An efficient spreading strategy considering information decays and partial interactions between people in scale-free networks

Abstract

Complex networks are extensively applied to study the dynamics of real systems, such as how information spreads in social networks. Most existing spreading strategies are studied based on simple information spreading model, such as the optimized compartmental models in epidemics. However, for information spreading in social networks, more complex social factors should be considered. In this paper, we build an information spreading model that involves information decays and partial interactions based on multi-agent modeling in scale-free networks. The positive effects of a set of vertices on the spreading efficiency are discovered based on the proposed information spreading model. On the basis of the positive effects of those vertices, we propose an efficient spreading strategy for extending the spreading in scale-free networks. Ten groups of Monte Carlo experiments are conducted to verify the effectiveness of the proposed strategy. The experimental results demonstrated the effectiveness and validity of the proposed strategy. The proposed strategy can be exploited to extend the spread of warnings or control the spread of rumors in social networks.