Dynamic Monitoring of Political Networks, Censorship and Propaganda in China
Researcher: Molly Roberts (UC San Diego)
This project will develop an infrastructure for automated information extraction, storage, retrieval and analysis of millions of web-accessible documents produced by the Chinese news media, public and government, entering these documents into a novel data-management system so they can be efficiently accessed. Second, the team will develop methods that allow for real-time analysis, detection and updating of relations between political leaders, propaganda and strategy from these sets of documents. Last, the analysis of this data will be made available to the public in an interactive visualization tool, allowing policymakers and academics to better understand the internal workings of the Chinese government.
Large-scale analysis of this data will allow researchers to:
- conduct real-time detection of political propaganda,
- identify omission of sensitive topics in Chinese news media, and
- conduct dynamic detection of political associations among elites.
It is well known the Chinese government uses the coordination of articles across newspapers as a primary method of government propaganda, but also for omitting reports of sensitive events that could damage the image of the Chinese government. Such propaganda will point to topics and issues that are most important to the Chinese government, providing clues to the government’s agenda. And identifying and classifying relationships among leaders has long been a central challenge in the analysis of Chinese elite politics. The data will allow us to track when, where and how much different political figures appear together in media reports to generate new, more empirically grounded maps of personal and political associations among elites.The combination of these methods will allow mapping of emerging governance trends and political strategies in China. Spatial and temporal variance in governance discourse and outcomes offers important clues about the underlying configuration of political forces in China. A combination of text analytics and named-entity recognition techniques will capture differences across provinces and over time in policy formulation and implementation that may signal political cleavages.