ClusterRank is a local ranking algorithm which takes into account not only the number of neighbors and the neighbors’ influences, but also the clustering coefficient.
ClusterRank, quantify the influence of a node by taking into account not only its direct influence (measured by the number of its followers) and influences of its neighbors, but also its clustering coefficient. Mathematically, the ClusterRank score si of node i is defined as:
where the term f (ci) accounts for the effect of i’s local clustering and the term ‘+1’ results from the contribution of j itself.
Here f(ci) = 10 -ci

ClusterRank can also be applied to undirected networks where the superiority of ClusterRank is significant compared with degree centrality and k-core decomposition.



  • CHEN, D.-B., GAO, H., LÜ, L. & ZHOU, T. 2013. Identifying Influential Nodes in Large-Scale Directed Networks: The Role of Clustering. PLoS ONE, 8, e77455. DOI: 10.1371/journal.pone.0077455 Publisher web site Endnote RIS file


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