Published March 24, 2023 | Version v1
Journal article Open

Surprising combinations of research contents and contexts are related to impact and emerge with scientific outsiders from distant disciplines

  • 1. University of Chicago

Description

We investigate the degree to which impact in science and technology is associated with surprising breakthroughs, and how those breakthroughs arise. Identifying breakthroughs across science and technology requires models that distinguish surprising from expected advances at scale. Drawing on tens of millions of research papers and patents across the life sciences, physical sciences and patented inventions, and using a hypergraph model that predicts realized combinations of research contents (article keywords) and contexts (cited journals), here we show that surprise in terms of unexpected combinations of contents and contexts predicts outsized impact (within the top 10% of citations). These surprising advances emerge across, rather than within researchers or teams—most commonly when scientists from one field publish problem-solving results to an audience from a distant field. Our approach characterizes the frontier of science and technology as a complex hypergraph drawn from high-dimensional embeddings of research contents and contexts, and offers a measure of path-breaking surprise in science and technology.

Data availability

The raw MEDLINE data are available at the PubMed database (https://pubmed.ncbi.nlm.nih.gov/download/) and the processed MEDLINE data used in this study are open-access at Harvard Dataverse (https://doi.org/10.7910/DVN/NFSYYA). The APS data used in this study are available at https://journals.aps.org/datasets. These data can be obtained through APS by submitting a request. The US Patent data used in this study are open-access in the patentsview database at https://patentsview.org/download/data-download-tables. The "Nobel Prize Papers" data used in this study are open-access at Harvard Dataverse https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/6NJ5RN. The "General Award-Winning Papers" data used in this study are open-access at Harvard Dataverse https://doi.org/10.7910/DVN/NFSYYA). The "facultyopinions" data used in this study are open-access at Harvard Dataverse (https://doi.org/10.7910/DVN/NFSYYA). Source data are provided with this paper.

Code that supports the main findings of this study are available on GitHub: https://github.com/KnowledgeLab/hyper-novelty.

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Surprising-combinations-of-research-contents-and-contexts-are-related-to-impact-and-emerge-with-scientific-outsiders-from-distant-disciplines.pdf

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Additional details

Identifiers

DOI
10.1038/s41467-023-36741-4
Other
oai:uchicago.tind.io:5673

Funding

University of North Carolina at Chapel Hill
Data@Carolina initiative
John Templeton Foundation
United States Air Force Office of Scientific Research
FA9550-19-1-0354
U.S. National Science Foundation
1829366
Defense Advanced Research Projects Agency
HR00111820006

UChicago Information

Division(s)
Social Sciences Division
Department(s)
Sociology
Center(s) or Institute(s)
Knowledge Lab