The impacts of the individual activity and attractiveness correlation on spreading dynamics in time-varying networks

The heterogeneous distributions of individual activity and attractiveness can significantly affect the dynamic processes in time-varying networks. Here we study the impacts of the correlation between the activity and attractiveness on epidemic spreading and rumor diffusion. Through theoretical analyses and numerical simulations, we find that the temporality of active edges and the correlation between activity and attractiveness in dynamic networks have distinct effects on the two spreading dynamics. In particular, the temporality greatly inhibits the spread of disease, but to a certain extent promotes the diffusion of rumor. As a result, the scale of rumor diffusion in the temporal network is much larger than that of disease spreading. The stronger the correlation between activity and attractiveness in time-varying networks, the more it can accelerate the spread of disease but inhibit the diffusion of rumor. We further study the importance of nodes on disease spreading and rumor diffusion with very large or small products of activity and attractiveness. We find that the nodes with large products of activity and attractiveness in time-varying networks greatly promote the spread of disease, but significantly inhibit the diffusion of rumor. On the contrary, the nodes with small products of activity and attractiveness can promote the rumor diffusion. This work emphasizes the importance of heterogeneity and correlation of individual attributes in different spreading dynamics and contributes to the prevention and control of spreading processes in real time-varying networks.