Identifying influential spreaders in interconnected networks

Identifying the most influential spreaders in spreading dynamics is of the utmost importance for various purposes for understanding or controlling these processes. The existing relevant works are limited to a single network. Most real networks are actually not isolated, but typically coupled and affected by others. The properties of epidemic spreading have recently been found to have some significant differences in interconnected networks from those in a single network. In this paper, we focus on identifying the influential spreaders in interconnected networks. We find that the well-known k-shell index loses effectiveness; some insignificant spreaders in a single network become the influential spreaders in the whole interconnected networks while some influential spreaders become no longer important. The simulation results show that the spreading capabilities of the nodes not only depend on their influence for the network topology, but also are dramatically influenced by the spreading rate. Based on this perception, a novel index is proposed for measuring the influential spreaders in interconnected networks. We then support the efficiency of this index with numerical simulations.