Layered centrality tournament ranking: To rank nodes in multilayer networks

The assessment of node centrality in complex networks has been a central issue of great interest. With the continuous evolution of modern science, the single-layer network model is no longer sufficient to meet the current needs of complex networks. It is necessary to accurately identify important nodes in multilayer networks. In this paper, we propose a novel node centrality method called LCTR for multilayer networks. LCTR evaluates node importance by tournament ranking, which combines the node ranking information in both aggregated and expanded formations of a multilayer network. The concept of “tournament ranking” is borrowed from graph theory. Multiple experiments on different datasets reveal that the LCTR method significantly outperforms existing centrality methods.