Growth signals determine the topology of evolving networks

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dc.citation.issue1
dc.citation.rankM21
dc.citation.spage013405
dc.citation.volume2021
dc.contributor.authorVranić, Ana
dc.contributor.authorMitrović Dankulov, Marija
dc.date.accessioned2024-06-14T10:32:23Z
dc.date.available2024-06-14T10:32:23Z
dc.date.issued2021-01-22
dc.description.abstractNetwork science provides an indispensable theoretical framework for studying the structure and function of real complex systems. Different network models are often used for finding the rules that govern their evolution, whereby the correct choice of model details is crucial for obtaining relevant insights. Here, we study how the structure of networks generated with the aging nodes model depends on the properties of the growth signal. We use different fluctuating signals and compare structural dissimilarities of the networks with those obtained with a constant growth signal. We show that networks with power-law degree distributions, which are obtained with time-varying growth signals, are correlated and clustered, while networks obtained with a constant growth signal are not. Indeed, the properties of the growth signal significantly determine the topology of the obtained networks and thus ought to be considered prominently in models of complex systems.
dc.identifier.doi10.1088/1742-5468/abd30b
dc.identifier.issn1742-5468
dc.identifier.scopus2-s2.0-85100727837
dc.identifier.urihttps://pub.ipb.ac.rs/handle/123456789/99
dc.identifier.wos000610055600001
dc.language.isoen
dc.publisherIOP Publishing Ltd
dc.relation.ispartofJournal of Statistical Mechanics: Theory and Experiment
dc.relation.ispartofabbrJ. Stat. Mech.: Theory Exp.
dc.rightsopenAccess
dc.titleGrowth signals determine the topology of evolving networks
dc.typeArticle
dc.type.versionpublishedVersion
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