Skip to main content
×
×
Home

Elites Tweet to Get Feet Off the Streets: Measuring Regime Social Media Strategies During Protest

  • Kevin Munger, Richard Bonneau, Jonathan Nagler and Joshua A. Tucker
Abstract

As non-democratic regimes have adapted to the proliferation of social media, they have began actively engaging with Twitter to enhance regime resilience. Using data taken from the Twitter accounts of Venezuelan legislators during the 2014 anti-Maduro protests in Venezuela, we fit a topic model on the text of the tweets and analyze patterns in hashtag use by the two coalitions. We argue that the regime’s best strategy in the face of an existential threat like the narrative developed by La Salida and promoted on Twitter was to advance many competing narratives that addressed issues unrelated to the opposition’s criticism. Our results show that the two coalitions pursued different rhetorical strategies in keeping with our predictions about managing the conflict advanced by the protesters. This article extends the literature on social media use during protests by focusing on active engagement with social media on the part of the regime. This approach corroborates and expands on recent research on inferring regime strategies from propaganda and censorship.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Elites Tweet to Get Feet Off the Streets: Measuring Regime Social Media Strategies During Protest
      Available formats
      ×
      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Elites Tweet to Get Feet Off the Streets: Measuring Regime Social Media Strategies During Protest
      Available formats
      ×
      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Elites Tweet to Get Feet Off the Streets: Measuring Regime Social Media Strategies During Protest
      Available formats
      ×
Copyright
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Footnotes
Hide All
*

Kevin Munger, PhD student, Department of Politics, New York University, New York, NY 10012 (km2713@nyu.edu). Richard Bonneau is the Professor of Biology and Computer Science; Director at the NYU Center for Data Science and Co-Director at the NYU Social Media and Political Participation (SMaPP) lab, Center for Genomics and Systems Biology, 12 Waverly Place, New York, NY 10003 (bonneau@nyu.edu). Jonathan Nagler is the Professor of Politics; Co-Director at the NYU Social Media and Political Participation (SMaPP) lab and Affiliated Professor of Data Science, Department of Politics, New York University, 19 W. 4th Street, New York, NY 10012 (jonathan.nagler@nyu.edu). Joshua Tucker is the Professor of Politics; Director at the Jordan Center for the Advanced Study of Russia; Co-Director at the NYU Social Media and Political Participation (SMaPP) lab and Affiliated Professor of Russian and Slavic Studies and of Data Science, Department of Politics, New York University, 19 W. 4th Street, New York, NY 10012 (joshua.tucker@nyu.edu). The writing of this article was supported by the Social Media and Political Participation Lab at NYU, which is funded in part by the INSPIRE program of the National Science Foundation (Award SES-1248077), and New York University’s Dean Thomas Carew’s Research Investment Fund. This article was written in conjunction with NYU’s Social Media and Political Participation (SMaPP) lab. We would like to thank Dorothy Kronick, Livio di Lonardo, Pedro Rodriguez, Andy Guess, Neal Beck, Chris Lucas, Alex Scacco, Duncan Penfold-Brown, Jonathan Ronen, Yvan Scher, and Adam Przeworksi, along with two anonymous reviewers; participants at the 2016 Society for Institutional & Organizational Economics Conference, the NYU Graduate Political Economy Seminar, and the 2015 Midwest Political Science Association meeting; seminar attendees at the Universidad del Desarollo (Chile) and the Universidad del Rosario (Colombia); and members of the NYU Social Media and Political Participation (SMaPP) Lab, for their valuable feedback on earlier versions of this project. K.M. is a PhD student member and the remaining authors are Co-Directors. Munger conducted all of the statistical analyses and wrote the first draft of the manuscript. All of the authors contributed to the research design, data collection, and revisions of the manuscript. To view supplementary material for this article, please visit https://doi.org/10.1017/psrm.2018.3

Footnotes
References
Hide All
Agarwal, Sheetal D., Bennett, W. Lance, Johnson, Courtney N., and Walker, Shawn. 2014. ‘A Model of Crowd Enabled Organization: Theory and Methods for Understanding the Role of Twitter in the Occupy Protests’. International Journal of Communication 8:646672.
Bennett, W. Lance, Segerberg, Alexandra, and Walker, Shawn. 2014. ‘Organization in the Crowd: Peer Production in Large-Scale Networked Protests’. Information, Communication & Society 17(2):232260.
Blei, David M., Ng, Andrew Y., and Jordan, Michael I.. 2003. ‘Latent Dirichlet Allocation’. The Journal of Machine Learning Research 3:9931022.
Blei, David M., and Lafferty, John D.. 2007. ‘A Correlated Topic Model of Science’. The Annals of Applied Statistics 1:1735.
Chen, Jidong, Pan, Jennifer, and Xu, Yiqing. 2015. ‘Sources of Authoritarian Responsiveness: A Field Experiment in China’. American Journal of Political Science 60(2):383400.
Christensen, Darin, and Garfias, Francisco. 2015. ‘Can You Hear Me Now?: How Communication Technology Affects Protest and Repression’. Available at https://ssrn.com/abstract=2529769, accessed 11 August 2015.
Ciccariello-Maher, Georeg. 2014. ‘LaSalida? Venezuela at a Crossroads’. The Nation. Available at https://www.thenation.com/article/lasalida-venezuela-crossroads/, accessed 1 September 2015.
Corrales, Javier. 2013. ‘Chavismo After Chavez’. Foreign Affairs. Available at https://www.foreignaffairs.com/articles/venezuela/2013-01-04/chavismo-after-ch-vez, accessed 1 September 2015.
Corrales, Javier, and Penfold-Becerra, Michael. 2011. Dragon in the Tropics: Hugo Chavez and the Political Economy of Revolution in Venezuela. Washington, DC: Brookings Institution Press.
Deibert, Ronald, Palfrey, John, Rohozinski, Rafal, Zittrain, Jonathan, and Haraszti, Miklos. 2010. Access Controlled: The Shaping of Power, Rights, and Rule in Cyberspace. Cambridge: MIT Press.
Diaz, Sara Carolina. 2014. ‘Sector de la oposicin convoca a marcha para el 12 de febrero’. El Universal. Available at http://www.eluniversal.com/nacional-y-politica/140202/sector-de-la-oposicion-convoca-a-marcha-para-el-12-de-febrero, accessed 1 September 2015.
Earl, Jennifer, Hurwitz, Heather McKee, Mesinas, Analicia Mejia, Tolan, Margaret, and Arlotti, Ashley. 2013. ‘This Protest will be Tweeted: Twitter and Protest Policing During the Pittsburgh G20’. Information, Communication & Society 16(4):459478.
Edmond, Chris. 2013. ‘Information Manipulation, Coordination, and Regime Change’. The Review of Economic Studies 80(4):14221458.
Enikolopov, Ruben, Makarin, Alexey, and Petrova, Maria. 2015. ‘Social Media and Protest Participation: Evidence from Russia’. Available at https://ssrn.com/abstract=2777540, accessed 31 May 2016.
Freedom House. 2014. Freedom in the World 2014: The Annual Survey of Political Rights and Civil Liberties. New York: Rowman & Littlefield.
Friedman, Uri. 2014. ‘Why Venezuela’s Revolution Will Be Tweeted’. The Atlantic. Available at https://www.theatlantic.com/international/archive/2014/02/why-venezuelas-revolution-will-be-tweeted/283904/, accessed 11 August 2015.
Greitens, Sheena Chestnut. 2013. ‘Authoritarianism Online: What Can We Learn from Internet Data in Nondemocracies?’. PS: Political Science & Politics 46(2):262270.
Griffiths, Thomas L., and Steyvers, Mark. 2004. ‘Finding Scientific Topics’. Proceedings of the National Academy of Sciences of the United States of America 101(Suppl 1):52285235.
Gunitsky, Seva. 2015. ‘Corrupting the Cyber-Commons: Social Media as a Tool of Autocratic Stability’. Available at https://doi.org/10.1017/S153792714003120, accessed 31 May 2016.
Hassanpour, Navid. 2014. ‘Media Disruption and Revolutionary Unrest: Evidence From Mubarak’s Quasi-Experiment’. Political Communication 31(1):124.
Hastie, Trevor, Tibshirani, Robert, and Friedman, Jerome. 2009. The Elements of Statistical Learning, vol. 2. New York, NY: Springer.
Hong, Liangjie, and Davison, Brian D.. 2010. ‘Empirical Study of Topic Modeling in Twitter’. Proceedings of the First Workshop on Social Media Analytics, Association for Computing Machinery, Washington, DC, 80–88.
Hornik, Kurt, and Grün, Bettina. 2011. ‘topicmodels: An R Package for Fitting Topic Models’. Journal of Statistical Software 40(13):130.
Howard, Philip N., and Hussain, Muzammil M.. 2011. ‘The Role of Digital Media’. Journal of Democracy 22(3):3548.
Howard, Philip N., Agarwal, Sheetal D., and Hussain, Muzammil M.. 2011. ‘When Do States Disconnect Their Digital Networks? Regime Responses to the Political Uses of Social Media’. The Communication Review 14(3):216232.
King, Gary, Pan, Jennifer, and Roberts, Margaret E.. 2013. ‘How Censorship in China Allows Government Criticism But Silences Collective Expression’. American Political Science Review 107(2):326343.
King, Gary, Pan, Jennifer, and Roberts, Margaret E.. 2017. ‘How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument’. American Political Science Review 111(3):484501.
Leshchenko, Sergii. 2014. ‘The Maidan and Beyond: The Media’s Role’. Journal of Democracy 25(3):5257.
Mainwaring, Scott. 2012. ‘From Representative Democracy to Participatory Competitive Authoritarianism: Hugo Chavez and Venezuelan Politics’. Perspectives on Politics 10(4):955967.
Malesky, Edmund, and Schuler, Paul. 2010. ‘Nodding or Needling: Analyzing Delegate Responsiveness in an Authoritarian Parliament’. American Political Science Review 104(3):482502.
Oates, Sarah. 2013. Revolution Stalled: The Political Limits of the Internet in the Post-Soviet Sphere. Oxford: Oxford University Press.
Pan, Jennifer. 2017. ‘How Market Dynamics of Domestic and Foreign Social Media Firms Shape Strategies of Internet Censorship’. Problems of Post-Communism 64(3–4): 167188.
Perez, Valentina. 2014. ‘The Grim Reality of Venezuelan Protests’. Harvard Political Review. Available at http://harvardpolitics.com/world/grim-reality-venezuela-protests/, accessed 1 September 2015.
Phan, Xuan-Hieu, Nguyen, Le-Minh, and Horiguchi, Susumu. 2008. ‘Learning to Classify Short and Sparse Text & Web With Hidden Topics From Large-Scale Data Collections’. Proceedings of the 17th International Conference on World Wide Web, Association for Computing Machinery, Beijing, China, 91–100.
Qin, Bei, Strömberg, David, and Wu, Yanhui. 2017. ‘Why Does China Allow Freer Social Media? Protests Versus Surveillance and Propaganda’. Journal of Economic Perspectives 31(1):117140.
Roberts, Margaret E., M. Stewart, Brandon, and Tingley, Dustin. 2014. ‘stm: R Package for Structural Topic Models’. R Package Version 0.6 1. Available at https://cran.r-project.org/web/packages/stm/vignettes/stmVignette.pdf, accessed 1 June 2016.
Sanovich, Sergey, Stukal, Denis, and Tucker, Joshua A.. 2018. ‘Turning the Virtual Tables: Government Strategies for Addressing Online Opposition with an Application to Russia’. Comparative Politics (forthcoming).
Schattschneider, Elmer E. 1960. The Semi-Sovereign People: A Realist’s View of Democracy in America. New York: Wadsworth Publishing.
Schoonderwoerd, Nico. 2013. ‘4 Ways How Twitter Can Keep Growing-PeerReach Blog’, Available at http://peerreach.com/2013/11/4-ways-howtwitter-can-keep-growing/, accessed 13 April 2015.
Shannon, Claude. 1948. ‘A Mathematical Theory of Communication’. The Bell System Technical Journal 27:379423.
Tufekci, Zeynep. 2014. ‘Social Movements and Governments in the Digital Age: Evaluating a Complex Landscape’. Journal of International Affairs 68(1):118.
Tufekci, Zeynep, and Wilson, Christopher. 2012. ‘Social Media and the Decision to Participate in Political Protest: Observations from Tahrir Square’. Journal of Communication 62(2):363379.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Political Science Research and Methods
  • ISSN: 2049-8470
  • EISSN: 2049-8489
  • URL: /core/journals/political-science-research-and-methods
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×
Type Description Title
PDF
Supplementary materials

Munger et al. supplementary material 1
Munger et al. supplementary material

 PDF (191 KB)
191 KB

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed