Rumor spreading model considering hesitating mechanism in complex social networks

The study of rumor spreading has become an important issue on complex social networks. On the basis of prior studies, we propose a modified ​susceptible–exposed–infected–removed (SEIR) model with hesitating mechanism by considering the attractiveness and fuzziness of the content of rumors. We derive mean-field equations to characterize the dynamics of SEIR model on both homogeneous and heterogeneous networks. Then a steady-state analysis is conducted to investigate the spreading threshold and the final rumor size. Simulations on both artificial and real networks show that a decrease of fuzziness can effectively increase the spreading threshold of the SEIR model and reduce the maximum rumor influence. In addition, the spreading threshold is independent of the attractiveness of rumor. Simulation results also show that the speed of rumor spreading obeys the relation “BA network > WS network”, whereas the final scale of spreading obeys the opposite relation.