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Nonlinear growth: An origin of hub organization in complex networks

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.

Publication metadata

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


DOI: 10.1098/rsos.160691

Data Source Location:

PubMed id: 160691


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Funder referenceFunder name
MR/N015037/1Medical Research Council (MRC)