Gene Lee

 
Prospective Graduate Students / Postdocs

This faculty member is currently not actively recruiting graduate students or Postdoctoral Fellows, but might consider co-supervision together with another faculty member.

Associate Professor

Research Interests

Applied Machine Learning
Business Analytics
Computer Science and Statistics
Cybersecurity
Information Systems
Mobile Ecosystem
Social Media Analysis
Text Mining

Relevant Thesis-Based Degree Programs

Research Options

I am available and interested in collaborations (e.g. clusters, grants).
I am interested in and conduct interdisciplinary research.
 
 

Research Methodology

machine learning
Network Analysis
Econometrics
Natural Language Processing
Big Data

Graduate Student Supervision

Master's Student Supervision

Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.

How does AI-generated voice affect online video creation? : evidence from TikTok (2023)

The rising demand for online video content has fostered one of the fastest-growing markets as evidenced by the popularity of platforms like TikTok. Because video content is often difficult to create, platforms have attempted to leverage recent advancements in artificial intelligence (AI) to help creators with their video creation process. However, surprisingly little is known about the effects of AI on content creators’ productivity and creative patterns in this emerging market. Our paper investigates the adoption impact of AI-generated voice – a generative AI technology creating acoustic artifacts – on video creators by empirically analyzing a unique dataset of 4,021 creators and their 428,918 videos on TikTok. Utilizing multiple audio and video analytics algorithms, we detect the adoption of AI voice from the massive video data and generate rich measurements for each video to quantify its characteristics. We then estimate the effects of AI voice using a difference-in-differences model coupled with look-ahead propensity score matching. Our results suggest that the adoption of AI voice increases creators’ video production and that it induces creators to produce shorter videos with more negative words. Interestingly, creators produce more novel videos with less self-disclosure when using AI voice. We also find that AI-voice videos received less viewer engagement unintendedly. Our paper provides the first empirical evidence of how generative AI reshapes video content creation on online platforms, which provides important implications for creators, platforms, and policymakers in the digital economy.

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Publications

 
 

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