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Genealogical Trees of Scientific Papers

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  • Michaël Charles Waumans
  • Hugues Bersini

Abstract

Many results have been obtained when studying scientific papers citations databases in a network perspective. Articles can be ranked according to their current in-degree and their future popularity or citation counts can even be predicted. The dynamical properties of such networks and the observation of the time evolution of their nodes started more recently. This work adopts an evolutionary perspective and proposes an original algorithm for the construction of genealogical trees of scientific papers on the basis of their citation count evolution in time. The fitness of a paper now amounts to its in-degree growing trend and a “dying” paper will suddenly see this trend declining in time. It will give birth and be taken over by some of its most prevalent citing “offspring”. Practically, this might be used to trace the successive published milestones of a research field.

Suggested Citation

  • Michaël Charles Waumans & Hugues Bersini, 2016. "Genealogical Trees of Scientific Papers," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-15, March.
    • Handle: RePEc:plo:pone00:0150588
    DOI: 10.1371/journal.pone.0150588
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    References listed on IDEAS

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    Cited by:

    1. Orlando Fonseca Guilarte & Simone Diniz Junqueira Barbosa & Sinesio Pesco, 2021. "RelPath: an interactive tool to visualize branches of studies and quantify the expertise of authors by citation paths," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4871-4897, June.
    2. Pandey, Pradumn Kumar & Singh, Mayank & Goyal, Pawan & Mukherjee, Animesh & Chakrabarti, Soumen, 2020. "Analysis of reference and citation copying in evolving bibliographic networks," Journal of Informetrics, Elsevier, vol. 14(1).

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