KAI ZHU
Courses a.y. 2022/2023
20593
INNOVATION AND MARKETING ANALYTICS
20840 DATA MINING FOR MARKETING, BUSINESS, AND SOCIETY
30603 COMPUTATIONAL APPLICATIONS IN MARKETING
41037 DATA MINING FOR MARKETING ANALYTICS
20840 DATA MINING FOR MARKETING, BUSINESS, AND SOCIETY
30603 COMPUTATIONAL APPLICATIONS IN MARKETING
41037 DATA MINING FOR MARKETING ANALYTICS
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
Kai Zhu
Bridge the Digital Language Divide: Can Machine Translation Narrow Knowledge Gap across Different Languages?
Bridge the Digital Language Divide: Can Machine Translation Narrow Knowledge Gap across Different Languages?
Kai Zhu
Monetization and Unintended Consequences for Digital Cultural Markets: Evidence from a Two-sided Market for Book Promotion
Monetization and Unintended Consequences for Digital Cultural Markets: Evidence from a Two-sided Market for Book Promotion
Kai Zhu
Negative Peer Feedback and User Content Generation: Evidence from a Restaurant Review Platform
Negative Peer Feedback and User Content Generation: Evidence from a Restaurant Review Platform
Selected Publications
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
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, Dylan Walker, Lev Muchnik
Content Growth and Attention Contagion in Information Networks: Addressing Information Poverty on Wikipedia
Information Systems Research, 2020
Content Growth and Attention Contagion in Information Networks: Addressing Information Poverty on Wikipedia
Information Systems Research, 2020