Modeling complex social contagions in big data era

In big data era, individuals are surrounded by various kinds of social medium, such as Facebook, Twitter and Microblog. These social media produce vast information every day and support diverse social contagions. However, the dynamics and mechanisms of these social contagions are still obscure and unrevealed because of the big data. In this paper, we propose a novel non-Markovian social contagion model to study behavior spreading under the environment of big data, in which a fraction of global individuals can transmit the behavior information to every susceptible individual, and the remaining local individuals can only transmit the behavior information to neighbors. Through extensive numerical simulations, we find that the global individuals markedly promote the behavior spreading and decrease the critical information transmission probability. In addition, we note that the degree heterogeneity of social network does not change the phenomena qualitatively. Our results may shed some lights in predicting and controlling social contagions. In further, the proposed model may be applied in real simulation platforms for emergency management in big data era.