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A Model of Protests, Revolution, and Information

Author

Listed:
  • Salvador Barbera

    (MOVE, Universitat Autònoma de Barcelona and Barcelona GSE)

  • Matthew O. Jackson

    (Stanford University)

Abstract
A revolt or protest succeeds only if sufficient people participate. We study how potential participants' ability to coordinate is affected by their information. We distinguish four phenomena that affect whether information either encourages or inhibits protests and revolutions: (i) Unraveling: When agents learn about each others' types, some are discouraged by meeting partisans of the status quo. This can unravel, as even confident agents realize that enough supporters will be discouraged to preclude a successful revolution. (ii) Homophily: Learning someone else's type under homophily is less informative since that individual is more likely to be similar to the learner. This can lead people to be less confident of a revolution, but can also stop potential unraveling. (iii) Extremism: Meeting other protestors, and seeing pilot demonstrations or outcomes in similar countries, reveal not only how much support for change exists, but also from which constituencies it emerges. This can undercut a revolution if factions differ sufficiently in their preferred changes. (iv) Counter Demonstrations: partisans for the status quo can hold counter-demonstrations to signal their strength. We also discuss why holding mass demonstrations before a revolution may provide better signals of peoples willingness to actively participate than other less costly forms of communication (e.g., via social media), and how governments use redistribution and propaganda to avoid a revolution.

Suggested Citation

  • Salvador Barbera & Matthew O. Jackson, 2017. "A Model of Protests, Revolution, and Information," HiCN Working Papers 243, Households in Conflict Network.
    • Handle: RePEc:hic:wpaper:243
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Kishishita, Daiki & Yamagishi, Atsushi, 2021. "Contagion of populist extremism," Journal of Public Economics, Elsevier, vol. 193(C).
    2. Leopoldo Fergusson & Carlos Molina, 2020. "Facebook Causes Protests," HiCN Working Papers 323, Households in Conflict Network.
    3. Andrea Tesei & Filipe Campante & Ruben Durante, 2022. "Media and Social Capital," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 69-91, August.
    4. González, Felipe, 2020. "Collective action in networks: Evidence from the Chilean student movement," Journal of Public Economics, Elsevier, vol. 188(C).
    5. Nathan Canen & Anujit Chakraborty, 2022. "Choosing The Best Incentives for Belief Elicitation with an Application to Political Protests," Papers 2210.12549, arXiv.org.
    6. Cantoni, Davide & Heizlsperger, Louis-Jonas & Yang, David Y. & Yuchtman, Noam & Zhang, Y. Jane, 2022. "The fundamental determinants of protest participation: Evidence from Hong Kong’s antiauthoritarian movement," Journal of Public Economics, Elsevier, vol. 211(C).
    7. Canen, Nathan & Chakraborty, Anujit, 2023. "Belief elicitation in political protest experiments: When the mode does not teach us about incentives to protest," Journal of Economic Behavior & Organization, Elsevier, vol. 216(C), pages 320-331.
    8. Gisli Gylfason, 2023. "From Tweets to the Streets: Twitter and Extremist Protests in the United States," PSE Working Papers halshs-04188189, HAL.
    9. Pierre C. Boyer & Thomas Delemotte & Germain Gauthier & Vincent Rollet & Benoît Schmutz, 2020. "Social Media and the Dynamics of Protests," CESifo Working Paper Series 8326, CESifo.
    10. Gerling, Lena & Kellermann, Kim Leonie, 2022. "Contagious populists: The impact of election information shocks on populist party preferences in Germany," European Journal of Political Economy, Elsevier, vol. 72(C).
    11. Afridi, Farzana & Basistha, Ahana & Dhillon, Amrita & Serra, Danila, 2023. "Activating Change: The Role of Information and Beliefs in Social Activism," IZA Discussion Papers 16358, Institute of Labor Economics (IZA).
    12. Masiliūnas, Aidas, 2017. "Overcoming coordination failure in a critical mass game: Strategic motives and action disclosure," Journal of Economic Behavior & Organization, Elsevier, vol. 139(C), pages 214-251.
    13. Boyer, Pierre & Delemotte, Thomas & Gauthier, Germain & Rollet, Vincent & Schmutz, Benoit, 2020. "The Gilets jaunes: Offline and Online," CEPR Discussion Papers 14780, C.E.P.R. Discussion Papers.
    14. Vicente Calabuig & Natalia Jiménez-Jiménez & Gonzalo Olcina & Ismael Rodriguez-Lara, 2024. "Coordinated and uncoordinated punishment in a team investment game," Theory and Decision, Springer, vol. 97(2), pages 191-217, September.

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    More about this item

    Keywords

    Revolution; demonstration; protests; strikes; Arab Spring;
    All these keywords.

    JEL classification:

    • D74 - Microeconomics - - Analysis of Collective Decision-Making - - - Conflict; Conflict Resolution; Alliances; Revolutions
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games

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