Study Of Information Spreading In Complex Network

With the rapid development of computer technology, spreading of information has been changed from mouth-to-mouth into the communication on internet. The speed and width of the spreading become stronger obviously. The spreading ways are more different than the ways before. Till now, the studies on information spreading are mostly based on the SIR model or SIS model of disease, or the model changed from them, but the spreading of information is much different from that of disease.When information is spreading, human characteristics, subject of information, and the communication network are all very important, furthermore, each piece of information will die out finally. However, in the spreading of disease, human is passive, virus can stay active for a long time, and the spreading are via body-touch or air. As a result, the models of disease spreading are not suitable to deal with the spreading of information, especially when the spreading takes place in the internet. In addition, related but opposite information about one event may spread at mean time, and they will interact with each other which makes the spreading much more complicated. Thus, finding the characters of information spreading and choosing a suitable model are hot topics.This thesis explores two topics on information spreading, and the concrete contents are as follows:1. Taking the difference between individuals into account and then set up a new model of information spreading. In consideration of every individual has its unique attribute in real life, a revised information spreading model is proposed with some active or/and stubborn persons in the system, and the model is separately stimulated in a regular network and the corresponding stochastic networks. It's found that under the same initial conditions, the active persons will always improve the information spreading while the stubborn ones will always take the opposite effects, no matter what the network is. Moreover, the stubborn persons have stronger effects in regular networks and the active ones are more important in random networks.2. The multi-information transmission is common in real life system, which makes the communication process much more complicated. Here in this thesis, the spreading of two kinds of information about one issue is studied, and the two kinds of information are set to start spreading at the same time or there is a short lag between them. The simulation results show when there are two kind of information spreading in a system, the spreading range of each will reduce from the situation when there is only one piece of information, but the total of the two will increase. Another finding is that neither kind of information will be believed when the individual received two. Our work is of some significance to further understanding the behavior of information dissemination on complex networks, and to predict the trend of information transmission.