An Influence Maximization Algorithm Based on Community-Topic Features for Dynamic Social Networks

Real social networks are huge and continueto expand rapidly. Most existing dynamic influence maximization (IM) algorithms are based on the node-to-node propagation model; hence, they have high time complexity and large storage space consumption. They usually reduce computational complexity using a sampling method while sacrificing the influence spread. In this paper, we propose a topic-aware commu...