Abstract
We propose an efficient and accurate measure for ranking spreaders and identifying the influential ones in spreading processes in networks. While the edges determine the connections among the nodes, their specific role in spreading should be considered explicitly. An edge connecting nodes and may differ in its importance for spreading from to and from to . The key issue is whether node , after infected by through the edge, would reach out to other nodes that itself could not reach directly. It becomes necessary to invoke two unequal weights and characterizing the importance of an edge according to the neighborhoods of nodes and . The total asymmetric directional weights originating from a node leads to a novel measure , which quantifies the impact of the node in spreading processes. An -shell decomposition scheme further assigns an -shell index or weighted coreness to the nodes. The effectiveness and accuracy of rankings based on and the weighted coreness are demonstrated by applying them to nine real-world networks. Results show that they generally outperform rankings based on the nodes' degree and -shell index while maintaining a low computational complexity. Our work represents a crucial step towards understanding and controlling the spread of diseases, rumors, information, trends, and innovations in networks.
1 More- Received 26 April 2017
- Revised 3 August 2017
DOI:https://doi.org/10.1103/PhysRevE.96.022323
©2017 American Physical Society