COM2-04-15
660 13789
qiaodd@comp.nus.edu.sg

QIAO Dandan

Assistant Professor

  • Ph.D. (Tsinghua University)
  • B.S. (Beijing University of Posts and Telecommunications)

QIAO Dandan is an assistant professor in the Department of Information Systems and Analytics at the National University of Singapore (NUS). Prior to joining NUS, She earned her Ph.D in Information Systems from Tsinghua University and also visited University of Texas at Austin for two years. Her research interests lie in the intersection of information systems, behavioural science, and data mining. Her work focuses to explore interesting behaviour patterns and extract valuable crowd wisdom from online UGC, in the aim of providing guidelines for information system design. She also studies darkweb economies to decipher the mechanism of online illegal transactions and cyber-crime.

RESEARCH AREAS

Digital Transformation, Platforms & Innovation
Data Science & Business Analytics

RESEARCH INTERESTS

  • Economics of Information Systems
  • Economics of Dark Web
  • Online Altruism and Crowd Wisdom
  • Competitive Intelligence and Predictive Analytics

RESEARCH PROJECTS

RESEARCH GROUPS

TEACHING INNOVATIONS

SELECTED PUBLICATIONS

  • Qiao, D., Lee, S. Y., Whinston, A. B.,& Wei, Q. 2020. FinancialIncentives Dampen Altruism in Online Pro-Social Contributions: A Study of Online Reviews.Information SystemsResearch, forthcoming
  • Qiao, D., Lee, S. Y., Whinston, A. B., & Wei, Q. 2020. Mitigating the Adverse Effect of Monetary Incentives on Voluntary Contributions Online.Journal of Management Information Systems, forthcoming
  • Guo, X., Wei, Q., Chen, G., Zhang, J., & Qiao, D. 2017. Extracting Representative Information on Intra-Organizational Blogging Platforms.MIS Q.,414, 1105-1127.
  • Wei, Q., Qiao, D., Zhang, J., Chen, G., & Guo, X. 2016. A novel bipartite graph based competitiveness degree analysis from query logs.ACM Transactions on Knowledge Discovery from Data TKDD,112, 1-25.

AWARDS & HONOURS

TEACHING (2021/2022)

BT4222
Mining Web Data for Business Insights
BT4014
Analytics Driven Design of Adaptive Systems