The evolution of scientific literature as metastable knowledge states

PLoS One. 2023 Jul 12;18(7):e0287226. doi: 10.1371/journal.pone.0287226. eCollection 2023.

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.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Cluster Analysis
  • Humans
  • Knowledge
  • Language
  • Physicians*
  • Publications*

Grants and funding

This research was supported by the National Center for Science and Engineering Statistics (NCSES) at the National Science Foundation through award 49100420C0030. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.