Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK
Weifeng Zhong

Weifeng Zhong
Senior Research Fellow, Mercatus Center at George Mason University


Weifeng Zhong is a senior research fellow at the Mercatus Center at George Mason University. His work focuses on bridging the field of natural language processing and machine learning to economic policy studies. His other research interests include the political economy, US-China economic relations, and China’s economic issues. Weifeng is a core maintainer of the open source Policy Change Index (PCI) project, a framework that uses machine learning to “read” large volumes of text and detect subtle, structural changes embedded in it. As a first use case, the PCI for China is an algorithm that can predict China’s policy changes using the information in the government’s official newspaper. The PCI framework has received significant academic interest and media coverage. The resources of this project are freely available at Weifeng has been published in a variety of scholarly journals, including the Journal of Institutional and Theoretical Economics. His research and writings have been featured in the Financial Times, Foreign Affairs, The National Interest, Real Clear Markets, Real Clear Politics, the South China Morning Post, and the Wall Street Journal, among others.


17:2518:05 Wednesday, 1 May 2019
Data Science, Machine Learning & AI
Location: Capital Suite 15/16
Weifeng Zhong (Mercatus Center at George Mason University)
Average rating: ****.
(4.75, 4 ratings)
Weifeng Zhong shares a machine learning algorithm built to “read” the People’s Daily (the official newspaper of the Communist Party of China) and predict changes in China’s policy priorities. The output of this algorithm, named the Policy Change Index (PCI) of China, turns out to be a leading indicator of the actual policy changes in China since 1951. Read more.