KAI ZHU

KAI ZHU

Courses a.y. 2025/2026

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

The AI Democratization Paradox: Evidence from Decentralized Knowledge Platforms

Quantifying Consumer-Product Fit: A Representation Learning Approach

Customer Journey with AI Search

Selected Publications

Kai Zhu; Qiaoni Shi; Shrabastee Barnerjee
Monetizing Platforms: An Empirical Analysis of Supply and Demand Responses to Entry Costs in Two-sided Markets
Management Science, 2025

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

Kai Zhu, Dylan Walker, Lev Muchnik
Content Growth and Attention Contagion in Information Networks: Addressing Information Poverty on Wikipedia
Information Systems Research, 2020