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Assessing the interdependencies between scientific disciplinary profiles

Author

Listed:
  • Cinzia Daraio

    (Sapienza University of Rome)

  • Francesco Fabbri

    (Sapienza University of Rome)

  • Giulia Gavazzi

    (Sapienza University of Rome)

  • Maria Grazia Izzo

    (Sapienza University of Rome
    Fondazione Istituto Italiano di Tecnologia (IIT))

  • Luca Leuzzi

    (CNR-NANOTEC
    Sapienza University of Rome)

  • Giammarco Quaglia

    (Sapienza University of Rome)

  • Giancarlo Ruocco

    (Fondazione Istituto Italiano di Tecnologia (IIT)
    Sapienza University of Rome)

Abstract

The investigation of the dynamics of national disciplinary profiles is at the forefront in quantitative investigations of science. We propose a new approach to investigate the complex interactions among scientific disciplinary profiles. The approach is based on recent pseudo-likelihood techniques introduced in the framework of machine learning and complex systems. We infer, in a Bayesian framework, the network topology and the related interdependencies among national disciplinary profiles. We analyse data extracted from the Incites database which relate to the national scientific production of most productive world countries at disciplinary level over the period 1992–2016.

Suggested Citation

  • Cinzia Daraio & Francesco Fabbri & Giulia Gavazzi & Maria Grazia Izzo & Luca Leuzzi & Giammarco Quaglia & Giancarlo Ruocco, 2018. "Assessing the interdependencies between scientific disciplinary profiles," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1785-1803, September.
    • Handle: RePEc:spr:scient:v:116:y:2018:i:3:d:10.1007_s11192-018-2816-5
    DOI: 10.1007/s11192-018-2816-5
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    References listed on IDEAS

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    Cited by:

    1. Moriah B. Bostian & Cinzia Daraio & Rolf Fare & Shawna Grosskopf & Maria Grazia Izzo & Luca Leuzzi & Giancarlo Ruocco & William L. Weber, 2018. "Inference for Nonparametric Productivity Networks: A Pseudo-likelihood Approach," DIAG Technical Reports 2018-06, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".

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