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Reliance on science by inventors: Hybrid extraction of in‐text patent‐to‐article citations

Author

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  • Matt Marx
  • Aaron Fuegi
Abstract
We curate and characterize a complete set of citations from patents to scientific articles, including 16.8 million from the full text of USPTO and EPO patents. Combining hand‐tuned heuristics and the GROBID machine‐learning package, we achieve much higher performance than machine learning alone. Recall is evaluated with a set of 5939 randomly sampled, cross‐verified “known good” citations, which the authors have never seen. At 99.4% precision, we achieve recall rates of 78% for the full test set and 88% for references specified without mistakes. We compare these “in‐text” citations with those on the front page of patents. In‐text citations are more diverse temporally, geographically, and topically; moreover, they are less self‐referential and less likely to be copied from one patent to the next. In‐text citations have dropped from two‐thirds of all patent‐to‐article citations half a century ago to about one‐third today. In replicating two articles that use only front‐page citations, we show that failing to capture in‐text citations leads to understating the role of academic science in commercial invention. All patent‐to‐article citations, the known‐good test set, and the source code are available at http://relianceonscience.org.

Suggested Citation

  • Matt Marx & Aaron Fuegi, 2022. "Reliance on science by inventors: Hybrid extraction of in‐text patent‐to‐article citations," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(2), pages 369-392, April.
    • Handle: RePEc:bla:jemstr:v:31:y:2022:i:2:p:369-392
    DOI: 10.1111/jems.12455
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    References listed on IDEAS

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    1. Jasjit Singh & Matt Marx, 2013. "Geographic Constraints on Knowledge Spillovers: Political Borders vs. Spatial Proximity," Management Science, INFORMS, vol. 59(9), pages 2056-2078, September.
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    Cited by:

    1. Francesco Lissoni & Ernest Miguelez, 2024. "Migration and Innovation: Learning from Patent and Inventor Data," Journal of Economic Perspectives, American Economic Association, vol. 38(1), pages 27-54, Winter.
    2. Cesare Righi & Davide Cannito & Theodor Vladasel, 2023. "Continuing patent applications at the USPTO," Economics Working Papers 1855, Department of Economics and Business, Universitat Pompeu Fabra.
    3. Cesare Righi & Davide Cannito & Theodor Vladasel, 2023. "Continuing Patent Applications at the USPTO," Working Papers 1382, Barcelona School of Economics.
    4. Righi, Cesare & Cannito, Davide & Vladasel, Theodor, 2023. "Continuing patent applications at the USPTO," Research Policy, Elsevier, vol. 52(4).
    5. Yang, Alex J., 2024. "Unveiling the impact and dual innovation of funded research," Journal of Informetrics, Elsevier, vol. 18(1).
    6. de Rassenfosse, Gaétan & Palangkaraya, Alfons, 2023. "Do patent pledges accelerate innovation?," Research Policy, Elsevier, vol. 52(5).

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