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Florian Englmaier: "Words to Numbers – Extracting Information from Unstructured Text"

Organizational Economics, LMU

Academic Year 2022/2023

When studying economic questions empirically, we often need to find numeric measures for constructs such as culture, trust, individual traits, strength of institutions, etc. However, most human interaction is not numeric, but verbal. Only recently, computer-based analytical methods have become available to study large amounts of text and speech data, in astringent, more objective way. This computer-linguistic revolution has great impact for all the social sciences, and economics in particular, because we now can apply these methods to distill complex concepts such as "trust" down to numbers.

The proposed CAS Research Group employs state of the art computer linguistic methods to novel, high-dimensional data sets, aka "unstructured text", to address substantive questions in three project areas:

I. Understanding knowledge production,

II. Measuring firm culture and management practices, and

III. Adapting to institutional and sectoral change.



  • Prof. Eliott Ash, Ph.D. (ETH Zuerich)
  • Prof. Diego Battiston, Ph.D. (University of Edinburgh)
  • Prof. Alexia Delfino, Ph.D. (Bocconi University, Milano)
  • Prof. Miguel Espinosa, Ph.D. (Bocconi University, Milano)
  • Prof. Ricard Gil, Ph.D. (Queen's University)
  • Prof. Michela Giorcelli, Ph.D. (University of California, Los Angeles)
  • Prof. Stephen Hansen, Ph.D. (Imperial College Business School, London)
  • Prof. Nicola Lacetera, Ph.D. (University of Toronto)
  • Prof. Stephen Leider, Ph.D. (University of Michigan)
  • Prof. Raffaella Sadun, Ph.D. (Harvard Business School)
  • Caspar Siegert, Ph.D. (Bank of England)
  • Prof. Erina Ytsma, Ph.D. (Tepper School of Business, Carnegie Mellon University)