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Diffusion of knowledge and globalization in the web of twentieth century science

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  • Naumis, G.G.
  • Phillips, J.C.

Abstract

Scientific communication is an essential part of modern science: whereas Archimedes worked alone, Newton (correspondence with Hooke, 1676) acknowledged that “If I have seen a little further, it is by standing on the shoulders of Giants.” How is scientific communication reflected in the patterns of citations in scientific papers? How have these patterns changed in the 20th century, as both means of communication and individual transportation changed rapidly, compared to the earlier post-Newton 18th and 19th centuries? Here we discuss a diffusive model for scientific communications, based on a unique 2009 scientometric study of 25 million papers and 600 million citations that encapsulates the epistemology of modern science. The diffusive model predicts and explains, using no adjustable parameters, a surprisingly universal internal structure in the development of scientific research, which is essentially constant across the natural sciences, but which because of globalization changed qualitatively around 1960. Globalization corresponds physically to anomalous diffusion, which has been observed near the molecular glass transition, and can enhance molecular diffusion by factors as large as 100.

Suggested Citation

  • Naumis, G.G. & Phillips, J.C., 2012. "Diffusion of knowledge and globalization in the web of twentieth century science," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(15), pages 3995-4003.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:15:p:3995-4003
    DOI: 10.1016/j.physa.2012.02.005
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    Citations

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    Cited by:

    1. Phillips, J.C., 2015. "Similarity is not enough: Tipping points of Ebola Zaire mortalities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 277-281.
    2. Lyu, Haihua & Bu, Yi & Zhao, Zhenyue & Zhang, Jiarong & Li, Jiang, 2022. "Citation bias in measuring knowledge flow: Evidence from the web of science at the discipline level," Journal of Informetrics, Elsevier, vol. 16(4).
    3. Mauro, John C. & Mauro, Yihong Z., 2018. "On the Prony series representation of stretched exponential relaxation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 75-87.
    4. Phillips, J.C., 2014. "Fractals and self-organized criticality in proteins," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 440-448.
    5. Phillips, J.C., 2015. "Phase transitions in the web of science," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 173-177.

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