  New scientific ideas fuel economic progress, yet their identification and
measurement remains challenging. In this paper, we use natural language
processing to identify the origin and impact of new scientific ideas in the
text of scientific publications. To validate the new techniques and their
improvement over traditional metrics based on citations, we first leverage
Nobel prize papers that likely pioneered new scientific ideas with a major
impact on scientific progress. Second, we use literature review papers that
typically summarize existing knowledge rather than pioneer new scientific
ideas. Finally, we demonstrate that papers introducing new scientific ideas are
more likely to become highly cited by both publications and patents. We provide
open access to code and data for all scientific papers up to December 2020.
