Measuring the Evolution and Influence in Society’s Information Networks
We analyze and study information transmission by mathematical model. This is of great significance for the purpose to help or inhibit the spread of information. The dissemination of information is complex in the social network with large scale and remarkable heterogeneity. Information dissemination happens mainly through social contact network. We use complex network to model, which is more detailed and practical.
We work on the basis of previous work, and set up a dynamic model according to the network characteristics of the population structure and utilizing dynamics, complex network, qualitative and stability theory of differential equations and mean field approximation. The dynamics model established on the heterogeneous network has a strong universality. And we use some real data to prove the reliability of the model.
We theoretically and numerically prove the global stability of the model, and made sensitivity analysis of the parameters. We find the information energe index of the information is proportional to the heterogeneity of the network. Nodes with large degrees have easy access to information. Different parameters of our model explain different information spreads in different conditions. So these parameters can help us measure the evolution and influence in society’s information networks.
