Concepedia

TLDR

The study analyzes the outcomes of what may be the most extensive selective censorship effort ever implemented. The authors built a system that automatically collects and analyzes millions of Chinese social media posts from 1,400 platforms, then applies computer‑assisted text analytics to compare censored and uncensored content across 85 topics over time. The analysis shows that state criticism is not more likely to be censored, but the censorship program targets comments that could spark collective action, aiming to prevent current or future mobilization.

Abstract

We offer the first large scale, multiple source analysis of the outcome of what may be the most extensive effort to selectively censor human expression ever implemented. To do this, we have devised a system to locate, download, and analyze the content of millions of social media posts originating from nearly 1,400 different social media services all over China before the Chinese government is able to find, evaluate, and censor (i.e., remove from the Internet) the subset they deem objectionable. Using modern computer-assisted text analytic methods that we adapt to and validate in the Chinese language, we compare the substantive content of posts censored to those not censored over time in each of 85 topic areas. Contrary to previous understandings, posts with negative, even vitriolic, criticism of the state, its leaders, and its policies are not more likely to be censored. Instead, we show that the censorship program is aimed at curtailing collective action by silencing comments that represent, reinforce, or spur social mobilization, regardless of content. Censorship is oriented toward attempting to forestall collective activities that are occurring now or may occur in the future—and, as such, seem to clearly expose government intent.

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