K-Shell Rank Analysis Using Local Information

  • Akrati Saxena
  • S. R. S. IyengarEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11280)


For network scientists, it has always been an interesting problem to identify the influential nodes in a given network. K-shell decomposition method is a widely used method which assigns a shell-index value to each node based on its influential power. K-shell method requires the entire network to compute the shell-index of a node that is infeasible for large-scale real-world dynamic networks. In the present work, first, we show that the shell-index of a node can be estimated using its \(h^2-index\) which can be computed using local neighborhood information. We further show that \(h^2-index\) has better monotonicity and correlation with the spreading power of the node than the shell-index. Next, we propose hill-climbing based methods to identify top-ranked nodes in a small number of steps. We further propose a heuristic method to estimate the percentile rank of a node without computing influential power of all the nodes.


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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Computer Science and Engineering DepartmentIndian Institute of Technology RoparRupnagarIndia

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