Spatial Growth of Real-world Networks
arXiv:cond-mat/0312037 · doi:10.1103/PhysRevE.69.036103
Abstract
Many real-world networks have properties of small-world networks, with clustered local neighborhoods and low average-shortest path (ASP). They may also show a scale-free degree distribution, which can be generated by growth and preferential attachment to highly connected nodes, or hubs. However, many real-world networks consist of multiple, inter-connected clusters not normally seen in systems grown by preferential attachment, and there also exist real-world networks with a scale-free degree distribution that do not contain highly connected hubs. We describe spatial growth mechanisms, not using preferential attachment, that address both aspects.
6 pages, 4 figures
References in corpus (8)
- Emergence of scaling in random networks
- Statistical mechanics of complex networks
- Lethality and centrality in protein networks
- Hierarchical organization of modularity in metabolic networks
- The large-scale organization of metabolic networks
- Random graphs with arbitrary degree distributions and their applications
- Identity and Search in Social Networks
- Scale-free Networks from Optimal Design
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