Efficient target strategies for contagion in scale-free networks

Abstract

Organizations or individuals often have an incentive to target a certain number of agents to launch a contagion process effectively and efficiently, for example, sampling consumers in the diffusion of new products. We present an effective strategy for contagion in scale-free networks. The proposed strategy, hub strategy, calls for targeting mostly the highly connected nodes. The biased level implemented in this strategy characterizes its ability to identify hub nodes. We demonstrate that hub strategy can improve the contagion effects evidently. We find that biased level increases first with heterogeneity level of contagion network but decreases with that after a certain value, and decreases with initial adopter rate all the time. Moreover, degree correlations in contagion networks may reduce biased level.