Bin Zhang
Assistant Professor
Department of Information & Operations Management
Biography
Bin Zhang is an Assistant Professor of Information & Operations Management at Mays Business School. He has joined Texas A&M since July 2021.
Dr. Zhang’s primary research interests are social media analytics and machine learning. He is specifically interested in designing algorithms to analyze large social network and developing deep learning methods to investigate social media content such as text, image and video. His work has been published in premier IS journals such as MIS Quarterly, Information Systems Research, Journal of Management Information Systems, etc. His projects have been funded by federal agencies such as NSF and NIH. Dr. Zhang has extensive teaching experience in Database, Data Mining, Data Analytics, and Programming Languages. All of these courses receive very high evaluation from the students.
Dr. Zhang has served on multiple review panels for NSF, and is the current Vice Chair of INFORMS College of AI. He is also a Visiting Research Fellow affiliated with iLab at Carnegie Mellon University.
Research Interests
Very large social network analysis, statistical modeling for social network problems, social media, technology diffusion and business analyticsResearch
| Title | Year | Type |
|---|---|---|
|
Information Systems Research |
2021 | Article |
|
ACM Transactions on Management Information Systems |
2021 | Article |
|
Write Like a Pro or an Amateur? Effect of Medical Language Formality ACM Transactions on Management Information Systems |
2021 | Article |
|
Go to YouTube and See Me Tomorrow: Social Media and Self-Care of Chronic Conditions MIS Quarterly |
2020 | Article |
|
Information Systems Research |
2018 | Article |
|
On Direct vs. Indirect Peer Influences in Large Social Networks Information Systems Research |
2018 | Article |
|
Examining Hacker Participation Length within Cybercriminal IRC Communities Journal of Management Information Systems |
2016 | Article |
|
ACM Transactions on Management Information Systems |
2013 | Article |
|
The Structure and Dynamics of Generative Innovations: An Organizational Genetics Approach National Science Foundation |
2013 | Monographs |