Most Influential Node Selection in Social Network using Genetic Algorithm

Goal of Influence Maximization problem is to find a top-k powerful nodes as a seed set which has a maximum influence with respect to a propagation model. This is NP-hard in nature. Most of the related algorithms are based on greedy methods, which are computationally expensive. Any exhaustive search algorithm can't discover the good solution in a sensible time. In this paper we introduce a performance oriented algorithm for solving the influence maximization problem using Greedy inspired Genetic Algorithm. We have observed that the performance of proposed algorithm is outperforming similar existing algorithms for maximizing influence Spread.