research-article

A Bayesian Analysis of Collective Action and Internet Shutdowns in India

Authors:

Michael Collyer,

Joss WrightAuthors Info & Claims

WebSci '21: Proceedings of the 13th ACM Web Science Conference 2021

Pages 309 - 318

https://doi.org/10.1145/3447535.3462480

Published: 22 June 2021 Publication 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.

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Cited By

Tagat APhokeer AKreitem H(2024)Net Loss: An econometric method to measure the impact of Internet shutdownsACM Journal on Computing and Sustainable Societies10.1145/36594662:2(1-22)Online publication date: 20-Jun-2024
https://dl.acm.org/doi/10.1145/3659466
Sedashov EBelenkov VKoncha V(2023)The Effect of Internet Shutdowns on Protest Activity in India: an Empirical Investigation2023 16th International Conference Management of large-scale system development (MLSD)10.1109/MLSD58227.2023.10304037(1-4)Online publication date: 26-Sep-2023
https://doi.org/10.1109/MLSD58227.2023.10304037

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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].

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Published: 22 June 2021

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WebSci '21: WebSci '21 13th ACM Web Science Conference 2021

June 21 - 25, 2021

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Cited By

Tagat APhokeer AKreitem H(2024)Net Loss: An econometric method to measure the impact of Internet shutdownsACM Journal on Computing and Sustainable Societies10.1145/36594662:2(1-22)Online publication date: 20-Jun-2024
https://dl.acm.org/doi/10.1145/3659466
Sedashov EBelenkov VKoncha V(2023)The Effect of Internet Shutdowns on Protest Activity in India: an Empirical Investigation2023 16th International Conference Management of large-scale system development (MLSD)10.1109/MLSD58227.2023.10304037(1-4)Online publication date: 26-Sep-2023
https://doi.org/10.1109/MLSD58227.2023.10304037

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