Information dissemination and phase transition in fractal social networks

Abstract

Fractals are a common geometric structure in nature, exhibiting the rich complexity and regularity of the physical world. In the study of complex networks, the self-similarity and multi-layered characteristics of fractal networks make them an ideal model for investigating information dissemination mechanisms. This paper constructs a fractal social network with three-layer granularity structure and proposes a novel dynamic fractal propagation model: F-SI model, in order to explore the factors influencing information propagation and the phase transition phenomena in fractal social networks. In the propagation model, node interest and node contribution are introduced to measure the cumulative impact and propagation probability of nodes in networks of different granularities, and to explore the dynamics of information dissemination under different conditions. The experiments show that information dissemination in fractal social networks exhibits the staircase propagation and phase transition phenomenon. The phase transition is closely related to the group structure and infection density of networks with varying granularities. Research indicates that controlling the propagation speed is more effective in curbing information dissemination in fractal network than controlling the propagation scope. This study provides theoretical guidance for controlling the spread of epidemics and public opinion in networks.