The Royal Society
Browse
rsos160691_si_001.pdf (2.91 MB)

ESM.pdf: Information on materials, methods and parameters. from Nonlinear growth: an origin of hub organization in complex networks

Download (5.83 MB)
Version 2 2017-03-17, 15:11
Version 1 2017-03-08, 15:36
journal contribution
posted on 2017-03-17, 15:11 authored by Roman Bauer, Marcus Kaiser
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 with 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.

History

Usage metrics

    Royal Society Open Science

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC