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Maximizing Influence-based Group Shapley Centrality
[article]
2020
arXiv
pre-print
One key problem in network analysis is the so-called influence maximization problem, which consists in finding a set S of at most k seed users, in a social network, maximizing the spread of information from S. This paper studies a related but slightly different problem: We want to find a set S of at most k seed users that maximizes the spread of information, when S is added to an already pre-existing - but unknown - set of seed users T. We consider such scenario to be very realistic. Assume a
arXiv:2003.07966v1
fatcat:6dr24ikfvjbrbi23zritfwxpkm