Abstract.
Co-authorship networks of neighbouring scientific disciplines, i.e. granular (G) media and networks (N) are studied in order to observe drastic structural changes in evolving networks. The data is taken from ar**ves. The system is described as coupled networks. By considering the 1995–2005 time interval and scanning the author-article network evolution with a mobile time window, we focus on the properties of the links, as well as on the time evolution of the nodes. They can be in three states, N, G or multi-disciplinary (M). This leads to drastic jumps in a so-called order parameter, i.e. the link proportion of a given type, forming the main island, that reminds of features appearing at percolation and during metastable (aggregation-desaggregation) processes. The data analysis also focuses on the way different kinds (N, G or M) of authors collaborate, and on the kind of the resulting collaboration.
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Noise is intrinsic to this sort of data as anyone having put a paper on the arxives knows
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Ausloos, M., Lambiotte, R. Drastic events make evolving networks. Eur. Phys. J. B 57, 89–94 (2007). https://doi.org/10.1140/epjb/e2007-00159-6
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DOI: https://doi.org/10.1140/epjb/e2007-00159-6