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Lookup NU author(s): Dr Roman BauerORCiD, Professor Marcus Kaiser
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Many real-world networks contain highly-connected nodes called hubs. Hubs are often crucial for network function and spreading dynamics. However, classical models of how hubs originate during network development unrealistically assume that new nodes attain information about the connectivity (for example the degree) of existing nodes. Here, we introduce hub formation through nonlinear growth where the number of nodes generated at each stage increases over time and new nodes form connections independent of target node features. Our model reproduces variation in number of connections, hub occurrence time, and rich-club organization of networks ranging from protein-protein, neuronal and fibre tract brain networks to airline networks. Moreover, nonlinear growth gives a more generic representation of these networks compared to previous preferential attachment or duplication-divergence models. Overall, hub creation through nonlinear network expansion can serve as a benchmark model for studying the development of many real-world networks.
Author(s): Bauer R, Kaiser M
Publication type: Article
Publication status: Published
Journal: Royal Society Open Science
Year: 2017
Online publication date: 22/03/2017
Acceptance date: 21/02/2017
Date deposited: 23/03/2017
ISSN (electronic): 2054-5703
URL: http://doi.org/10.1098/rsos.160691
DOI: 10.1098/rsos.160691
Data Access Statement: https://dx.doi.org/10.6084/m9.figshare.c.3711967 http://dx.doi.org/10.5061/dryad.6h8pm
PubMed id: 160691
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