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Comparative science mapping: a novel conceptual structure analysis with metadata

Author

Listed:
  • Massimo Aria

    (University of Naples Federico II
    K-Synth)

  • Corrado Cuccurullo

    (University of Campania L. Vanvitelli
    K-Synth)

  • Luca D’Aniello

    (University of Naples Federico II
    K-Synth)

  • Michelangelo Misuraca

    (University of Calabria
    K-Synth)

  • Maria Spano

    (University of Naples Federico II
    K-Synth)

Abstract

Textual analyses on scientific publications are increasingly employed in Bibliometrics to explore the conceptual structure of a research domain, often overlooking other rich metadata that can provide deeper insights into the scientific landscape of reference. This paper introduces an innovative technique to explore the conceptual structure of different observation units in a joint representation. The proposed strategy segments bibliographic datasets based on several metadata dimensions, such as the authors (and their characteristics), the corresponding institutions, or their geographical localisation. It provides detailed maps that depict multiple conceptual frameworks, allowing for detailed comparisons and insights in a joint visualisation. We employed these strategic diagrams to visualise and analyse the oncological research of Italian Academic Medical Centres (AMCs), particularly focusing on public institutions. The analysis focuses on how different AMCs specialise and interact, providing a comparative framework that aids AMCs themselves in directing their research strategies toward innovative fronts. Furthermore, these visualisations can assist policymakers and healthcare stakeholders in understanding the broader research environment, which is crucial for informed decision-making regarding funding and policy development related to the AMCs’ triple mission.

Suggested Citation

  • Massimo Aria & Corrado Cuccurullo & Luca D’Aniello & Michelangelo Misuraca & Maria Spano, 2024. "Comparative science mapping: a novel conceptual structure analysis with metadata," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7055-7081, November.
  • Handle: RePEc:spr:scient:v:129:y:2024:i:11:d:10.1007_s11192-024-05161-6
    DOI: 10.1007/s11192-024-05161-6
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