skip to main content
10.1145/3447535.3462480acmconferencesArticle/Chapter ViewAbstractPublication PageswebsciConference Proceedingsconference-collections
research-article

A Bayesian Analysis of Collective Action and Internet Shutdowns in India

Published:22 June 2021Publication History

ABSTRACT

Since 2011, internet shutdowns have steadily become an increasingly popular form of digital repression, especially in India – which accounted for more than 50% of global recorded shutdowns from 2016 to 2019. Common shutdown justifications include ‘ensuring public safety’ in order to curb the prevalence of collective action in the form of protests and riots. This paper examines the correlation between internet shutdowns and a range of predictors, identifying riots as the main predictor of a shutdown.

We focus on shutdowns throughout India between 2016 and 2019 with particular attention to Jammu and Kashmir. Primarily using data from the NGO Access Now and the Integrated Conflict Early Warning System, we apply Bayesian inference via generalised linear modelling implemented using the Stan probabilistic programming language, to estimate correlates of shutdown behaviour. We first examine how the prevalence of collective action may impact the probability of observing a shutdown; and second how the length of a shutdown impacts subsequent collective action.

Our main finding is that riots seem to be the key predictor of a shutdown with increased protests and riots increasing the odds of observing a shutdown the same day by 7% with a 95% credible interval of 0.01-0.13 and 15% with a 95% credible interval of 0.03-0.26 respectively. As a predictor, however, the duration of an internet shutdown only has a marginal negative effect on the occurrence of riots at -8% per subsequent shutdown day with a 95% credible interval of -0.16 to -0.002.

References

  1. E. Stepanova, “The Role of Information Communication Technologies in the “ Arab Spring" IMPLICATIONS BEYOND THE REGION,” PONARS Eurasia Policy Memo, no. 159, pp. 1–6, 2011.Google ScholarGoogle Scholar
  2. P. N. Howard and M. M. Hussain, Democracy's Fourth Wave? 2013.Google ScholarGoogle ScholarCross RefCross Ref
  3. H. Peleg and J. Mendilow, “Corruption and the Arab Spring Comparing the Pre- and Post-Spring Situation,” pp. 99–115, 2014.Google ScholarGoogle Scholar
  4. L. Grinin, A. Korotayev, and A. Tausch, Islamism, Arab Spring, and the Future of Democracy, Perspectives on Development in the Middle East and North Africa (MENA) Region. 2018.Google ScholarGoogle Scholar
  5. B. Wellman , “The Social Affordances of the Internet for Networked Individualism,” J. Comput. Commun., vol. 8, no. 3, pp. 0–0, 2003.Google ScholarGoogle Scholar
  6. L. DeNardis, “Hidden levers of internet control: An infrastructure-based theory of Internet governance,” Inf. Commun. Soc., vol. 15, no. 5, pp. 720–738, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  7. Access Now, “Fighting Internet Shutdowns Around The World,” Access Now, p. 4, 2018.Google ScholarGoogle Scholar
  8. Access Now, “The State of Internet Shutdowns Around the World: The 2018 #Keepiton Report,” 2019.Google ScholarGoogle Scholar
  9. Access Now, “Targeted, Cut off, and Left in the Dark: The #KeepItOn report on internet shutdowns in 2019,” 2020.Google ScholarGoogle Scholar
  10. Internet Shutdown Project, “Internet Shutdown Tracker,” 2020. [Online]. Available: https://internetshutdowns.in/. [Accessed: 21-Jun-2020].Google ScholarGoogle Scholar
  11. International Federation of Library Associations and Institutions, “IFLA Statement on Internet Shutdowns,” no. August. 2018.Google ScholarGoogle Scholar
  12. Access Now, “RightsCon Silicon Valley 2016,” pp. 1–9, 2016.Google ScholarGoogle Scholar
  13. J. Wright, A. Darer, and O. Farnan, “On identifying anomalies in tor usage with applications in detecting internet censorship,” WebSci 2018 - Proc. 10th ACM Conf. Web Sci., pp. 87–96, 2018.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Internet Society, “Internet Shutdowns An Internet Society Public Policy Briefing,” no. December, pp. 1–13, 2017.Google ScholarGoogle Scholar
  15. K. Collins, “Inside the dystopian nightmare of an internet shutdown,” CNET, 31-Oct-2019. [Online]. Available: https://www.cnet.com/features/inside-the-dystopian-nightmare-of-an-internet-shutdown/. [Accessed: 13-Jun-2020].Google ScholarGoogle Scholar
  16. E. Marchant and N. Stremlau, “AFRICA ’ S INTERNET SHUTDOWNS WORKSHOP,” 2019.Google ScholarGoogle Scholar
  17. Internet and Mobile Association of India, “DIGITAL IN INDIA 2019-ROUND 2 REPORT,” 2019.Google ScholarGoogle Scholar
  18. D. M. West, “Internet shutdowns cost countries $2.4 billion last year,” Brookings Inst., no. October, pp. 1–20, 2016.Google ScholarGoogle Scholar
  19. R. Kathuria, M. Kedia, G. Varma, K. Bagchi, and R. Sekhani, “The Anatomy of an INTERNET BLACKOUT: Measuring the Economic Impact of Internet Shutdowns in India,” no. April, 2018.Google ScholarGoogle Scholar
  20. United Nations, “General Assembly - Item #10, Document Reference A/HRC/32/L.20.” 2016.Google ScholarGoogle Scholar
  21. J. Rydzak, “Disconnected: A Human Rights-Based Approach to Network Disruptions,” 2019.Google ScholarGoogle Scholar
  22. R. Shandler, “Measuring the political and social consequences of government-initiated cyber shutdowns,” 8th USENIX Work. Free Open Commun. Internet, FOCI 2018, co-located with USENIX Secur. 2018, 2018.Google ScholarGoogle Scholar
  23. J. Wright, “Regional variation in Chinese internet filtering,” Inf. Commun. Soc., vol. 17, no. 1, pp. 121–141, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  24. C. Davenport, “State Repression and Political Order,” Annu. Rev. Polit. Sci., vol. 10, no. 1, pp. 1–23, 2007.Google ScholarGoogle ScholarCross RefCross Ref
  25. W. Moore, “Repression and Dissent: Substitution , Context , and Timing,” Midwest Polit. Sci. Assoc., vol. 42, no. 3, pp. 851–873, 1998.Google ScholarGoogle Scholar
  26. D. McAdam, J. McCarthy, and M. Zald, Comparative Perspectives on Social Movements. New York, New York, USA: Cambridge University Press., 1996.Google ScholarGoogle ScholarCross RefCross Ref
  27. T. Gurr, “Why Men Rebel,” 1970.Google ScholarGoogle Scholar
  28. M. Olson, “The Logic of Collective Action,” The Political Economy of Growth. 1965.Google ScholarGoogle Scholar
  29. R. Hardin, “Collective Action As An Agreeable n-Prisoners’ Dilemma,” Behav. Sci., vol. 16, 1971.Google ScholarGoogle ScholarCross RefCross Ref
  30. B. Bimber, A. J. Flanagin, and C. Stohl, “Action in the Contemporary,” Commun. Theory, vol. 15, no. 4, pp. 365–388, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  31. W. L. Bennett and A. Segerberg, “The logic of connective action: Digital media and the personalization of contentious politics,” Inf. Commun. Soc., vol. 15, no. 5, pp. 739–768, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  32. BBC, “Citizenship Act protests: Three dead and thousands held in India - BBC News,” 19-Dec-2019. [Online]. Available: https://www.bbc.co.uk/news/world-asia-india-50833361. [Accessed: 17-Jun-2020].Google ScholarGoogle Scholar
  33. S. Keelery, “Number of social network users in India from 2015 to 2018 with a forecast until 2023,” Statista Database, 07-Jul-2020. [Online]. Available: https://www.statista.com/statistics/278407/number-of-social-network-users-in-india/. [Accessed: 05-Sep-2020].Google ScholarGoogle Scholar
  34. J. Rydzak, “A Total Eclipse of the Net: The Dynamics of Network Shutdowns and Collective Action Responses TT - Une éclipse totale du Net: Les coupures de communication digitale et l'action collective,” ProQuest Diss. Theses, p. 268, 2018.Google ScholarGoogle Scholar
  35. E. Boschee, J. Lautenschlager, S. O'Brien, S. Shellman, and J. Starz, “ICEWS Coded Event Data,” Harvard Dataverse, vol. V28, 2015.Google ScholarGoogle Scholar
  36. M. Betancourt, “Towards A Principled Bayesian Workflow,” Apr-2020. [Online]. Available: https://betanalpha.github.io/assets/case_studies/principled_bayesian_workflow.html. [Accessed: 27-Aug-2020].Google ScholarGoogle Scholar
  37. Stan Development Team, “Stan Modeling Language: User's Guide and Reference Manual,” 2015.Google ScholarGoogle Scholar
  38. P.-C. Buerkner, “brms: An R package for Bayesian multilevel models using Stan,” J. Stat. Softw., vol. 80, no. 1, pp. 1–28, 2017.Google ScholarGoogle Scholar
  39. J. Fox, “Applied Regression Analysis and Generalized Linear Models. Chapter 15: Generalized Linear Models,” 2015.Google ScholarGoogle Scholar
  40. A. Vehtari, A. Gelman, J. Gabry, P.-C. Bürkner, and M. Magnusson, “Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models,” Stat. Comput., vol. 27, no. 5, pp. 1413–1432, 2017.Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. A. Gelman, A. Jakulin, M. G. Pittau, and Y. S. Su, “A weakly informative default prior distribution for logistic and other regression models,” Ann. Appl. Stat., vol. 2, no. 4, pp. 1360–1383, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  42. Y. Breindl and J. Wright, “Internet filtering trends in western liberal democracies: French and German regulatory debates,” 2nd USENIX Work. Free Open Commun. Internet, FOCI 2012, co-located with USENIX Secur. 2012, 2012.Google ScholarGoogle Scholar
  43. D. Polatin-Reuben and J. Wright, “An internet with BRICS characteristics: Data sovereignty and the balkanisation of the internet,” 4th USENIX Work. Free Open Commun. Internet, FOCI 2014, co-located with USENIX Secur. 2014, 2014.Google ScholarGoogle Scholar
  44. B. Zevenbergen, I. Brown, J. Wright, and D. Erdos, “Ethical Privacy Guidelines for Mobile Connectivity Measurements,” SSRN Electron. J., no. November, pp. 1–41, 2013.Google ScholarGoogle Scholar
  45. A. Darer, O. Farnan, and J. Wright, “FilteredWeb: A framework for the automated search-based discovery of blocked URLs,”, 2017 Network Traffic Measurement and Analysis Conference (TMA), 2017.Google ScholarGoogle ScholarCross RefCross Ref
  46. A. Darer, O. Farnan, J. Wright, "Automated discovery of internet censorship by web crawling", Proceedings of the 10th ACM Conference on Web Science. 2018Google ScholarGoogle Scholar
  47. K. Rasler, “Concessions, Repression, and Political Protest in the Iranian Revolution,” vol. 61, no. 1, pp. 132–152, 1996.Google ScholarGoogle Scholar

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Conferences
    WebSci '21: Proceedings of the 13th ACM Web Science Conference 2021
    June 2021
    328 pages
    ISBN:9781450383301
    DOI:10.1145/3447535

    Copyright © 2021 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 22 June 2021

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • research-article
    • Research
    • Refereed limited

    Acceptance Rates

    Overall Acceptance Rate218of875submissions,25%

    Upcoming Conference

    Websci '24
    16th ACM Web Science Conference
    May 21 - 24, 2024
    Stuttgart , Germany

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format .

View HTML Format