Analyzing the Complexity of Public Opinion Evolution on Weibo: A Super Network Model

Social media networks play a crucial role in encouraging the emergence and development of public opinion (PO) events due to the rapid advancement in social networking. Weibo is a brand new mode of communication in China. The growth of Weibo rose due to the mix of technological improvement and socially significant events. This study contributes to investigating the complexity of PO dissemination and the evolution of Weibo in China. To achieve this, a super network model is constructed. The study starts by introducing a media-influenced dissemination model that takes into account viewpoint similarity. An evolutionary model is then developed to explore the interaction among PO, environmental information, netizens, and opinion leaders. The study also considers the role of Weibo.com platform characteristics in information acquisition. To simulate the overall pattern and cyclic characteristics of communication, the Net logo is utilized as a tool. Hypothesis testing is employed to validate the proposed hypothesis. The novelty of the study lies in analyzing the dynamic evolution of public sentiment on Weibo. Real-life PO events are analyzed to identify the factors that affect opinion evolution. Based on these findings, the study proposes guidance strategies and specific feasible schemes to manage real crises. The study suggests that the overall emotional characteristics of Chinese netizens and the existence of network promoters are considered, bringing the model closer to the authentic Weibo PO scenario.