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The problem of influence maximization aims to specify the small number of initial individuals that will eventually influence the individuals as much as possible, which has aroused wide attention of researchers. However, the most existing work is limited to the static social network and ignores the role of time in information propagation. In this paper, we analyze the influence maximization problem in temporal social networks and present a greedy-based on the latency-aware independent cascadedoi:10.1109/access.2019.2894155 fatcat:3zt6whdoeja3rkjqbm3prdo26e