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Draw me Science

Author

Listed:
  • David Chavalarias

    (Complex Systems Institute of Paris Île-de-France (ISC-PIF)
    EHESS, Centre d’Analyse et de Mathématique Sociales (CAMS))

  • Quentin Lobbé

    (Complex Systems Institute of Paris Île-de-France (ISC-PIF))

  • Alexandre Delanoë

    (Complex Systems Institute of Paris Île-de-France (ISC-PIF))

Abstract

In 1751, Jean le Rond d’Alembert had a dream: “to make a genealogical or encyclopedic tree which will gather the various branches of knowledge together under a single point of view and will serve to indicate their origin and their relationships to one another”. In this paper, we address the question identifying the branches of science by taking advantage of the massive digitization of scientific production. In the framework of complex systems studies, we first formalize the notion of level and scale of knowledge dynamics. Then, we demonstrate how we can reconstruct a reasonably precise and concise multi-scale and multi-level approximation of the dynamical structures of Science: phylomemies. We introduce the notion of phylomemetic networks—projections of phylomemies in low dimensional spaces that can be grasped by the human mind—and propose a new algorithm to reconstruct both phylomemies and the associated phylomemetic networks. This algorithm offers, passing, a new temporal clustering on evolving semantic networks. Last, we show how phylomemy reconstruction can take into account users’ preferences within the framework of embodied cognition, thus defining a third way between the quest for objective “ground truth” and the ad-hoc adaptation to a particular user’s preferences. The robustness of this approach is illustrated by several case studies.

Suggested Citation

  • David Chavalarias & Quentin Lobbé & Alexandre Delanoë, 2022. "Draw me Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 545-575, January.
  • Handle: RePEc:spr:scient:v:127:y:2022:i:1:d:10.1007_s11192-021-04186-5
    DOI: 10.1007/s11192-021-04186-5
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    References listed on IDEAS

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    1. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    2. Vahe Tshitoyan & John Dagdelen & Leigh Weston & Alexander Dunn & Ziqin Rong & Olga Kononova & Kristin A. Persson & Gerbrand Ceder & Anubhav Jain, 2019. "Unsupervised word embeddings capture latent knowledge from materials science literature," Nature, Nature, vol. 571(7763), pages 95-98, July.
    3. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    4. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    5. Robert R. Braam & Henk F. Moed & Anthony F. J. van Raan, 1991. "Mapping of science by combined co‐citation and word analysis. I. Structural aspects," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 42(4), pages 233-251, May.
    6. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    7. Gergely Palla & Albert-László Barabási & Tamás Vicsek, 2007. "Quantifying social group evolution," Nature, Nature, vol. 446(7136), pages 664-667, April.
    8. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    9. Robert R. Braam & Henk F. Moed & Anthony F. J. van Raan, 1991. "Mapping of science by combined co‐citation and word analysis. II: Dynamical aspects," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 42(4), pages 252-266, May.
    10. David Chavalarias & Jean-Philippe Cointet, 2013. "Phylomemetic Patterns in Science Evolution—The Rise and Fall of Scientific Fields," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-11, February.
    11. David Chavalarias & Jean-Philippe Cointet, 2008. "Bottom-up scientific field detection for dynamical and hierarchical science mapping, methodology and case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(1), pages 37-50, April.
    12. Chen, Baitong & Tsutsui, Satoshi & Ding, Ying & Ma, Feicheng, 2017. "Understanding the topic evolution in a scientific domain: An exploratory study for the field of information retrieval," Journal of Informetrics, Elsevier, vol. 11(4), pages 1175-1189.
    13. Xiaoguang Wang & Qikai Cheng & Wei Lu, 2014. "Analyzing evolution of research topics with NEViewer: a new method based on dynamic co-word networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1253-1271, November.
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    More about this item

    Keywords

    Phylomemy reconstruction; Knowledge dynamics; Phenomenological reconstruction; Multi-scale and multi-level complex systems; Science map; Co-word analysis;
    All these keywords.

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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