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dc.contributor.authorKing, Gary
dc.contributor.authorPan, Jennifer Jie
dc.contributor.authorRoberts, Margaret E.
dc.date.accessioned2018-06-07T21:26:43Z
dc.date.issued2014
dc.identifier.citationKing, G., J. Pan, and M. E. Roberts. 2014. “Reverse-Engineering Censorship in China: Randomized Experimentation and Participant Observation.” Science 345 (6199) (August 21): 1251722–1251722. doi:10.1126/science.1251722.en_US
dc.identifier.issn0036-8075en_US
dc.identifier.issn1095-9203en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:37091695
dc.description.abstractExisting research on the extensive Chinese censorship organization uses observational methods with well-known limitations. We conducted the first large-scale experimental study of censorship by creating accounts on numerous social media sites, randomly submitting different texts, and observing from a worldwide network of computers which texts were censored and which were not. We also supplemented interviews with confidential sources by creating our own social media site, contracting with Chinese firms to install the same censoring technologies as existing sites, and—with their software, documentation, and even customer support—reverse-engineering how it all works. Our results offer rigorous support for the recent hypothesis that criticisms of the state, its leaders, and their policies are published, whereas posts about real-world events with collective action potential are censored.en_US
dc.description.sponsorshipGovernmenten_US
dc.language.isoen_USen_US
dc.publisherAmerican Association for the Advancement of Science (AAAS)en_US
dc.relation.isversionofdoi:10.1126/science.1251722en_US
dash.licenseOAP
dc.titleReverse-engineering censorship in China: Randomized experimentation and participant observationen_US
dc.typeJournal Articleen_US
dc.description.versionAccepted Manuscripten_US
dc.relation.journalScienceen_US
dash.depositing.authorKing, Gary
dc.date.available2018-06-07T21:26:43Z
dc.identifier.doi10.1126/science.1251722*
dash.identifier.orcid0000-0002-5327-7631*
dash.contributor.affiliatedPan, Jennifer
dash.contributor.affiliatedKing, Gary
dc.identifier.orcid0000-0002-5327-7631


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