Paper Info
Title
Fuzzy m-ary adjacency relations in social network analysis: Optimization and consensus evaluation
Abstract
The main contribution of this paper consists in extending the 'soft' consensus paradigm of fuzzy group decision making developed under the framework of numerical fuzzy preferences. We address the problem of consensus evaluation by endogenously computing the importance of the decision makers in terms of their influence strength in the network. To this aim, we start from centrality measure and combine it with the fuzzy m-ary adjacency relation approach. In this way, we introduce a flexible consensus measure that takes into account the influence strength of the decision makers according to their eigenvector centrality. Moreover, we propose an optimization problem which determines the maximum number of the most important decision makers that share a fixed desirable consensus level.
Year
DOI
Venue
2014
10.1016/j.inffus.2011.11.001
Information Fusion
Keywords
Field
DocType
fuzzy m-ary adjacency relation,fixed desirable consensus level,influence strength,consensus paradigm,consensus evaluation,numerical fuzzy preference,fuzzy group decision,flexible consensus measure,decision maker,social network analysis,important decision maker,group decision making,consensus
Adjacency list,Eigenvector centrality,Social network analysis,Fuzzy logic,Centrality,Network theory,Artificial intelligence,Optimization problem,Machine learning,Mathematics,Group decision-making
Journal
Volume
ISSN
Citations 
17,
1566-2535
12
PageRank 
References 
Authors
0.48
16
3
Name
Order
Citations
PageRank
Matteo Brunelli130317.62
Mario Fedrizzi214829.78
Michele Fedrizzi334220.01