SP: Shell-Based Perturbation Approach to Localize Principal Eigen Vector of a Network Adjacency Matrix

Recently, research in the spread of information is found to be a crucial domain in the field of social network analysis. Understanding information spreadability and controllability are the two aspects of the same study. One of the important network parameters, the Inverse Participation Ratio (IPR) of a network adjacency matrix can measure the state of information localization. Higher the value of IPR, the higher the state of localization. This paper proposes a new perturbation approach based on k-shell decomposition to meet the optimal IPR. The proposed Shell-based Perturbation (SP) approach is compared with one of the state-of-the-art approaches: Random Perturbation (RP). The result confirms the superior performance of the proposed SP approach over the existing RP approach.