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A hypergraph model for representing scientific output

Author

Listed:
  • Rodica Ioana Lung

    (Babeş-Bolyai University)

  • Noémi Gaskó

    (Babeş-Bolyai University)

  • Mihai Alexandru Suciu

    (Babeş-Bolyai University)

Abstract

Representation and analysis of publication data in the form of a network has become a common method of illustrating and evaluating the scientific output of a group or of a scientific field. Co-authorship networks also reveal patterns and collaboration practices. In this paper we propose the use of a hypergraph model—a generalized network—to represent publication data by considering papers as hypergraph nodes. Hyperedges, connecting the nodes, represent the authors connecting all their papers. We show that this representation is more straightforward than other authorship network models. Using the hypergraph model we propose a collaboration measure of an author that reflects the influence of that author over the collaborations of its co-authors. We illustrate the introduced concepts by analyzing publishing data of computer scientists and mathematicians in Romania over a 10 year period.

Suggested Citation

  • Rodica Ioana Lung & Noémi Gaskó & Mihai Alexandru Suciu, 2018. "A hypergraph model for representing scientific output," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1361-1379, December.
    • Handle: RePEc:spr:scient:v:117:y:2018:i:3:d:10.1007_s11192-018-2908-2
    DOI: 10.1007/s11192-018-2908-2
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    References listed on IDEAS

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    Cited by:

    1. Daniela Aguirre-Guerrero & Roberto Bernal-Jaquez, 2023. "A Methodology for the Analysis of Collaboration Networks with Higher-Order Interactions," Mathematics, MDPI, vol. 11(10), pages 1-17, May.

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