Natural Language Processing and Innovation Research

Antonin Bergeaud, Adam Jaffe and Dimitris Papanikolaou

No 33821, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Innovation is central to models in economics, strategy, management, and finance, yet it remains difficult to measure due to its intangible and knowledge-based na ture. Recent advancements in Natural Language Processing offer new methods to analyze textual artifacts, providing empirical insights into previously hard-to-measure aspects of innovation. This paper provides an overview of the current applications of these methods in empirical innovation research, highlights their transformative potential for reshaping how researchers study and quantify innovation, and discusses the critical challenges that accompany their use.

JEL-codes: C80 O30 O31 (search for similar items in EconPapers)
Date: 2025-05
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