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In this episode of the Data Exchange I speak with Weifeng Zhong, Senior Research Fellow at the Mercatus Center at George Mason University. He is the core maintainer of the open source Policy Change Index (PCI), a framework that uses machine learning and NLP to “process and read” large amounts of text to discern government priorities and policies. The initial PCI is focused on major policy shifts in China and uses NLP and machine learning to process and analyze the People’s Daily.
Detailed show notes can be found on The Data Exchange web site.
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By Ben Lorica4.6
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Subscribe: iTunes, Android, Spotify, Stitcher, Google, and RSS.
In this episode of the Data Exchange I speak with Weifeng Zhong, Senior Research Fellow at the Mercatus Center at George Mason University. He is the core maintainer of the open source Policy Change Index (PCI), a framework that uses machine learning and NLP to “process and read” large amounts of text to discern government priorities and policies. The initial PCI is focused on major policy shifts in China and uses NLP and machine learning to process and analyze the People’s Daily.
Detailed show notes can be found on The Data Exchange web site.
Subscribe to The Gradient Flow Newsletter.

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