Shortest path of temporal networks: An information spreading-based approach

The shortest path is a widely studied network science problem and has attracted great attention. Nevertheless, it draws little attention in temporal networks, in which temporal edges determine information dissemination. In this paper, we propose an information spreading-based method to calculate the shortest paths distribution in temporal networks. We verify our method on both artificial and real-world temporal networks and obtain a good agreement. We further generalize our method to identify influential nodes and found an effective method. Finally, we verify the influential nodes identifying method on four networks.