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Topic-aware Social Influence Minimization
2015
Proceedings of the 24th International Conference on World Wide Web - WWW '15 Companion
In this paper, we address the problem of minimizing the negative influence of undesirable things in a network by blocking a limited number of nodes from a topic modeling perspective. When undesirable thing such as a rumor or an infection emerges in a social network and part of users have already been infected, our goal is to minimize the size of ultimately infected users by blocking k nodes outside the infected set. We first employ the HDP-LDA and KL divergence to analysis the influence and
doi:10.1145/2740908.2742767
dblp:conf/www/YaoSZWG15
fatcat:omn2tnf5rba7pby4vyomt55tpy