Large-scale group decision-making method based on negative behavior management and improved minimum cost consensus model in social network environment
This paper proposes expert negative behavior identification and management based on social network analysis,and constructs an improved minimum cost consensus model in the large-scale group decision-making method.First,the concepts of experts'positive social image,negative social image and opinion indicator are defined,and three management strategies including negative social image,negative evaluation preference and double negative behavior to manage experts'negative behavior are proposed.Secondly,the similarity of opinions,the similarity of positive social image,and the similarity of negative social image of experts are calculated,and large-scale experts are clustered based on the K-means clustering method.Then,considering the influence of social image on consensus,an improved minimum-cost consensus model based on social image is proposed to reach group consensus and obtain the final plan ranking.Finally,a crowdfunding platform selection is presented to show the effectiveness and feasibility of the proposed method.
social network analysisnegative behaviorsocial imageminimum cost consensus modellarge-scale decision
NETL
NSTL
万方数据
维普
