Crossbred Method: A New Method for Identifying Influential Spreaders from Directed Networks

Influential spreaders are used to maximize or control the spreading dynamics in a network. It acts as a maximizer in the case of information dissemination and a controller to control the epidemic spreading. In the literature, researchers are mostly focused on finding the best spreader from an undirected network. Indeed, the edge’s direction of a spreading process in the network has immense significance while estimating the influential spreaders. This paper presents a novel method, i.e., the “crossbred method” to identify the best spreaders for a directed network. The proposed method considers the spreading properties of the directed network. It takes account of two popular parameters of a spreading process, i.e., node’s out-degree and spreading’s reachability of an originator node. We have verified the spreading performance of the proposed method with the Directed Susceptible-Infected-Recovered (SIR) spreading epidemic model on six real networks. The outcome of the investigation demonstrates that the proposed method achieved significant improvement in terms of spreading dynamics over the existing methods of directed networks such as out-degree centrality, betweenness centrality, pagerank centrality, eigenvector centrality, cluster-rank centrality, outgoing closeness centrality, hybrid centrality.