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Authorship and citation cultural nature in Density Functional Theory from solid state computational packages

Author

Listed:
  • Marie Dumaz

    (West Virginia University
    Lane Department of Computer Science and Electrical Engineering)

  • Reese Boucher

    (West Virginia University)

  • Miguel A. L. Marques

    (Martin-Luther-Universität Halle-Wittenberg)

  • Aldo H. Romero

    (West Virginia University)

Abstract

Density functional theory is the most used methodology in the characterization of the electronic structure of materials. Its applications have spread out to almost every STEM field and it is recognized as one of the most successful theories in materials science. In this paper we measure the specific impact of this theory by means of the citation record of the most important solid-state first principle ab initio packages. We report the exponential growth of publications and how the different electronic structure packages are supporting different scientific communities. Analysis of the growing community, relations between different communities, network strength, relation between citations and number of publications with respect to country of origin of the authors, number of authors per paper, words per title and publication journal is performed. We make several interesting observations, e.g., regarding the connection between the countries where the packages are developed and used, or concerning the collaboration networks. We also find bibliometrical evidence for the specialization of the software packages, even if they include similar capabilities.

Suggested Citation

  • Marie Dumaz & Reese Boucher & Miguel A. L. Marques & Aldo H. Romero, 2021. "Authorship and citation cultural nature in Density Functional Theory from solid state computational packages," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6681-6695, August.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:8:d:10.1007_s11192-021-04057-z
    DOI: 10.1007/s11192-021-04057-z
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    References listed on IDEAS

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    1. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
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    3. Robin Haunschild & Werner Marx, 2020. "Discovering seminal works with marker papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2955-2969, December.
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