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On entropy research analysis: cross-disciplinary knowledge transfer

Author

Listed:
  • R. Basurto-Flores

    (Unidad Profesional Interdisciplinaria en Ingeniería y Tecnologías Avanzadas)

  • L. Guzmán-Vargas

    (Unidad Profesional Interdisciplinaria en Ingeniería y Tecnologías Avanzadas)

  • S. Velasco

    (Universidad de Salamanca
    Universidad de Salamanca)

  • A. Medina

    (Universidad de Salamanca)

  • A. Calvo Hernandez

    (Universidad de Salamanca
    Universidad de Salamanca)

Abstract

Our aim is to illustrate how the thermodynamics-based concept of entropy has spread across different areas of knowledge by analyzing the distribution of papers, citations and the use of words related to entropy in the predefined Scopus categories. To achieve this, we analyze the Scopus papers database related to entropy research during the last 20 years, collecting 750 K research papers which directly contain or mention the word entropy. First, some well-recognized works which introduced novel entropy-related definitions are monitored. Then we compare the hierarchical structure which emerges for the different cases of association, which can be in terms of citations among papers, classification of papers in categories or key words in abstracts and titles. Our study allowed us to evaluate, to some extent, the utility and versatility of concepts such as entropy to permeate in different areas of science. Furthermore, the use of specific terms (key words) in titles and abstracts provided a useful way to account for the interaction between areas in the category research space.

Suggested Citation

  • R. Basurto-Flores & L. Guzmán-Vargas & S. Velasco & A. Medina & A. Calvo Hernandez, 2018. "On entropy research analysis: cross-disciplinary knowledge transfer," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 123-139, October.
    • Handle: RePEc:spr:scient:v:117:y:2018:i:1:d:10.1007_s11192-018-2860-1
    DOI: 10.1007/s11192-018-2860-1
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    1. Alexey Lyutov & Yilmaz Uygun & Marc-Thorsten Hütt, 2021. "Machine learning misclassification of academic publications reveals non-trivial interdependencies of scientific disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1173-1186, February.
    2. repec:ehu:cuader:56542 is not listed on IDEAS

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