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NETWORK OF SCIENTIFIC CONCEPTS: EMPIRICAL ANALYSIS AND MODELING

    https://doi.org/10.1142/S0219525921400014Cited by:3 (Source: Crossref)
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    This article is part of the issue:
    Special Issue on Success in Science
    Guest Editors: Luca Verginer, Giacomo Vaccario and Alexander M. Petersen

    Abstract

    Concepts in a certain domain of science are linked via intrinsic connections reflecting the structure of knowledge. To get a qualitative insight and a quantitative description of this structure, we perform empirical analysis and modeling of the network of scientific concepts in the domain of physics. To this end, we use a collection of manuscripts submitted to the e-print repository arXiv and the vocabulary of scientific concepts collected via the ScienceWISE.info platform and construct a network of scientific concepts based on their co-occurrences in publications. The resulting complex network possesses a number of specific features (high node density, dissortativity, structural correlations, skewed node degree distribution) that cannot be understood as a result of simple growth by several commonly used network models. We show that the model based on a simultaneous account of two factors, growth by blocks and preferential selection, gives an explanation of empirically observed properties of the concepts network.

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