A discrete time dynamic model is proposed for bursty propagation of incidental events based on the node popularity and activeness in blog networks. The parameters of this model are clearly associated with the actual propagation and can reflect the characteristics of the dynamic propagation process. The model can provide a basis for predicting the trend of social events propagation in blog networks. Numerical testing is performed with the data from widely discussed events in Sina Blog, one of the most popular blogospheres in China in several months, and the results show that this model can emulate the actual event propagation and reflect the heavy tail phenomena of the decreasing propagation rate.