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How Saudi Crackdowns Fail to Silence Online Dissent

Published online by Cambridge University Press:  27 December 2019

JENNIFER PAN Open the ORCID record for JENNIFER PAN [Opens in a new window]  and
ALEXANDRA A. SIEGEL Open the ORCID record for ALEXANDRA A. SIEGEL [Opens in a new window]
JENNIFER PAN*
Affiliation:
Stanford University
ALEXANDRA A. SIEGEL*
Affiliation:
Stanford University
*
*Jennifer Pan, Assistant Professor, Department of Communication, Stanford University, [email protected].
†Alexandra A. Siegel, Postdoctoral Fellow, Immigration Policy Lab, Stanford University, [email protected].
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Abstract

Saudi Arabia has imprisoned and tortured activists, religious leaders, and journalists for voicing dissent online. This reflects a growing worldwide trend in the use of physical repression to censor online speech. In this paper, we systematically examine the consequences of imprisoning well-known Saudis for online dissent by analyzing over 300 million tweets as well as detailed Google search data from 2010 to 2017 using automated text analysis and crowd-sourced human evaluation of content. We find that repression deterred imprisoned Saudis from continuing to dissent online. However, it did not suppress dissent overall. Twitter followers of the imprisoned Saudis engaged in more online dissent, including criticizing the ruling family and calling for regime change. Repression drew public attention to arrested Saudis and their causes, and other prominent figures in Saudi Arabia were not deterred by the repression of their peers and continued to dissent online.

Type
Research Article
Information
American Political Science Review , Volume 114 , Issue 1 , February 2020 , pp. 109 - 125
Copyright
Copyright © American Political Science Association 2019 

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Footnotes

Our thanks to Charles Crabtree, Killian Clarke, Christian Davenport, Martin Dimitrov, Jennifer Earl, Will Hobbs, Holger Kern, Beatriz Magaloni, Elizabeth Nugent, Molly Roberts, Arturas Rozenas, Anton Sobolev, Rory Truex, Lauren Young, Zachary Steinert-Threlkeld, and participants at the 2018 APSA pre-conference on politics and computational social science for their helpful comments and suggestions; to SMaPP Global for making our collaboration possible; to the Stanford King Center on Global Poverty and Development and the National Science Foundation (Award #1647450) for research support. We would also like to thank Twitter for providing us with access to historical data as well as Steve Eglash for facilitating this access. Replication files are available at the American Political Science Review Dataverse: https://doi.org/10.7910/DVN/9AMKHL.

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