THE ESIS MODEL: ENHANCED SOCIAL INFORMATION SPREAD MODEL FOR MULTI-SOURCE INFORMATION DIFFUSION IN SOCIAL NETWORKS

In this paper, we propose a refined mathematical framework-termed the ‘ESIS model’, to address key limitations found in the classical SSEIR model of information propagation. Since the SSEIR model offers a foundational approach to capturing the dynamics of information spread, it falls short in representing scenarios where information circulates or stays active in a population over time. To overcome this, the ESIS model introduces a modified structure with additional compartments that more accurately represent the real-world flow of information. We develop its corresponding system of dynamic differential equations and offer a thorough state transition diagram to illustrate the behavior of individuals across different stages of information exposure. To assess the performance of the ESIS model, we simulate and compare it against the SSEIR framework through graphical analysis. The results indicate that the ESIS model enables more sustained and realistic propagation, making it a more effective tool for studying long-term influence in social networks and other information-driven systems.