A random interacting network model for complex networks

Bedartha Goswami*, Snehal M. Shekatkar, Aljoscha Rheinwalt, G. Ambika, Juergen Kurths

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Citation (Scopus)
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Abstract

We propose a RAndom Interacting Network (RAIN) model to study the interactions between a pair of complex networks. The model involves two major steps: (i) the selection of a pair of nodes, one from each network, based on intra-network node-based characteristics, and (ii) the placement of a link between selected nodes based on the similarity of their relative importance in their respective networks. Node selection is based on a selection fitness function and node linkage is based on a linkage probability defined on the linkage scores of nodes. The model allows us to relate within-network characteristics to between-network structure. We apply the model to the interaction between the USA and Schengen airline transportation networks (ATNs). Our results indicate that two mechanisms: degree-based preferential node selection and degree-assortative link placement are necessary to replicate the observed inter-network degree distributions as well as the observed inter-network assortativity. The RAIN model offers the possibility to test multiple hypotheses regarding the mechanisms underlying network interactions. It can also incorporate complex interaction topologies. Furthermore, the framework of the RAIN model is general and can be potentially adapted to various real-world complex systems.

Original languageEnglish
Article number18183
Number of pages10
JournalScientific Reports
Volume5
Early online date11 Dec 2015
DOIs
Publication statusPublished - 11 Dec 2015

Keywords

  • community structure
  • brain networks
  • transition
  • emergence
  • dynamics

Cite this

Goswami, B., Shekatkar, S. M., Rheinwalt, A., Ambika, G., & Kurths, J. (2015). A random interacting network model for complex networks. Scientific Reports, 5, [18183]. https://doi.org/10.1038/srep18183