Assessing the interdependencies between scientific disciplinary profiles
Maria Grazia Izzo,
Giammarco Quaglia and
Giancarlo Ruocco ()
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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
Luca Leuzzi: CNR-NANOTEC
Giammarco Quaglia: Sapienza University of Rome
Giancarlo Ruocco: Fondazione Istituto Italiano di Tecnologia (IIT)
Scientometrics, 2018, vol. 116, issue 3, 1785-1803
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.
Keywords: Disciplinary profiles; Country-level studies; Pseudo-likelihood estimation; Incites (search for similar items in EconPapers)
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