MIS Speaker's Series: Gene Moo Lee


1 p.m. to 2 p.m. Feb. 25, 2022



Gene Moo Lee, Associate Professor of Information Systems, University of British Columbia.

Title: Developing Visual Data Analytics in Information Systems Research

Abstract: Visual data (e.g., photos in Facebook and Instagram, videos in YouTube and TikTok) are becoming a first-class citizen in social media and online platforms with the wide adoption of mobile devices with advanced camera features. Compared to textual information that requires significant cognitive efforts for consumers to comprehend, visual information can easily communicate the message from the content creator to the general audience. These visual datasets from online platforms provide a great opportunity to advance our knowledge of consumer behavior, business strategies, and societal phenomena. However, they also pose a methodological challenge in incorporating such unstructured data into conventional research models.

In this talk, I will introduce three of my recent studies that develop visual data analytics in information systems research using computer vision and deep learning approaches. Drawing on theories from psychology and cognitive science, Shin et al. (2020) develops a deep learning framework (based on convolutional neural networks) to analyze the persuasiveness of images and text in social media marketing. Next, Park et al. (2020) extends the framework to video ad context by incorporating the multimodal nature of the content (video and audio) and uncovers new theoretical findings on ad-content congruence. Lastly, in the context of online dating platforms, Kwon et al. (2021) applies visual data analytics on face images to predict attractiveness and uses generative AI models (StyleGAN) to visually interpret deep learning-enabled facial features, which are otherwise incomprehensible to researchers. These studies show how visual data analytics and theory can create synergies in information systems research.

Shin, D., S. He, G. M. Lee, A. B. Whinston, S. Cetintas, K. Lee (2020) Enhancing Social Media Analysis with Visual Data Analytics: A Deep Learning Approach, MIS Quarterly 44(4): 1459-1492.

Park, S., G. M. Lee, D. Shin, S.-P. Han (2020) Targeting Pre-Roll Ads using Video Analytics, Workshop on Information Technologies and Systems (WITS) 2020.

Kwon, S., S.-H. Park, G. M. Lee, D. Lee (2021) Learning Faces to Predict Matching Probability in an Online Dating Market, Workshop on Information Technologies and Systems (WITS) 2021.

Bio: Gene Moo Lee is an Associate Professor (with tenure) of Information Systems at UBC Sauder School of Business. He received his Ph.D. in Computer Science from UT Austin in 2015. His research in business analytics and AI has been published in top-tier journals such as MIS Quarterly, Information Systems Research, Journal of MIS, and Journal of Business Ethics, as well as top-tier CS conferences such as the ACM EC, ACM IMC, and IEEE INFOCOM. His research has been financially supported by 17 grants (e.g., U.S. National Science Foundation, Canada SSHRC, and multiple industry grants) with a total of $1.1 million. He received the AIS Early Career Award in 2019 and is a Distinguished Member of AIS. He has extensive industry experience at Samsung Electronics, AT&T, Intel, and Goldman Sachs, has collaborated with various tech firms (Yahoo, IGAWorks, KISTI, KIRI, Canada Energy Regulator), and holds 11 patents in mobile technology.

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