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ABSTRACT
The ability of authoritarian regimes to maintain power hinges, in part, on how well they are able to manipulate the flow of information to the masses. While authoritarian states have had success controlling traditional media, the growth of social media over the last decade has created new challenges for such regimes. The Russian experience offers an example of how an authoritarian regime responds to this potential threat. Because of the massive demonstrations surrounding the 2011–2012 Duma elections, the ruling Russian government suspected that social media provided a significant impetus for the demonstrations. Social media, through its dissemination of opposition blogs, could have helped drive negative attitudes about the governing party. As such, the government responded by employing strategies to tighten their grip on the digital flow of information. We use survey data to demonstrate that exposure to blogs via social media at the time of the demonstrations led many to believe that the elections were fraudulent. Ultimately, we contend that Russian fears concerning the importance of social media for the fomenting of opposition movements is well grounded. Social media can drive support for opposition in an autocratic state.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1 Additional studies linking the 2011–2012 protests to social media networking include Soldatov and Borogan, The Red Web; Klyueva, “Taming Online Political Engagement”; White and McAllister, “Did Russia (Nearly)”; Oates, Revolution Stalled.
2 Freedom House gave Russia scores of 52 in 2011 and 2012 in its Freedom on the Net report, but by 2014 the score had dropped to 60, and reached 65 in 2016 (a score of 0 is most free, 200 is least free). At https://freedomhouse.org/report/freedom-net/2016/russia.
3 Koesel and Bunce, “Diffusion-Proofing.”
4 Soldatov and Borogan, “Russia's Surveillance State.”
5 Reuter and Szakonyi, “Online Social Media.”
6 Ibid.
7 Oates, Revolution Stalled.
8 Soldatov and Borogan, The Red Web.
9 Soldatov and Borogan, “Russia's Surveillance State.”
10 See Boulianne for a complete review, “Does Internet Use Affect Engagement?”
11 Nisbet, Stoycheff and Pearce, “Internet Use”; Valenzuela, Park and Kee, “Is There Social Capital?”
12 Reuter and Szakonyi, “Online Social Media.”
13 Toepfl, “Making Sense of the News”; Reuter and Szakonyi, “Online Social Media”; Hassid, “Safety Valve or Pressure Cooker?”
14 Boulianne, “Does Internet Use Affect Engagement?”
15 Gainous and Wagner, Tweeting to Power; Wagner and Gainous, “Digital Uprising.”
16 Giustozzi, Koran, Kalashnikov, and Laptop.
17 Gainous, Wagner and Abbott, “Civic Disobedience”.
18 Zaller, The Nature and Origins; Bizer et al., “Memory-Based Versus On-line Processing”; Hastie and Park, “The Relationship Between Memory and Judgment”; Cassino, Taber and Lodge, “Information Processing”; Lodge and Taber, “Three Steps Toward a Theory.”
19 Hassid, “Safety Valve or Pressure Cooker?”; Bailard, “A Field Experiment.”
20 Wagner and Gainous, “Digital Uprising”; Lynch, “After Egypt.”
21 Oates, Revolution Stalled.
22 Gainous, Wagner and Abbott, “Civic Disobedience”; Wagner and Gainous, “Digital Uprising.”
23 La Due Lake and Huckfeldt, “Social Capital, Social Networks.”
24 Freedom on the Net 2016, Russia. https://freedomhouse.org/report/freedom-net/2016/russia.
25 RIA Novosti, “Two Thirds of Russians.”
26 Lipman, “Russia's Nongovernmental Media”; Oates, “GLASNOST 2.0.”
27 A VTsIOM survey conducted 10–11 December 2011 found Putin's popularity at 51%, down from 68% in January 2011. Medvedev's popularity had dropped from 66 to 51% over the same period. “Vladimir Putin's Popularity Drops”, The Telegraph, 16 December 2011. http://www.telegraph.co.uk/news/worldnews/europe/russia/8960649/Vladimir-Putins-popularity-drops.html
28 Volkov, “Putinism Under Siege.”
29 This multi-stage sample involved four stages. The first stage was categorizing the country by seven federal regions (North-Western, Central, Southern, Povolzhskii, Uralskii, Siberian, and Far Eastern), and inside each region there were five population-based strata created where the number of respondents selected were proportional to the total population. Altogether this first stage of the sample resulted inclusion of 127 settlements (92 urban settlements 35 rural districts). The second stage involved random selection of electoral districts within each settlement. This totaled 280 electoral districts. The third stage was the selection of households. Route lists were used and each 17th household was selected on blocks with high-rise buildings and each 5th household was selected on blocks with individual houses. The final stage was the section of the respondent. The respondent, 18 years or older, with the nearest birthday was interviewed.
30 We also use a host of control variables in this model including Support for the Status Quo Government, Civic Engagement, Traditional Media Attention, Economic Security, Urbanicity, Gender, Age, and Education (see the Supplemental data for operationalizations).
31 These three ordinal items were each rescaled to range from 0 to 1, then summed, and rescaled to range from 0–1 to create a highly reliable index (α = 0.88).
32 For the mediating model that follows, we added the Facebook and Twitter use items together and rescaled it to range 0–1 creating an ordinal indicator of Western Social Media Use.
33 Oates, Revolution Stalled.
34 Reuter and Szakonyi, “Online Social Media.”
35 Gainous and Wagner, Tweeting to Power.
36 King, Pan and Roberts, “How Censorship in China.”
37 Toepfl, “Making Sense of the News”; Reuter and Szakonyi, “Online Social Media”; Hassid, “Safety Valve or Pressure Cooker?”
38 The first stage of the model relies on an ordered logit estimation because Blog Exposure is distributed ordinally, and the second stage is a linear estimation because Perceived Electoral Fraud is distributed continuously.
39 Notice that the degree of missingness in the Stage 2 model is particularly high. There was a loss of 670 observations. We performed Little's Missing Completely at Random (MCAR) test and the results indicate that these values are not missing completely at random (p = .00), so there is reason to believe that these missing data may also not be Missing at Random (MAR). To address the possibility that our results in are a product of this missingness, we replaced the missing values using multiple imputation based on the multivariate normal and re-estimated the model based on five pooled imputed datasets using Rubin's Rules to correct the standard errors. The substantive results of the model did not change (see Supplemental data). As such, we decided to present the results of un-imputed model.
40 We tested the robustness of this mediating model by estimating multiple Stage 1 and Stage 2 model specifications. We estimated both stages by excluding each statistically significant variable, one at a time, to assure that the effects of our primary variables (Western Social Media Use in Stage 1 and Stage 2, and Blog Exposure in Stage 2) were consistent with the fully specified model. The results suggested this was the case. The pattern of statistical significance did not change (see Supplemental data).
41 Before matching there was some imbalance across our collapsed Support for the Status Quo Government and both our Blog Exposure and Western SM Use treatment dummies (Χ2 p-value = .02 for both).
42 Reuter and Szakonyi, “Online Social Media.”
43 Brownlee, Authoritarianism in an Age.
44 Oates, “GLASNOST 2.0”; Lipman, “Russia's Nongovernmental Media”; Kovalyova, “Kremlin Sets Out to Extend Control.” For a list of Russian legislation and significant developments affecting digital freedom in Russia, see the Digital Rights in Russia website. https://russiadigitalrights.org/
45 Toepfl, “Making Sense of the News”; Reuter and Szakonyi, “Online Social Media.”
46 Pallin, “Internet Control through Ownership.”
47 Nocetti, “Contest and Conquest.”
48 Roth, “Putin Signs New Anti-Terror Law.”
49 Brennan, “Putin Says CIA Created the Internet.”
51 “Russia's 2016 Elections.”
52 Calculated from Kommersant. http://www.kommersant.ru/districts/results.
53 Mukhametshchina, “Iz Rossii uezhaet.”
54 Semenova, “Novia emigratsiia.”
Additional information
Notes on contributors
Jason Gainous
Jason Gainous is a professor of political science at the University of Louisville whose research focuses on information technology and politics. He has co-authored two books: Tweeting to Power: The Social Media Revolution in American Politics, and Rebooting American Politics: The Internet Revolution. He has also published various articles in journals including American Politics Research, Journal of Information Technology & Politics, Political Research Quarterly, Political Communication, Social Science Quarterly, and Statistical Science, among others.
Kevin M. Wagner
Kevin M. Wagner is an attorney and an associate professor of political science at Florida Atlantic University. He has published 2 co-authored books, one with Oxford University Press (Tweeting to Power: The Social Media Revolution in American Politics) and one with Rowman and Littlefield (Rebooting American Politics: The Internet Revolution). His research and scholarship on American politics have been published in leading journals, including American Politics Research, Journal of Information Technology & Politics, Journal of Legislative Studies, and Social Science Quarterly, among others.
Charles E. Ziegler
Charles E. Ziegler is a professor of political science and Distinguished University Professor at the University of Louisville. He is the author or editor of five books and more than 80 refereed book chapters and articles in journals such as International Studies Perspectives, International Relations, Comparative Politics, British Journal of Political Science, and International Politics on Russia and Eurasia. His latest edited book is Civil Society and Politics in Central Asia (University Press of Kentucky).