Research on key node identification of online public opinion on public health emergencies based on complex network

With the development of Internet technology, social media platforms have become an important channel for the public to express their opinions and obtain information, especially in the case of public health emergencies, and the dissemination speed and influence of online public opinion have increased significantly. Based on complex network theory and data mining techniques, this paper identifies and analyzes the key nodes in the dissemination of online public opinion on the "Rat Head Duck Neck Incident" on Weibo platform. A network model with 22,277 nodes and 25,034 edges is constructed, and the structural characteristics of the network are analyzed by the Gephi tool, including the degree distribution of the nodes, the average path length, the intermediary centrality and the proximity centrality. The results show that very few authenticated user nodes have very high access degree and mediated centrality degree in the network, which is the core of information dissemination. Meanwhile, modular analysis reveals that there is a distinct community structure in the network, in which large communities have a significant influence on the overall trend of online public opinion. The study proposes a guidance and control strategy based on key nodes, aiming to optimize online public opinion management and improve the efficiency of public crisis response. The article concludes by pointing out the limitations of the study and providing an outlook on future research directions.