Abstract: With the rapid development of online social networks,extracting information propagation characteristics and building the propagation model have become hot research topics.The traditional propagation models of the microblog network have not considered the users’ incomplete reading behavior,the incubation period and direct immunization at the same time,so they couldn’t accurately identify the immune nodes.In view of these defects,by analyzing the behavior characteristics of the users,the paper proposed a MSLIR which increases the classification of spread individuals and improves the propagation path.The users can get,spread and shield information timely according to the propagation cha-racteristics of microblog information by the algorithm,the function of social network will be improved according to the model response of social relations and online social behaviors.Taking sina microblog as an example,the paper analyzed the effect of the propagation mechanism and network parameters on the processes of information spreading,deduced the dynamic evolution equations and elaborated the temporal evolution rules of the processes of information spreading.Based on the real user datasets of sina microblog,the MSLIR algorithm and its dynamical evolution equations were utilized in the computer simulation for the process of microblog information propagation.Compared with several other representative algorithms,the simulation results show the effectiveness and feasibility of the MSLIR algorithm.

Key words: Microblog,Information propagation,SIR model,Incomplete reading,Incubation period