Insight Into Online Social Network Driven by Explosive Effect

The diversity structure of the information diffusion and network topology on online social networks were investigated in this article. To accurately capture these phenomena, we combined scale-free and small-world networks to construct a new hybrid network, and the characteristics and evolution law of the network topology and information propagation were probed. The proposed network model is as close as possible to a real network. Further, we constructed hybrid propagation models with susceptible-infected-susceptible, susceptible-infected-recovered, and susceptible-infected-recovered-susceptible models mixed in arbitrary proportions. The resulting model is then used to capture the explosive effect, which refers to the explosive characteristic of information propagation by triggering implicit edges. A threshold analysis, mathematical derivation, and simulation of the new model for simulating hybrid networks were conducted. The results were compared with the power-law distribution of five real network data, demonstrating that our network model can effectively simulate the network generation process. Finally, a simulation experiment on the propagation process was performed, and the results were compared with three sets of real data, confirming that the proposed propagation model can accurately predict the spread of information.