Courses a.y. 2023/2024

Biographical note

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.

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, 2020

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, 2022

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, 2024