Dokyun Lee
Assistant Professor of Business Analytics
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- Personal Website: http://www.leedokyun.com/
- Focused Concept Miner for Text Exploration: www.fcminer.com
- Business Insights through Text Lab (BIT Lab) www.cmubitlab.com
Education
- The Wharton School, University of Pennsylvania - Ph D (Operation and Information Management) - 2015
- Yale University - MS (Statistics) - 2010
- Columbia University - BS (Computer Science) - 2009
Research
Application and Impact of Machine Learning in Business,Economic Impact of Unstructured Data,
Interpretable ML for Business,
Unintended Consequence of Machine Learning
Publications
- How Do Product Attributes and Reviews Moderate the Impact of Recommender Systems Through Purchase Stages?
(author(s): Dokyun Lee, Kartik Hosanagar)
Accepted and forthcoming at Management Science - Good Explanation for Algorithmic Transparency
(author(s): Joy Lu Tong, Dokyun Lee, Tae Wan Kim, David Danks)
AIES 2020: AAAI/ACM Conference on AI, Ethics, and Society, 2020 - How Do Recommender Systems Affect Sales Diversity? A Cross-Category Investigation via Randomized Field Experiment
(author(s): Dokyun Lee, Kartik Hosanagar)
Information Systems Research 30(1), 2019; iii-viii, 1-349 - Large Scale Cross-Category Analysis of Consumer Review Content on Sales Conversion Leveraging Deep Learning
(author(s): Xiao Liu, Dokyun Lee, Kannan Srinivasan)
Journal of Marketing Research 56(6), 2019; 918–943 - Peer Symbolic Awards Increase User Content Generation but Reduce Content Novelty
(author(s): Gordon Burtch, Qinglai He, Yili Hong, Dokyun Lee)
International Conference on Information Systems (ICIS), 2019 - Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook
(author(s): Dokyun Lee, Kartik Hosanagar, Harikesh Nair)
Management Science 64(11), 2018; 4967-5460 - Deep Learning of Consumer Review Content
(author(s): Xiao Liu, Dokyun Lee, Kannan Srinivasan)
AAAI-18: Thirty-Second AAAIM Conference on AI, 2018 - Micro-Giving: On the Use of Mobile Devices and Monetary Subsidies in Charitable Giving
(author(s): Dongwon Lee, Anandasivam Gopal, Dokyun Lee)
International Conference in Information Systems (ICIS), 2017 - When do Recommender Systems Work the Best? The Moderating Effects of Product Attributes and Consumer Reviews on Recommender Performance
(author(s): Dokyun Lee, Kartik Hosanagar)
Proceedings of the 25th International Conference on World Wide Web, 2016; 85–97 - How Much Is An Image Worth? An Empirical Analysis of Property’s Image Aesthetic Quality on Demand at AirBNB
(author(s): Shunyuan Zhang, Dokyun Lee, Param Singh, Kannan Srinivasan)
International Conference on Information Systems (ICIS), 2016 - The Effect of Consumer Review Content on Sales Conversion: Analysis of Consumer Information Journey Across Categories with Deep Learning
(author(s): Xiao Liu, Dokyun Lee, Kannan Srinivasan)
NET Institute Conference, 2016
People Who Liked This Study Also Liked: The Impact of Recommender Systems on Sales Volume and Diversity
(author(s): Dokyun Lee, Kartik Hosanagar)
International Conference on Information Systems (ICIS), 2014 - Will the Global Village Fracture into Tribes: Recommender Systems and their Effects on Consumers
(author(s): Kartik Hosanagar, Daniel Fleder, Dokyun Lee, Andreas Buja)
Management Science 60(4), 2014; 805-823
Working Papers
- How Much is an Image Worth? The Impact of Professional versus Amateur Airbnb Property Images on Property Demand
(author(s): Shunyuan Zhang, Dokyun Lee, Param Singh, Kannan Srinivasan)
Third round at Management Science - Micro-Giving: On the Use of Mobile Devices and Monetary Subsidies in Charitable Giving
(author(s): Dongwon Lee, Anandasivam Gopal, Dokyun Lee)
Second round at MISQ - Demand Interactions in Sharing Economies: Evidence from a Natural Experiment Involving Airbnb and Uber/Lyft
(author(s): Shunyuan Zhang, Dokyun Lee, Param Singh, Tridas Mukhopadhyay)
First round at Journal of Marketing Research - Focused Concept Miner (FCM): An Interpretable Deep Learning for Text Exploration
(author(s): Dokyun Lee, Emaad Ahmed Manzoor, Zhaoqi Cheng)
Third round at Marketing Science - Peer Symbolic Awards Increase User Content Generation but Reduce Content Novelty
(author(s): Gordon Burtch, Qinglai He, Yili Hong, Dokyun Lee)
Second round at Management Science - Good Explanation for Algorithmic Transparency
(author(s): Joy Tong Lu, Dokyun Lee, Taewan Kim, David Danks)
Under revision - Soul and Machine (Learning)
(author(s): Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Alex Burnap, Tong Guo, Dokyun Lee, Randall A. Lewis, Kanishka Misra, Eric M. Schwartz, Artem Timoshenko, Lilei Xu, Hema Yoganarasimhan)
Second round at Marketing Letters - Can High Street Fashion Erode Premium Brand Equity? A Structural Analysis
(author(s): June Shi, Dokyun Lee, Kannan Srinivasan) - Quantifying Dialectic Persuasion - Measuring d(Opinion)/d(Argument) In Gun Control Debate
(author(s): Emaad Ahmed Manzoor, Dokyun Lee,George Chen, Alan Montgomery) - Interpretable Deep Learning Approach to Customer Churn Prediction
(author(s): Daehwan Ahn, Dokyun Lee, Kartik Hosanagar) - A Bayesian Multi-View Topic Model for Predictive Analytics in a Business-to-Business Context
(author(s): Sam Levy, Dokyun Lee, Daniel M McCarthy, Alan Montgomery) - Do Aggressive Comments Bring Better Questions? Evidence from Stack Overflow
(author(s): Zhaoqi Cheng, Dokyun Lee, Tridas Mukhpadhyay) - Generative Model of Innovation
(author(s): Zhaoqi Cheng, Dokyun Lee, Prasanna Tambe, David Hsu)
Awards and Honors
- INFORMS - Best Paper Runner Up - E-Business (2019)
- Management Science ISR Division 2016-2018 Best Paper Award Finalist – Journal Paper 2 (2019)
- Wharton Customer Analytics Initiative - Collaborative Data Grant (only 1 team) (2019)
- MSI - Marketing Science Institute Research Grant (Principal Investigator, $10,000) (2018)
- INFORMS - Best Paper Runner Up - E-Business (2018)
- Carnegie Bosch Institute Research Award [Explainable AI – Definition of Good Explanation] (Co-PI, $116,400) (2018)
- Academy of Management Best Student Paper Award (2018)
- NSF i-Corp - Optipik (Chief Scientist) (2017)
- AIS - ICIS 2017 Best Conference Paper (2017)
- AIS - ICIS 2017 Best Track Paper in IT and Social Changes Award (2017)
- CIST INFORMS Best Student Paper Award (2017)
- Tepper School - Xerox Junior Faculty Chair, Tepper School (2017)
- Adobe Data Science Faculty Research Award Grant (PI, $40,000) (2017)
- NVIDIA Academic GPU grants for Deep Learning Projects (PI, GPU Received) (2017)
- XSEDES Pittsburgh Super Computing for Deep Learning (PI) (2017)
- CIST INFORMS - Best Student Paper Award (2016)
- ISS Nunamaker-Chen Dissertation Award, Runner Up (2016)
- Management Science ISR Division 2012-2014 Best Paper Award Finalist – Journal Paper 1 (2016)
- NET Institute - Research Grant (Principal Investigator, $3,000) (2016)
- Marketing Science Institute - Research Grant (Co-Principal Investigator, $17,000) (2016)
- Tepper School - The Lave Weil Faculty Research Award ($10,000) (2016)
- XSEDES Pittsburgh Super Computing for Deep Learning (PI) (2016)
- Wharton Customer Analytics Initiative - Data Grant (2019)
- CMU - The Berkman Award Fund (Principal Investigator, $9,142) (2015)
- Wharton School - Wharton Behavioral Lab Research Grant (Principal Investigator, $9,200) (2015)
- WISE - Best Student Paper, Runner Up –Journal Paper 2 (2014)
Professional Service
- Conference on Information Systems and Technology (INFORMS, Phoenix Arizona), Conference Co-Chair (2018)
University Service
- CAIR (CMU AI Retail) Initiative, Founding Member and Faculty Co-Director (2020)
- K&L Gates Advisory Group, Committee Member (2020)
- MEAC Committee (2016 - current)
- IS Faculty Hiring Committee (2015 - )
- IS PhD Hiring Committee (2015 - )
- IS Seminar Organizer (2015 – 2018)
- MS in Business Analytics Curriculum Committee (2016 - 2018)