关键词: 社会网络分析, 大群体决策, 概率语言, 重叠社区, 群体一致性

Abstract: Aimed at the multi-attribute large group decision-making problem that the decision-makers’ preference information are probabilistic language information in social network analysis, this paper proposes a new probabilistic language multi-attribute large group decision-making method based on group consistency. First, for the situation that decision-makers belong to multiple community clusters to participate in decision-making, this paper proposes the concept of community sub-module membership degree and preprocesses it. Next, considering the social network relationship between decision-maker, it improves the Louvain community detection algorithm to divide the community of large group decision makers. Then, it extends the maximum consensus sequence mining algorithm to the field of probabilistic language information, and proposes a consensus measurement method and consensus achievement model based on group consistency to obtain the final solution. Finally, it applies an example to verify the effectiveness of the proposed method, and illustrates its rationality and advantages by comparative analysis.

Key words: social network analysis；large group decision-making, probabilistic language, overlapping communities, group consistency