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A Model of Protests, Revolution, and Information

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  • Barbera, Salvador
  • Jackson, Matthew O.

Abstract

A collective action or revolt succeeds only if sufficiently many people participate. We study how potential revolutionaries' ability to coordinate is affected by what they learn from different sources. We first examine how people learn about the likelihood of a revolution's success by talking to those around themselves, which can either work in favor or against the success of an uprising, depending on the prior beliefs of the agents, the homogeneity of preferences in the population, and the number of contacts. We extend the analysis by examining the effects of homophily on learning: people are more likely to meet others who have similar preferences, undercutting learning. We introduce variants of our model to discuss other ways of learning about the support for a revolution. We discuss why holding mass protests before a revolt provides more informative signals of people's willingness to actively participate than other less costly forms of communication (e.g., via social media). We also show how outcomes of revolutions in one region can inform citizens of another region and thus trigger (or discourage) neighboring revolutions. We also discuss the role of governments in avoiding revolutions and learning about their citizens' concerns; in particular, by observing the strength of protests and counter-protests.

Suggested Citation

  • Barbera, Salvador & Jackson, Matthew O., 2020. "A Model of Protests, Revolution, and Information," Quarterly Journal of Political Science, now publishers, vol. 15(3), pages 297-335, July.
  • Handle: RePEc:now:jlqjps:100.00019002
    DOI: 10.1561/100.00019002
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    Citations

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    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; revolt; rebellion; strike; Arab Spring; homophily;
    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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