Research

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My research goal is to propose and apply eclectic but robust solutions from statistical natural language processing and network science in order to understand latent patterns in large-scale text about individuals and organizations from social media, digital publications (e.g., blogs, articles, resumes, patents) and the World Wide Web.

Currently I'm working on the field of economics of information technology in general and examining the relationship among big data, innovation and firm performance. I started research in my junior year of college, working with Prof. Gongshen Liu on machine learning and statistical natural language processing for content-based online public opinion. For most of my time in Chicago, from Jan. 2014 to July 2015, I worked as a research programmer in Knowledge Lab, Computation Institute, with Dr. Aaron Gerow and Prof. James Evans, primarily in an exciting field of computational social science. (my intro in lab homepage) In addition, I also worked as a research assistant for Prof. Amanda J. Sharkey in Booth School of Business, exploring some review dataset for organization-level analysis.

Previously, I worked in Intel IT CCAP group, and conducted bank data analyses in China Guangfa Bank Shanghai Branch.

Working Papers

  • Data Analytics Skills, Innovation and Firm Productivity. (with Lynn Wu & Lorin Hitt, Under review in Management Science)

  • Data Analytics Skills and the Decentralized Innovation Communities. (with Lynn Wu & Lorin Hitt)

  • Does Employer Brand Matter: An Empirical Analysis on Online Job Reviews, Social Media Usage and Firm Performance. (with Fujie Jin & Lorin Hitt)

Other Paper

  • Aaron Gerow, Bowen Lou, Eamon Duede, James Evans. Proposing Ties in a Dense Hypergraph of Academics. Proceedings of the 7th International Conference on Social Informatics, Beijing, China, 2015.