Identifying Influential Nodes in Community Networks

Real systems often own strong community attributes. Considering the high clustering and the heterogeneity of communities, a community-based Clustering-LeaderRank (CCL) Algorithm is proposed to identify influential nodes in community networks. Nodes are ranked by the CCL method and other node ranking methods in Dolphin network and Aviation network. Simulation Results show that our method performs well on node ranking and identifying the high-influence nodes.