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In this paper, we discuss the problem of target selection for discovering influential node groups (target set) in a social network. Target set selection has been proven to be NP hard, and a method proposed by Kempe et al. that is based on a greedy algorithm is known as a sophisticated approximate solution method for the target set selection problem. However, since no consideration was given to the dynamic change that occurs in social networks, issues arise with the method proposed by Kempe et al. in networks where the number of nodes and links change. In this paper, we propose an algorithm in which we augment the method of Kempe et al. so that information is diffused while the network is changed over time and influential node groups are discovered from an expected number of diffused nodes.