Bin Zhang

Assistant Professor of MIS

Visiting Research Fellow, Carnegie Mellon University

Bin Zhang

McClelland Hall 430Z
1130 E. Helen St. 
P.O. Box 210108 
Tucson, Arizona 85721-0108

Areas of Expertise

  • Large social network analysis
  • Statistical modeling for social network problems
  • Social media, technology diffusion and business analytics


PhD, Information Systems, Carnegie Mellon University, 2012

MS, Machine Learning, Carnegie Mellon University, 2011

Additional Links

Bin Zhang joined the Eller College of Management in 2014. Before coming to Eller, Zhang worked as an assistant professor at Temple University. His areas of expertise include large social network analysis, statistical modeling for social network problems, social media, technology diffusion and business analytics. He is a member of the Institute for Operations Research and the Management Sciences (INFORMS), the Association of Information Systems (AIS), the Institute of Electrical and Electronics Engineers, American Mensa as well as the Artificial Intelligence Lab in the Eller College of Management.


  • MIS 331 Database Management Systems
  • MIS 545 Data Mining for Business Intelligence

Teaching Interests

  • Database
  • Data mining
  • Business analytics
  • Programming languages

Refereed Journals

  • Liu, X., Zhang, B., Susarla, A., and Padman, R. Go To YouTube and Call Me in the Morning: Use of Social Media for Chronic Conditions. MIS Quarterly (forthcoming).
  • Zhao, K., Zhang, B., and Bai, X. (2018) Estimating External Motivating Factors in Virtual Inter-organizational Communities of Practice: Peer Effects and Organizational Influences. Information Systems Research.
  • Zhang, B., Pavlou, P., and Krishnan, R. (2018) On Direct vs Indirect Influence in Large Social Networks. Information Systems Research.
  • Benjamin, V., Zhang, B., Chen, H., and Nunamaker, J. (2016) Examining Hacker Participation Length within Cybercriminal IRC Communities. Journal of Management Information Systems.
  • Zhang, B., Thomas, A. C., Krackhardt, D., Doreian, P., and Krishnan, R. (2013) Contrasting Multiple Social Network Autocorrelations for Binary Outcomes, with Applications to Technology Adoption. ACM Transactions on Management Information Systems.

Papers Under Review

  • Zhang, B., Zhao, X., Zhao, J. Becoming Human: A Hybrid Human-Machine Framework for E-commerce Last Mile Delivery Problem. Under review at MIS Quarterly.
  • Zhang, B. He, M., and Zhan, Y. Finding Wisdom in the House: An Empirical Study on the Impact of Enterprise Social Media on Knowledge Exchange.
  • Cai, X., Zhao, X., and Zhang, B. Identify Multiple Types of Social Influences on Smart Contract Adoption in Blockchain User Network: An Empirical Examination of CryptoKitties in Ethereum.
  • Moraes, H., Sanchez, O., Brown, B., and Zhang, B. Trust and Distrust in Big Data Recommendation Agents.
  • Xie, J., Zhang, B., Brown, S., and Zeng, D. Write Like a Pro or an Amateur? The Effect of Medical Language Formality in Senior Care: A Multi-Method Approach. Under review at Information Systems Research.
  • Zhang, B., Geng, R., Chen, X., and Pavlou, P., A Network Autocorrelation Model to Predict Repeat Purchases in Multi-Relational Social Networks: Evidence from Online Games. Under review at Management Science.
  • Xie, J., Zhang, B., Ma, J., Zeng, D. and Lo-Ciganic, W. Readmission Prediction for Patients with Heterogeneous Hazard: A Trajectory-Based Deep Learning Approach. R&R at Information Systems Research.
  • Liu, X., Zhang, B., Susarla, A., and Padman, R. Go To Youtube and See Me Tomorrow: Social Media and Self-care of Chronic Conditions. R&R at MIS Quarterly.
  • Um, S., Yoo, Y., Wattal, S., Zhang, B., and Kulathinal R. The Architecture of Generativity of an Open Digital Ecosystems: A Network Biology Perspective. R&R at Management Science.

Refereed Conferences and Proceedings

  • Xie J, Zhang B. (2018) Readmission Risk Prediction for Patients with Heterogeneous Hazard: A Trajectory-Aware Deep Learning Approach. 2018 International Conference on Information Systems (ICIS), San Francisco, CA.
  • Guo, C., Zhang, B., Chen, X., and Goes, P. (2017) Pay Easy, Buy More: An Empirical Study of the Purchase Feature in Social Media Apps. In Proceedings of ICIS 2017, Seoul, South Korea.
  • Liu, X., Zhang, B., Susarla, A., and Padman, R. Go to YouTube and Call Me Tomorrow: Visual Social Media Analytics for Patient Self Care.  In 2017 Workshop on Information Systems and Economics (WISE 2017).
  • Zhao, K., Zhang, B., and Bai, X. (2016) Who Motivates My Participation in Virtual Interorganizational Communities of Practice: Self, Peers, or the Firm? In Proceedings of  ICIS 2016, Dublin, Ireland.
  • Pentland, S., Zhang, B. (2016) Identifying Deception using Facial Motion Capture and Analysis. In Workshop on Information Technologies and Systems (WITS) 2016, Dublin, Ireland.
  • Guo, C., Zhang, B., Chen, X., and Goes, P. (2016) Reviving Order Online? The Effect of Purchase Features in Social Media Mobile Apps. In Conference on Information Systems and Technology (CIST) 2016, Nashville, TN.
  • Geng, R., Zhang, B., and Han, S. (2015) Economics of "Tipping" Button in Social Media: An Empirical Analysis of Content Monetization. In WISE 2015, Dallas, TX.
  • Guo, C., Zhang, B., Chen, X., and Goes, P. (2015) Reviving Order Online? The Effect of Purchase Features in Social Media Mobile Apps. In WISE 2015, Dallas, TX.
  • Zhang, B., Liu, X., Susarla, A., Padman, R., and Chen, H. (2015) Improving YouTube Self-care Video Search: A Deep Learning Approach for Medical Knowledge Extraction. In WITS 2015, Dallas, TX.
  • Zhang, B., Geng, R., and Chen, X. Social Networks in Online Games: The Impact of Peer Influences on Repeat Purchase. In WITS 2015, Dallas, TX.
  • Zhang, Z., Yoo, Y., Wattal, S., Zhang, B., and Kulanthinal, R. (2014) Generative Diffusion of Innovations and Knowledge Networks in Open Source Projects. In Proceedings of ICIS 2014, Auckland, New Zealand.
  • Zhang, B., Pavlou, P., Krishnan, R., and Krackhardt, D. (2013) Comparing Peer Influences in Large Social Networks – An Empirical Study on CRBT. In Proceedings of ICIS 2013, Milan, Italy.
  • Um, S., Yoo, Y., and Wattal, S., Kulanthinal, R., and Zhang, B. (2013) The Architecture of Generativity in a Digital Ecosystem: A Network Biology Perspective. In Proceedings of ICIS 2013, Milan, Italy.
  • Zhang, B., Pavlou, P., Krishnan, R., and Krackhardt, D. (2013) An Empirical Investigation of Contagion on CRBT Adoption. In CIST 2013, Minneapolis, MN. (Nominated for best paper award)


  • National Institutes of Health (NIH), PI. Understanding E-Cigarette Adoption and Marketing: A Social Media Study (Project #: 5R01DA037378-05), $452,223, June 2018 – May 2020.
  • National Science Foundation (NSF) 
    Co-PI, The Structure and Dynamics of Generative Innovations: An Organizational Genetics Approach, $237,076
  • NSF 
    Co-Investigator, VOSS-Collaborative Research: Evolution in Virtualized Design Processes in Project-Based Design Organizations, $214,590
  • National Institutes of Health (NIH) 
    Co-Investigator, Understanding E-Cigarette Adoption and Marketing: A Social Media Study, $586,346
  • Center of Leadership Ethics, University of Arizona
    Co-PI, Identifying Cues to Deception During Job Interviews Using Motion Analysis
  • Center for Management Innovations in Health Care (CMIHC), University of Arizona 
    PI, Boosting Patient Knowledge: the Impact of Healthcare Video Intelligent Search on Diabetic Patient Self-care, $5,000.
  • Institute for Business and Information Technology, Temple University 
    PI, Analyzing Big Intraorganizational Network Data, $10,000.


  • Best Paper Award, Runner up, Sixth International Conference for Smart Health, 2018.
  • Nominee, Small Class Faculty of the Year, Eller College of Management, University of Arizona, 2015.
  • Teaching award, Eller College Student Council, University of Arizona, 2015.
  • Fellow, ICIS 2012 Junior Faculty Consortium, December 2012, Orlando, FL.
  • Nominee for Association of Information Systems (AIS) Best Dissertation Competition, Carnegie Mellon University, 2012.
  • Fellow, ICIS 2011 Doctoral Consortium, December 2011, Shanghai, China.