ABSTRACT
Development of communication technology made information spreading become more convenient and quicker. Individuals, whether it is an online community users or human beings in the word of mouth, are easier to capture the information on prevalence among their friends. Once the prevalent information is acquired, individuals will lose motivation if he found most of his friends already have known the information, as a result, the process of dynamics is influenced. The mechanism and impact of this human behavior is called as “stifling” phenomenon (Daley & Kendall 1964, Isham et al. 2011).According to its information source, stifling involves a dynamic process based on prevalence. In the past research, only local prevalence, i.e., friends and neighbors linked with individuals, have been considered. However, with the rapid development of communication technology, global prevalence information has become easier to get, stifling model with global and local source information is more reasonable. When prevalence information is collected and taken effect, there are two models to reflect different cases in the real world: one is the strength of stifling depends on the contact frequency with neighbors; the other is that stifling process is independent to contact, just using current prevalence as the criterion to enter the stifling state. In the study of rumor model, the first model is more frequently used, so we take this form in our work. In the study of information dynamics on complex networks, the impact of network topology on dynamics cannot be ignored, and random graph, the scale-free network, household and community network have achieved widespread study.
