In this paper, a stochastic network based information propagation model is developed. The model describes the information flow in interconnected networks with arbitrary degree distribution. Network connections propagate the information according to independent Poisson processes. A probabilistic differential equation system is derived and solved numerically for the expected reception times. By solving the differential equation system numerically, we can determine: -- the expected the number of informed nodes as a function time, -- the degree distribution of the set of informed nodes at every specific instant -- and the relationship between the node degree and its reception time. The validity of the results is justified by a network simulation. The characteristics of the information propagation were analyzed in scale-free and Erd\H os--R\'enyi networks.
In this paper, a stochastic network based information propagation model is developed. The model describes the information flow in interconnected networks with arbitrary degree distribution. Network connections propagate the information according to independent Poisson processes. A probabilistic differential equation system is derived and solved numerically for the expected reception times. By solving the differential equation system numerically, we can determine: - the expected number of informed nodes as a function time, - the degree distribution of the set of informed nodes at every specific instant - and the relationship between the node degree and its reception time. The validity of the results is justified by a network simulation. The characteristics of the information propagation were analyzed in scale-free and Erd\H os--R\'enyi networks.
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