With the rapid development of social media, reliable information released by the public on social media can provide important decision-making support. Therefore, the consideration of the public as another decision-making body participating in large-scale group decision-making (LSGDM) problems has become an extensively researched topic. However, the participation of the public as a decision-making body with decision-making experts faces several issues, such as the acquisition of public opinion, the reliability of public opinion, the integration of public and expert opinions, etc. Given this, this paper proposes a public and large-scale expert information fusion method that considers public dynamic reliability via sentiment analysis and intuitionistic fuzzy number (IFN) expressions. First, sentiment analysis technology is used to process public social media data and obtain IFNs as the opinions of the public decision-making body. Second, the concept of public dynamic reliability is defined to measure the degree of integration of public opinion. Third, a novel information entropy measure of IFNs is proposed, and a new method is introduced to determine the criteria weights under the two different decision-making bodies. Finally, an optimization model that considers the consensus levels of expert subgroups is proposed to determine the weights of different decision-making bodies. The public and expert opinions are then aggregated to obtain collective decision-making information. A case study is proposed to illustrate the application of the proposed method, and the comparative analysis reveals the features and advantages of this model.

随着社交媒体的快速发展，公众在社交媒体上发布的可靠信息可以提供重要的决策支持。因此，将公众作为参与大规模群体决策（LSGDM）问题的另一个决策主体的考虑已成为一个广泛研究的课题。但是，公众作为决策专家参与的决策主体，面临着民意的获取、民意的可靠性、民意与专家意见的融合等问题。论文提出了一种公共和大规模专家信息融合方法，通过情感分析和直觉模糊数（IFN）表达式考虑公共动态可靠性。第一的，情感分析技术用于处理公共社交媒体数据，获取干扰素作为公共决策机构的意见。其次，定义了公共动态可靠性的概念来衡量舆论的整合程度。第三，提出了一种新的干扰素信息熵度量，并引入了一种新方法来确定两个不同决策机构下的标准权重。最后，提出了一个考虑专家小组共识水平的优化模型，以确定不同决策机构的权重。然后汇总公众和专家意见以获得集体决策信息。提出了一个案例研究来说明所提出方法的应用，比较分析揭示了该模型的特点和优势。