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The evolution of scientific literature as metastable knowledge states

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  • Sai Dileep Koneru
  • David Rench McCauley
  • Michael C Smith
  • David Guarrera
  • Jenn Robinson
  • Sarah Rajtmajer

Abstract

The problem of identifying common concepts in the sciences and deciding when new ideas have emerged is an open one. Metascience researchers have sought to formalize principles underlying stages in the life cycle of scientific research, understand how knowledge is transferred between scientists and stakeholders, and explain how new ideas are generated and take hold. Here, we model the state of scientific knowledge immediately preceding new directions of research as a metastable state and the creation of new concepts as combinatorial innovation. Through a novel approach combining natural language clustering and citation graph analysis, we predict the evolution of ideas over time and thus connect a single scientific article to past and future concepts in a way that goes beyond traditional citation and reference connections.

Suggested Citation

  • Sai Dileep Koneru & David Rench McCauley & Michael C Smith & David Guarrera & Jenn Robinson & Sarah Rajtmajer, 2023. "The evolution of scientific literature as metastable knowledge states," PLOS ONE, Public Library of Science, vol. 18(7), pages 1-19, July.
    • Handle: RePEc:plo:pone00:0287226
    DOI: 10.1371/journal.pone.0287226
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    References listed on IDEAS

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    1. Bilancia, Massimo & Dačević, Rade, 2025. "A Dirichlet-Multinomial mixture model of Statistical Science: Mapping the shift of a paradigm," Journal of Informetrics, Elsevier, vol. 19(1).

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