Business Insights through Text
The BIT LAB
We explore, examine, and extract consumer behavior or market insights through abundantly available, yet severely untapped text data. Via a variety of methodologies including causal inference, generative models, deep learning, neural NLP, bayesian statistics, interpretable machine learning, spanning topics such as social media analytics, digital consumer management, persuasion, platform design, innovation, human-ai collaboration, our studies are focused on providing empirical evidence and empirical generalization to develop or extend consumer behavior and market theories. In particular, we study friction and solutions in applying cutting-edge technologies to business arising from human-technology interface.
BITLAB Meeting March 31 2023
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PI: Dokyun "DK" Lee
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Postdoctoral Researcher
Mohamed Zaki Balboula
Dr. Mohamed Zaki Balboula is a postdoctoral researcher in the Information Systems Department at Boston University, Questrom School of Business. He also held an Assistant Professor of Accounting position at Delta University for Science & Technology- Egypt. He employs predictive models to predict corporate going concern/bankruptcy to support the auditor's judgment via rough sets theory, neural networks, and particle swarm algorithm using structured financial data. He is currently exploring ways to apply machine learning, NLP, to address various research questions in corporate finance using textual data. His research interests include corporate disclosures, environmental, social, and governance (ESG), corporate social responsibility (CSR), corporate risk, and financial performance.
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Doctoral Students
Zhaoqi Cheng
Zhaoqi Cheng is an Information Systems PhD student at Boston University, Questrom School of Business. He combines machine learning with econometrics models to explore large-scale data with text-heavy attributes, such as patent files, online forums and user reviews. He is currently working on generative models related to the representation and characterization of innovations.
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Chen Jing
Chen Jing is a PhD student in Quantitative Marketing at Questrom School of Business, Boston University. His research interests include applying machine learning, econometrics, and statistical models to study brand communication, corporate social responsibility, and brand activism.
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Chengfeng Mao
Chengfeng Mao is a PhD student in Marketing at the MIT Sloan School of Management. He obtained his master's degree in Computer Science at Carnegie Mellon University. His research interests include applying machine learning to draw business and economic insights from unstructured data, such as text, image, and network graph.
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Eric Zhou
Eric will be a first year quant marketing doctoral student at Wash U. He holds a Bachelor’s degree in Finance and Marketing from Washington University In St. Louis and MBA from Tepper. He worked for one year at Nielsen BASES as a research analyst specializing in product innovation.
In his free time, he enjoys exercising and dancing and plans on choreographing his own piece some day! |
Hazel Hyeseung Kang
Hazel Hyeseung Kang is a PhD student in Information Systems at Boston University, Questrom School of Business.
She holds a bachelor's degree in Economics at Yonsei University and master's degree in Economics at Yonsei University. Her research interests include applying econometrics and machine learning to derive business insights from the voice of customers on online platforms. |
Yuan Gao
Yuan Gao is a senior undergraduate student in Economics and Data Science in Beijing Normal University. His research interest lies in exploring how AI impacts the formation and diffusion of human beliefs on social media, and investigating the resulting business, economic, and social implications. Yuan will start as a first year phd student at BU in 2024 September.
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