Modeling Information Diffusion in Bibliographic Multilayer Networks

Nowadays, most of information systems can be modeled as multilayer networks which each layer includes some nodes connected to each other by different types of links. Information diffusion in networks is the subject that researchers considered recently and they analyzed and modeled this process type in the networks. Although most of researches in this field have focused on single layer networks, but in the real world, because of the complexity of relations, most systems must be modeled as multilayer networks. In the previous works, there are much simplification in problem space, like projection all layer into one layer or negligence the mutual effect of nodes in different layers. So a new effective model for analyzing diffusion in multilayer networks is needed. This method is focused on predicting diffusion in multilayer networks, with considering mutual effect of different layers on each other. The most important specification of this proposed method, is the ability to specify power of all layers and measuring this power regardless node's similarity or difference. In fact, this model can determine the diffusion power of each type of nodes. The model is applied on two real bibliographic information networks, and experimentally demonstrated the effectiveness of this model compared with other diffusion models.