Dynamic of behavior spread driven by information on weighted networks

In this paper, a new behavior-spread model is proposed, which incorporate the analysis the degree of closely connects, preference for things, and the reciprocal interaction and collaborative spreading of information and behavior on a weighted networks. Comprehensive consideration for the mutual influences of the timeliness, social reinforcement effect of information, and the degree of closely connect between individuals, individual preference on the behavior spread. The study found that, some properties of the information itself, such as timeless and social reinforcement, have impacts on the scope and speed in the information spreading on the network. And subjective factors, such as the degree of closely connect between individuals and individual preference, mainly affect the behavioral conversion rate and the number of individuals has received the information.