015.
  7. Bruns, A. and J. Jacobs (eds) (2006). The Uses of Blogs. New York: Peter Lang.Google Scholar
  8. Chadwick, A. and B. Collister (2014). Boundary-Drawing Power and the Renewal of Professional News Organizations: The Case of The Guardian and the Snowden National Security Agency Leak. International Journal of Communication, vol. 8, pp. 2420–2441.Google Scholar
  9. Couldry, N., S. Livingstone and T. Markham (2007). Media Consumption and Public Engagement. Basingstoke: Palgrave.Google Scholar
  10. Dhillon, I.S. and D.S. Modha (2001). Concept Decompositions for Large Sparse Text Data Using Clustering. Machine Learning, vol. 42, no. 1, pp. 143–175.CrossRefzbMATHGoogle Scholar
  11. Duns J. (2015). News of Devils. The media and Edward Snowden. CreateSpace Independent Publishing Platform.Google Scholar
  12. Edward Snowden: the whistleblower behind the NSA surveillance revelations (2013, June 11). The Guardian. Accessed: March 21, 2015.
  13. Elster, Jon (2007). Explaining Human Behavior. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  14. Fleiss, J.L., B. Levin and M.C. Paik (2003): Statistical methods for rates and proportions, 3rd ed. Hoboken: Wiley.CrossRefzbMATHGoogle Scholar
  15. Gambetta, D. and H. Hamill (2005). Streetwise. How Taxi Drivers Establish Their Customer’s Trustworthiness. New York: Russell Sage.Google Scholar
  16. Greenwald, G. (2014). No Place to Hide. Edward Snowden, the NSA and the Surveillance State. London: Hamish Hamilton.Google Scholar
  17. Hornik, K., I. Feinerer, M. Kober and C. Buchta (2012). Spherical k-Means Clustering. Journal of Statistical Software, vol. 50, no. 10, 1–22.CrossRefGoogle Scholar
  18. Karpf, D. (2008). Understanding Blog Space. Journal of Information Technology and Politics. Vol. 5, no. 4, pp. 369–385.CrossRefGoogle Scholar
  19. Leccese, M. (2009). Online Information Sources of Political Blogs. Journalism and Mass Communication Quarterly. vol. 86, no. 3, pp. 578–593.CrossRefGoogle Scholar
  20. Manning, C. D., P. Raghavan and H. Schütze (2008). Introduction to Information Retrieval. Cambridge: Cambridge University Press.CrossRefzbMATHGoogle Scholar
  21. Meinel, C., J. Bross, P. Bergen and P. Henning (2015). Blogosphere and its Exploration. New York: Springer.CrossRefGoogle Scholar
  22. Moe, H. (2011). Mapping the Norwegian Blogosphere: Methodological Challenges in Internationalizing Internet Research. Social Science Computer Review. Vol. 29, no. 3, pp. 313–326CrossRefGoogle Scholar
  23. Rasmussen, Eric (2006). Games and Information. An Introduction to Game Theory. London: Blackwell.Google Scholar
  24. PEW Research Center (2013). Public Split over Impact of NSA Leak, But Most Want Snowden Persecuted. Last visited: March 21, 2015.
  25. Rettberg, J. W. (2008). Blogging. Cambridge: Polity.Google Scholar
  26. Rogers, R. (2013). Digital Methods. Cambridge: MIT Press.Google Scholar
  27. Rousseeuw, P. J. (1987). Silhouettes: a Graphical Aid to the Interpretation and Validation of Cluster Analysis. Computational and Applied Mathematics, vol. 20, pp. 53–65. doi: 10.1016/0377-0427(87)90125-7.CrossRefzbMATHGoogle Scholar
  28. van Dijck, J. (2014). Datafication, dataism and dataveillance: Big data between scientific paradigm and ideology. Surveillance & Society, vol. 12, no. 2, pp. 197–208.Google Scholar
  29. Wemple, E. (2013). Leaker, Source or Whistleblower. Washington Post Accessed 21 March 2015.

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Department of Information Science and Media StudiesUniversity of BergenBergenNorway
  2. 2.Department of InformaticsVienna University of TechnologyViennaAustria

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