FLOCK EFFECT DRIVES INFORMATION FRACTAL PROPAGATION

Abstract

In this paper, first, the structure of social networks was investigated from fractal perspective and the fractal network was built from online social networks. Then inspired by the flock effect, the characteristics of “separation”, “cohesion” and “alignment” in information propagation were studied from the inherent granularity structure of fractal communities. Accordingly, the agreement degree and controversy degree between community members at different granularities were defined. And the “Seeking Common Ground While Shelving Differences” propagation rule in fractal network was presented. On this basis, a new S2I propagation model was proposed. From this model, communicators were divided into two states, I and OI. People in status I have a tendency to express support for a message. While those in state OI have a tendency to oppose it. The information propagation process and characteristics were analyzed further by using S2I model. Finally, the effectiveness of S2I model was verified by comparative experiments of simulation and real data analysis.