Analysis of competitive information diffusion in a group-based population over social networks

The dynamics of competitive information diffusion over a connected social network is investigated in this paper. A modified SIR model for two competitive information is presented, where each individual may turn to either of the two information after interacting with a spreader, while the spreader associated with one information may change into the other information. The population is divided into three subgroups: innovators, ordinary and laggard subgroups, respectively. It is assumed that individuals in different subgroups have different spreading rates and switching rates, when they interact with others. The influence of innovators and network topology on the dynamics of the competitive information diffusion is analyzed through numerous numerical simulations. It is observed that innovators and larger network degree can help enlarge the coverage of the information among the population, but they cannot help one information to compete with the other one. Moreover, innovators cannot always accelerate the convergence speed, which depends more on the network topology. (C) 2019 Published by Elsevier B.V.