Improving information centrality of a node in complex networks by adding edges

The problem of increasing the centrality of a network node arises in many practical applications. In this paper, we study the optimization problem of maximizing the information centrality Iv of a given node v in a network with n nodes and m edges, by creating k new edges incident to v. Since Iv is the reciprocal of the sum of resistance distance Rv between v and all nodes, we alternatively consider the problem of minimizing Rv by adding k new edges linked to v. We show that the objective function is monotone and supermodular. We provide a simple greedy algorithm with an approximation factor left(1-frac1eright) and O(n3) running time. To speed up the computation, we also present an algorithm to compute left(1-frac1e-εright)-approximate resistance distance Rv after iteratively adding k edges, the running time of which is widetildeO (mkε-2) for any ε>0, where the widetildeO (·) notation suppresses the rm poly (log n) factors. We experimentally demonstrate the effectiveness and efficiency of our proposed algorithms.