Extending influence maximization by optimizing the network topology

Shuxin Yang, Jianbin Song, Suxin Tong, Yunliang Chen, Guixiang Zhu, Jianqing Wu, Wen Liang

Abstract: Highlights•An Activation Probability-aware framework for edge addition in both static and dynamic social network is proposed.•A seed mining algorithm named IMM++ is given, which help find seeds in the initial stage more effectively.•A method for establishing the influence set of nodes and update strategy in dynamic networks is designed.•Experiments are conducted to validate the outperformance of AP framework.