Information Propagation in a Social Network

Information propagation network analysis provides a new way to investigate online activities. From the perspective of information propagation analysis we can understand it in a constant evolving way, that is, the content of the information is modified by the netizens with a certain probability during the whole propagation process. By analysing the online behaviour of netizens, we constructed an information propagation network on social networks. In this paper, we found that the original information can keep its influence on the netizens only when most of them are forwarders. Meanwhile this paper reveals influence propagation is aggregated, for example, netizens tend to give a low rating after a low rating, as well as a high rating following a high rating. Our findings are helpful in better understanding information propagation.