Kai Zhu

foto Kai Zhu

My research broadly seeks to understand how digital technologies change market, media, politics, and society. I am particular interested in the impact of digital transformation in cultural markets, e.g. news, books, movies, music. In my research, I leverage various computational tools, such as machine learning, natural language processing, causal inference, and network analysis, to analyze large-scale structured and unstructured data in real-world to learn about human behavior and system dynamics.

Assistant Professor
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Research interests

Computational Social Science, Text as Data, Social Networks, Digital Platforms

Working papers
Jumping the Great Firewall: Understanding Citizen Resilience to Internet Censorship in China
Does Shooting Incidences Increase Gun Sales? Evidence from Exposure to Gun Violence through Social Network
The Promise and Pitfalls of AI Technology in Bridging Digital Language Divide: Insights from Machine Translation on Wikipedia
Giveaway for a Price: Understanding the Supply and Demand Responses to Platform Monetization
Selected Publications
Kai Zhu, Dylan Walker, Lev Muchnik

Content Growth and Attention Contagion in Information Networks: Addressing Information Poverty on Wikipedia

Information Systems Research
Masha Krupenkin, Kai Zhu, Dylan Walker, David Rothschild

If a Tree Falls in the Forest: Presidential Press Conferences and Early Media Narratives about the COVID-19 Crisis

Journal of Quantitative Description: Digital Media
Kai Zhu; Warut Khern-Am-Nual; Yinan Yu

Negative Peer Feedback and User Content Generation: Evidence from a Restaurant Review Platform

Production and Operation Management