Political Behavior

, Volume 38, Issue 1, pp 105–128 | Cite as

When Treatments are Tweets: A Network Mobilization Experiment over Twitter

  • Alexander Coppock
  • Andrew GuessEmail author
  • John Ternovski
Original Paper


This study rigorously compares the effectiveness of online mobilization appeals via two randomized field experiments conducted over the social microblogging service Twitter. In the process, we demonstrate a methodological innovation designed to capture social effects by exogenously inducing network behavior. In both experiments, we find that direct, private messages to followers of a nonprofit advocacy organization’s Twitter account are highly effective at increasing support for an online petition. Surprisingly, public tweets have no effect at all. We additionally randomize the private messages to prime subjects with either a “follower” or an “organizer” identity but find no evidence that this affects the likelihood of signing the petition. Finally, in the second experiment, followers of subjects induced to tweet a link to the petition are more likely to sign it—evidence of a campaign gone “viral.” In presenting these results, we contribute to a nascent body of experimental literature exploring political behavior in online social media.


Field experiments Networks Political participation 



The authors would like to thank the League of Conservation Voters, whose support and eagerness to include new experimental designs in its programs made this study possible. We also thank the Analyst Institute for its initial support of this project. The authors’ names are listed in alphabetical order. We particularly thank Amit Mistry, Vanessa Kritzer, Kristin Brown, and Mo Maraqa at LCV for their crucial roles in the planning and implementation of the two experiments. We are further grateful to Andy Przybylski and Neelanjan Sircar for extremely helpful discussions and feedback during the early stages of this project. We also thank Kevin Collins, Lindsay Dolan, Ben Farrer, Don Green, Lucas Leemann, three anonymous reviewers, and the editors of Political Behavior for their helpful comments and advice. An earlier version of this paper was presented at the 2014 Annual Meeting of the American Political Science Association in Washington, D.C., where we benefited from a lively discussion with participants and comments by Jaime Settle. This study would not have been possible without the use of Columbia University's Hotfoot High Performance Computing (HPC) Cluster for hosting the scraping programs.

Supplementary material

11109_2015_9308_MOESM1_ESM.pdf (1.1 mb)
Supplementary material 1 (PDF 1145 kb)


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Alexander Coppock
    • 1
  • Andrew Guess
    • 1
    Email author
  • John Ternovski
    • 2
  1. 1.Department of Political ScienceColumbia UniversityNew YorkUSA
  2. 2.Oxford Internet InstituteUniversity of OxfordOxfordUK

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