Literature DB >> 34282354

Effect of Inter-layer Coupling on Multilayer Network Centrality Measures.

Tarun Kumar1,2, Manikandan Narayanan1,2, Balaraman Ravindran1,2.   

Abstract

The study of networks has been evolving because of its applications in diverse fields. Many complex systems involve multiple types of interactions and such systems are better modeled as multilayer networks.The question "which are the most (or least) important nodes in a given network?", has gained substantial attention in the network science community. The importance of a node is known as centrality and there are multiple ways to define it. Extending the centrality measure to multilayer networks is challenging since the relative contribution of intra-layer edges vs. that of inter-layer edges to multilayer centrality is not straight-forward. With the growing applications of multilayer networks, several attempts have been made to define centrality in multilayer networks in recent years. There are different ways of tuning the inter-layer couplings which may lead to different classes of centrality measures. In this article, we provide an overview of the recent works related to centrality in multilayer networks with a focus on key use cases and implications of the type of inter-layer coupling on centrality and subsequent uses of the different centrality measures. We discuss the effect of three popular interlayer coupling methods viz. diagonal coupling between adjacent layers, diagonal coupling and cross coupling. We hope the colloquial tone of this article would make it a pleasant read for understanding the theoretical as well as experimental aspects of the work.

Entities:  

Keywords:  Betweenness centrality; Eigenvector centrality; Interconnected networks; Multilayer networks; Multiplex networks; PageRank centrality

Year:  2019        PMID: 34282354      PMCID: PMC7611298          DOI: 10.1007/s41745-019-0103-y

Source DB:  PubMed          Journal:  J Indian Inst Sci        ISSN: 0019-4964


  15 in total

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Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2012-02-13

2.  Eigenvector centrality of nodes in multiplex networks.

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Authors:  S Gómez; A Díaz-Guilera; J Gómez-Gardeñes; C J Pérez-Vicente; Y Moreno; A Arenas
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5.  EIGENVECTOR-BASED CENTRALITY MEASURES FOR TEMPORAL NETWORKS.

Authors:  Dane Taylor; Sean A Myers; Aaron Clauset; Mason A Porter; Peter J Mucha
Journal:  Multiscale Model Simul       Date:  2017-03-28       Impact factor: 1.930

Review 6.  The structure and dynamics of multilayer networks.

Authors:  S Boccaletti; G Bianconi; R Criado; C I Del Genio; J Gómez-Gardeñes; M Romance; I Sendiña-Nadal; Z Wang; M Zanin
Journal:  Phys Rep       Date:  2014-07-10       Impact factor: 25.600

7.  The multilayer temporal network of public transport in Great Britain.

Authors:  Riccardo Gallotti; Marc Barthelemy
Journal:  Sci Data       Date:  2015-01-06       Impact factor: 6.444

8.  A Multilayer perspective for the analysis of urban transportation systems.

Authors:  Alberto Aleta; Sandro Meloni; Yamir Moreno
Journal:  Sci Rep       Date:  2017-03-15       Impact factor: 4.379

9.  Hypergraphs and cellular networks.

Authors:  Steffen Klamt; Utz-Uwe Haus; Fabian Theis
Journal:  PLoS Comput Biol       Date:  2009-05-29       Impact factor: 4.475

10.  Suppressing disease spreading by using information diffusion on multiplex networks.

Authors:  Wei Wang; Quan-Hui Liu; Shi-Min Cai; Ming Tang; Lidia A Braunstein; H Eugene Stanley
Journal:  Sci Rep       Date:  2016-07-06       Impact factor: 4.379

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