Social network community analysis based large-scale group decision making approach with incomplete fuzzy preference relations

Large-scale group decision making (LSGDM) is characterized by a large number of participators, multiple groups and a mass of decision data provided by the participators. With the development of social media and e-democracy technologies, the social relationships among group decision makers should be taken into consideration when we address LSGDM problems with incomplete fuzzy preference relations. In this paper, a social network community detection approach of social networks based on the fuzzy clustering method is proposed. Then, a method of repairing incomplete fuzzy preference relations based on the divided communities is proposed. Moreover, we have proposed a two-stage consensus reaching method to balance the number of iterations and modification range of original decision information, in which the group closeness centrality of community is applied to measure its importance. Also, the procedure for LSGDM with fuzzy preference relations based on social network community analysis is established. The feasibility and advantages of the proposed method for LSGDM based on social network community analysis are illustrated by an illustrative example of a flexible manufacturing system.