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Profiling Insurrection: Characterizing Collective Action Using Mobile Device Data

Author

Listed:
  • David Van Dijcke

    (University of Michigan, Ann Arbor)

  • Austin L. Wright

    (University of Chicago - Harris School of Public Policy)

Abstract

We develop a novel approach for estimating spatially dispersed community-level participation in mass protest. This methodology is used to investigate factors associated with participation in the ‘March to Save America’ event in Washington, D.C. on January 6, 2021. This study combines granular location data from more than 40 million mobile devices with novel measures of community-level voting patterns, the location of organized hate groups, and the entire georeferenced digital archive of the social media platform Parler. We find evidence that partisanship, socio-political isolation, proximity to chapters of the Proud Boys organization, and the local activity on Parler are robustly associated with protest participation. Our research fills a prominent gap in the study of collective action: identifying and studying communities involved in mass-scale events that escalate into violent insurrection.

Suggested Citation

  • David Van Dijcke & Austin L. Wright, 2021. "Profiling Insurrection: Characterizing Collective Action Using Mobile Device Data," Working Papers 2021-13, Becker Friedman Institute for Research In Economics.
    • Handle: RePEc:bfi:wpaper:2021-13
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    References listed on IDEAS

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    1. Grolemund, Garrett & Wickham, Hadley, 2011. "Dates and Times Made Easy with lubridate," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i03).
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    Cited by:

    1. Iacoella, Francesco & Justino, Patrica & Martorano, Bruno, 2021. "Do pandemics lead to rebellion? Policy responses to COVID-19, inequality, and protests in the USA," MERIT Working Papers 2021-014, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).

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    More about this item

    Keywords

    insurrections; protests; riots; collective action; big data; cellphone; mobile devices;
    All these keywords.

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