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arXiv · 1707.05150

Information diffusion in interconnected heterogeneous networks

Shahin Mahdizadehaghdam·Han Wang·Hamid Krim·Liyi Dai
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Abstract

In this paper, we are interested in modeling the diffusion of information in a multilayer network using thermodynamic diffusion approach. State of each agent is viewed as a topic mixture represented by a distribution over multiple topics. We have observed and learned diffusion-related thermodynamical patterns in the training data set, and we have used the estimated diffusion structure to predict the future states of the agents. A priori knowledge of a fraction of the state of all agents changes the problem to be a Kalman predictor problem that refines the predicted system state using the error in estimation of the agents. A real world Twitter data set is then used to evaluate and validate our information diffusion model.

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Shahin Mahdizadehaghdam, Han Wang, Hamid Krim, Liyi Dai. 2017-07-13. Information diffusion in interconnected heterogeneous networks. https://doi.org/10.1109/icassp.2017.7952859

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