Computational Propaganda in China: An Alternative Model of a Widespread Practice

Abstract:

Computational propaganda is a growing issue in Western democracies, with evidence of online opinion manipulation orchestrated by robots, fake accounts and misinformation in many recent political events. China, the country with the most sophisticated regime of internet censorship and control in the world, presents an interesting and understudied example of how computational propaganda is used. This working paper summarizes the landscape of current knowledge in relation to public opinion manipulation in China. It addressees the questions of whether and how computational propaganda being used in and about China, whose interests are furthered by this computational propaganda and what is the effect of this computational propaganda on the landscape of online information in and about China. It also addresses the issue of how the case of computational propaganda in China can inform the current efforts of Western democracies to tackle fake news, online bots and computational propaganda. This working paper presents four case studies of computational propaganda in and about China: the Great Firewall and the Golden Shield project; positive propaganda on Twitter aimed at foreign audiences; the anti-Chinese state bots on Twitter; and domestic public opinion manipulation on Weibo. Surprisingly, I find that there is little evidence of automation on Weibo and little evidence of automation associated with state interests on Twitter. However, I find that issues associated with anti-state perspectives, such as the pro-democracy movement, contain a large amount of automation, dominating Chinese language information in certain hashtags associated with China and Chinese politics on Twitter.

Citation: Gillian Bolsover, “Computational Propaganda in China: An Alternative Model of a Widespread Practice.” Samuel Woolley and Philip N. Howard, Eds. Working Paper 2017.11. Oxford, UK: Project on Computational Propaganda. demtech.oii.ox.ac.uk<http://demtech.oii.ox.ac.uk/>. 32 pp.