Modeling and Analyzing Information Propagation Evolution Integrating Internal and External Influences

Online social networks have revolutionized communication, providing individuals with platforms to express their personal opinions on diverse topics. Researchers have independently explored information propagation and opinion evolution within complex networks. However, these phenomena exhibit interconnectedness, where information dissemination influences opinion evolution and vice versa. To address challenges in complex network modeling and opinion-information coupling, internal and external factors are considered in public opinion scenarios by incorporating the crowd effect, enhancement effect, and evolutionary game theory. The susceptible-latent-forwarding-immune-Jager-Amblard (SLFI-JA) model is presented by modifying the SLFI propagation dynamics model and the JA opinion dynamics model, enabling the integration of information propagation and opinion evolution at the microlevel. Through analyzing real-world social hotspots on Sina Weibo, case studies and comparative analyses are conducted to validate the rationality and effectiveness of the proposed model. Furthermore, the findings identify key factors influencing public opinion dissemination and group opinion evolution, offering valuable insights to relevant departments in public opinion response and management. The study aims to mitigate the harmful effects of negative public opinions, prevent extreme adverse online events, and foster a healthier online environment. Online social networks have revolutionized communication, providing individuals with platforms to express opinions on diverse topics. Through considering internal and external factors, the SLFI-JA model is presented, enabling the integration of information propagation and opinion evolution at the micro-level.image

Automated summary

Online social networks have transformed communication by providing individuals with platforms to express opinions. This study presents the SLFI-JA model, which integrates information propagation and opinion evolution by considering internal and external factors. The findings offer valuable insights for public opinion response and management.