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dc.contributor.authorChiclana, Franciscoen
dc.contributor.authorFujita, Hamidoen
dc.contributor.authorHerrera-Viedma, Enriqueen
dc.contributor.authorWu, Jianen
dc.contributor.authorDai, Lifangen
dc.date.accessioned2017-09-20T10:08:40Z
dc.date.available2017-09-20T10:08:40Z
dc.date.issued2017-09-15
dc.identifier.citationWu, J. et al. (2017) A new consensus model for social network group decision making based on a minimum adjustment feedback mechanism and distributed linguistic trust. Information Fusion. 41, pp. 232-242en
dc.identifier.urihttp://hdl.handle.net/2086/14514
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractA theoretical feedback mechanism framework to model consensus in social network group decision making (SN-GDM) is proposed with following two main components: (1) the modelling of trust relationship with linguistic information; and (2) the minimum adjustment cost feedback mechanism. To do so, a distributed linguistic trust decision making space is defined, which includes the novel concepts of distributed linguistic trust functions, expectation degree, uncertainty degrees and ranking method. Then, a social network analysis (SNA) methodology is developed to represent and model trust relationship between a networked group, and the trust in-degree centrality indexes are calculated to assign an importance degree to the associated user. To identify the inconsistent users, three levels of consensus degree with distributed linguistic trust functions are calculated. Then, a novel feedback mechanism is activated to generate recommendation advices for the inconsistent users to increase the group consensus degree. Its novelty is that it produces the boundary feedback parameter based on the minimum adjustment cost optimisation model. Therefore, the inconsistent users are able to reach the threshold value of group consensus incurring a minimum modification of their opinions or adjustment cost, which provides the optimum balance between group consensus and individual independence. Finally, after consensus has been achieved, a ranking order relation for distributed linguistic trust functions is constructed to select the most appropriate alternative of consensus.en
dc.language.isoenen
dc.publisherElsevieren
dc.subjectGroup Decision Makingen
dc.subjectFeedback Mechanismen
dc.subjectMinimum Adjustment Optimization Modelen
dc.subjectConsensusen
dc.subjectSocial Network Analysisen
dc.subjectDistributed Linguistic Trusten
dc.titleA minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trusten
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.1016/j.inffus.2017.09.012
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.funderThe authors are very grateful to the anonymous referees for their valuable comments and suggestions that have helped the authors to improve considerably the quality of this paper. This work was supported by National Natural Science Foundation of China (NSFC) (No.71571166, 71331002), Zhejiang Provincial Xingmiao Talent Foundation of China (No.2017R404001), the grants TIN2013-40658-P and TIN2016-75850-R support by FEDER funds.en
dc.projectidThe authors are very grateful to the anonymous referees for their valuable comments and suggestions that have helped the authors to improve considerably the quality of this paper. This work was supported by National Natural Science Foundation of China (NSFC) (No.71571166, 71331002), Zhejiang Provincial Xingmiao Talent Foundation of China (No.2017R404001), the grants TIN2013-40658-P and TIN2016-75850-R support by FEDER funds.en
dc.cclicenceCC-BY-NC-NDen
dc.date.acceptance2017-09-12en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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