A Randomized Experimental Study of Censorship in China

25 Pages Posted: 29 Aug 2013

See all articles by Gary King

Gary King

Harvard University

Jennifer Pan

Stanford University

Molly Roberts

Harvard University

Date Written: 2013

Abstract

Chinese government censorship of social media constitutes the largest selective suppression of human communication in the history of the world. Although existing systematic research on the subject has revealed a great deal, it is based on passive, observational methods, with well known inferential limitations. We attempt to generate more robust causal and descriptive inferences through participation and experimentation. For causal inferences, we conduct a large scale randomized experimental study by creating accounts on numerous social media sites spread throughout the country, submitting different randomly assigned types of social media texts, and detecting from a network of computers all over the world which types are censored. Then, for descriptive inferences, we supplement the current approach of confidential interviews by setting up our own social media site in China, contracting with Chinese firms to install the same censoring technologies as existing sites, and reverse engineering how it all works. Our results offer unambiguous support for, and clarification of, the emerging view that criticism of the state, its leaders, and their policies are routinely published whereas posts with collective action potential are much more likely to be censored. We are also able to clarify the internal mechanisms of the Chinese censorship apparatus and show that local social media sites have far more flexibility than was previously understood in how (but not what) they censor.

Keywords: China, Experiment

Suggested Citation

King, Gary and Pan, Jennifer and Roberts, Molly, A Randomized Experimental Study of Censorship in China (2013). APSA 2013 Annual Meeting Paper, American Political Science Association 2013 Annual Meeting, Available at SSRN: https://ssrn.com/abstract=2299509

Gary King

Harvard University ( email )

1737 Cambridge St.
Institute for Quantitative Social Science
Cambridge, MA 02138
United States
617-500-7570 (Phone)

HOME PAGE: http://gking.harvard.edu

Jennifer Pan

Stanford University ( email )

Stanford, CA 94305
United States

Molly Roberts (Contact Author)

Harvard University ( email )

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