Scalable Influence-Aware Profit Maximization Over Livestreaming Marketing Network

. Profit maximization (PM), with the purpose to select the appropriate set of initial seed users to maximize the effectiveness of diffusion, has become the focus of Social Network Analysis with broad prospects of applications such as social opinion propagation and Internet marketing. Under the condition of ensuring great performance, the existing PM models are faced with the challenge of time complexity and universality because they take too long to execute and their working conditions come-= with harsh restrictions. In this paper, we propose a new algorithm named CirclePrune (CP) which optimizes the runtime in large-scale network and loosens the constraints by warming up, and apply it to the scenario of livestreaming marketing. Experimental results confirm the effectiveness and efficiency for the CP algorithm.