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dc.contributor.authorYe, Mengbin
dc.contributor.authorLiu, J.
dc.contributor.authorAnderson, B.D.O.
dc.contributor.authorYu, C.
dc.contributor.authorBaşar, T.
dc.date.accessioned2021-07-06T12:34:53Z
dc.date.available2021-07-06T12:34:53Z
dc.date.issued2018
dc.identifier.citationYe, M. and Liu, J. and Anderson, B.D.O. and Yu, C. and Başar, T. 2018. Evolution of Social Power in Social Networks with Dynamic Topology. IEEE Transactions on Automatic Control. 63 (11): pp. 3793-3808.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/84242
dc.identifier.doi10.1109/TAC.2018.2805261
dc.description.abstract

The recently proposed DeGroot-Friedkin model describes the dynamical evolution of individual social power in a social network that holds opinion discussions on a sequence of different issues. This paper revisits that model, and uses nonlinear contraction analysis, among other tools, to establish several novel results. First, we show that for a social network with constant topology, each individual's social power converges to its equilibrium value exponentially fast, whereas previous results only concluded asymptotic convergence. Second, when the network topology is dynamic (i.e., the relative interaction matrix may change between any two successive issues), we show that the initial (perceived) social power of each individual is exponentially forgotten. Specifically, individual social power is dependent only on the dynamic network topology, and initial social power is forgotten as a result of sequential opinion discussion. Finally, we provide an explicit upper bound on an individual's social power as the number of issues discussed tends to infinity; this bound depends only on the network topology. Simulations are provided to illustrate our results.

dc.languageEnglish
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/arc/DP160104500
dc.subjectScience & Technology
dc.subjectTechnology
dc.subjectAutomation & Control Systems
dc.subjectEngineering, Electrical & Electronic
dc.subjectEngineering
dc.subjectDiscrete-time
dc.subjectdynamic topology
dc.subjectnonlinear contraction analysis
dc.subjectopinion dynamics
dc.subjectsocial networks
dc.subjectsocial power
dc.subjectLOOKING-GLASS SELF
dc.subjectOPINION DYNAMICS
dc.subjectCONSENSUS
dc.subjectSYSTEMS
dc.subjectCOORDINATION
dc.subjectMATRICES
dc.titleEvolution of Social Power in Social Networks with Dynamic Topology
dc.typeJournal Article
dcterms.source.volume63
dcterms.source.number11
dcterms.source.startPage3793
dcterms.source.endPage3808
dcterms.source.issn0018-9286
dcterms.source.titleIEEE Transactions on Automatic Control
dc.date.updated2021-07-06T12:34:53Z
curtin.note

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Sciences (EECMS)
curtin.accessStatusOpen access
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidYe, Mengbin [0000-0003-1698-0173]
dcterms.source.eissn1558-2523
curtin.contributor.scopusauthoridYe, Mengbin [56203529600]


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