The identification of recessive community organization in group decision making

Abstract

The reality of group decision problem is often a complex large group problem, and because of the influence of the factors such as personality, psychology, values and connection degree, group members can form different community organizations. The structure of community organizations, especially the division of the recessive community organizations and its structure in the group has a significant influence on the decision results. In this paper, under the perspective of complex network, the relationship between members of the group decision was abstracted as the weighted network, applying the agglomerative algorithm idea of nodes similarity, using the theory and method of the community partition of complex network, a community partition algorithm for the node empower network based on the measure the similarity of nodes is designed and verified. The algorithm considers both the properties and structural characteristics of nodes in the network, respectively reflects the individual’s knowledge level and communication network in group decision-making, which can be used to search for the recessive organization of group decision-making, laid a foundation to simulate group evolution process and the decision results.