A 61-million-person experiment in social influence and political mobilization

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Human behaviour is thought to spread through face-to-face social networks, but it is difficult to identify social influence effects in observational studies9, 10, 11, 12, 13, and it is unknown whether online social networks operate in the same way1419. Here we report results from a randomized controlled trial of political mobilization messages delivered to 61 million Facebook users during the 2010 US congressional elections. The results show that the messages directly influenced political self-expression, information seeking and real-world voting behaviour of millions of people. Furthermore, the messages not only influenced the users who received them but also the users’ friends, and friends of friends. The effect of social transmission on real-world voting was greater than the direct effect of the messages themselves, and nearly all the transmission occurred between ‘close friends’ who were more likely to have a face-to-face relationship. These results suggest that strong ties are instrumental for spreading both online and real-world behaviour in human social networks.

At a glance


  1. The experiment and direct effects.
    Figure 1: The experiment and direct effects.

    a, b, Examples of the informational message and social message Facebook treatments (a) and their direct effect on voting behaviour (b). Vertical lines indicate s.e.m. (they are too small to be seen for the first two bars).

  2. The effect of mobilization treatment that a friend received on a user/'s behaviour.
    Figure 2: The effect of mobilization treatment that a friend received on a user’s behaviour.

    ad, A validation study shows that at increasing levels of interaction, Facebook friends are more likely to have a close real-world relationship (a; see also the Supplementary Information). As the interaction increases, so does the observed per-friend effect of friend’s treatment on a user’s expressed voting (b), validated voting (c) and polling-place search (d). Blue diamonds indicate the observed treatment effect. Horizontal grey bars show the null distribution derived from simulations of identical networks in which the topology and incidence of the behaviour and treatment are the same but the assignments of treatment are randomly reassigned.


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Author information


  1. Political Science Department, University of California, San Diego, La Jolla, California 92093, USA

    • Robert M. Bond,
    • Christopher J. Fariss,
    • Jaime E. Settle &
    • James H. Fowler
  2. Psychology Department, University of California, San Diego, La Jolla, California 92093, USA

    • Jason J. Jones
  3. Data Science, Facebook, Inc., Menlo Park, California 94025, USA

    • Adam D. I. Kramer &
    • Cameron Marlow
  4. Medical Genetics Division, University of California, San Diego, La Jolla, California 92093, USA

    • James H. Fowler


Author Contributions All authors contributed to study design, data collection, analysis and preparation of the manuscript. J.H.F. secured funding.

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The authors declare no competing financial interests.

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Supplementary information

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  1. Supplementary Information (4.4M)

    This file contains Supplementary Text and Data, Supplementary Tables 1-19, Supplementary Figures 1-6 and additional references.

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