Maximizing topic propagation driven by multiple user nodes in micro-blogging

This work investigates the maximization of topic propagation jointly driven by multiple user nodes in micro-blogging. In this paper, we propose a new method to find a set of user nodes that jointly propagate topics approximately the most widely. First, we obtain multiple nodes with strong influence; Second, we exactly compute the breadth of information spread driven by a single node based on probabilistic models; Finally, we analyze the information propagation jointly driven by multiple nodes and derive an approximately optimal set of driving nodes. We find that the breadth of information propagation jointly driven by multiple nodes is approximately linear with both the breadth of information propagation of single driving nodes and the strength of tie among them, which indicates that selecting the optimal driving nodes needs to consider the link information among them as well as the ability of each node. Experimental results demonstrate the effectiveness of our method.