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A random interacting network model for complex networks

  • 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 multipleWe 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.show moreshow less

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Metadaten
Author:Bedartha Goswami, Snehal M. Shekatkar, Aljoscha RheinwaltORCiDGND, G. Ambika, Jürgen KurthsORCiDGND
DOI:https://doi.org/10.1038/srep18183
ISSN:2045-2322 (print)
Pubmed Id:http://www.ncbi.nlm.nih.gov/pubmed?term=26657032
Parent Title (English):Scientific reports
Publisher:Nature Publ. Group
Place of publication:London
Document Type:Article
Language:English
Year of first Publication:2015
Year of Completion:2015
Release Date:2017/03/27
Volume:5
Pagenumber:10
Funder:DAAD-DST PPP-Indien project [55516784, INT/FRG/DAAD/P-215]; DFG/FAPESP [IRTG 1740/TRP 2011/50151-0]; Government of the Russian Federation [14.Z50.31.0033]; University Grants Comission, New Delhi
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften
Peer Review:Referiert
Publication Way:Open Access