Topic-aware Social Influence Minimization

Qipeng Yao, Ruisheng Shi, Chuan Zhou, Peng Wang, Li Guo
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
more » ... vance from a topic modeling perspective. Then two topic-aware heuristics based on betweenness and out-degree for finding approximate solutions to this problem are proposed. Using two real networks, we demonstrate experimentally the high performance of the proposed models and learning schemes.
doi:10.1145/2740908.2742767 dblp:conf/www/YaoSZWG15 fatcat:omn2tnf5rba7pby4vyomt55tpy