A Novel Method of Influence Ranking via Node Degree and H-index for Community Detection
Identifying influential nodes is critical to have a better understanding of the network function and the process of information diffusion. Traditional methods of evaluating influential nodes such as degree centrality ignore the location of a node and its neighbors’ influence in networks, while this plays an important role in revealing the node’s local influence in spreading information. In this paper, we propose a novel method, named DH-index (node Degree and H-index), to measure a node’ importance by considering its and neighbors’ influence simultaneously. Meanwhile, we put forward a node DH-index based label propagation algorithm (DH_LPA) for community detection. We demonstrate its validity and feasibility on a set of real-world and synthetic networks for our new proposed community detection method.
KeywordsInfluence ranking Information diffusion Community detection Label propagation
This work was supported by 973 Program of China (Grant No. 2013CB329601, 2013CB329604, 2013CB329606).
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