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dc.creatorTsiotas D.en
dc.date.accessioned2023-01-31T10:15:17Z
dc.date.available2023-01-31T10:15:17Z
dc.date.issued2019
dc.identifier10.1371/journal.pone.0218477
dc.identifier.issn19326203
dc.identifier.urihttp://hdl.handle.net/11615/80006
dc.description.abstractAiming at serving the interdisciplinary demand in network science, this paper introduces a new concept for complex networks, named network stiffness, which is extracted from structural engineering by assuming that a complex network behaves similarly with a structured framework. This analogy allows interpreting that a complex network can resist against any cause attempting to induce deformation changes to the network’s structure, regardless of whether the network is material or not. Within this framework, this paper examines the context of applying the conceptual analogy of stiffness from the field of structural engineering to network science and then it develops computational approaches capturing different aspects of network stiffness so that to be used in complex network analysis. The implementation of these approaches to a real-world network (global inbound tourism network) shows that stiffness can produce interesting insights to complex network analysis about the factors related to changes caused to the structure and the status of a complex network. © 2019 Dimitrios Tsiotas. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en
dc.language.isoenen
dc.sourcePLoS ONEen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85067391372&doi=10.1371%2fjournal.pone.0218477&partnerID=40&md5=79e4fefea4b4d24f5554f8f69e68150b
dc.subjectarticleen
dc.subjectrigidityen
dc.subjecttourismen
dc.subjectalgorithmen
dc.subjectbuilding materialen
dc.subjectchemistryen
dc.subjecthumanen
dc.subjectmechanicsen
dc.subjectpolymeren
dc.subjectAlgorithmsen
dc.subjectConstruction Materialsen
dc.subjectHumansen
dc.subjectMechanical Phenomenaen
dc.subjectNeural Networks, Computeren
dc.subjectPolymersen
dc.subjectPublic Library of Scienceen
dc.titleNetwork stiffness: A new topological property in complex networksen
dc.typejournalArticleen


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