Information diffusion in interconnected heterogeneous networks
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.
Cite
@article{arxiv.1707.05150,
title = {Information diffusion in interconnected heterogeneous networks},
author = {Shahin Mahdizadehaghdam and Han Wang and Hamid Krim and Liyi Dai},
journal= {arXiv preprint arXiv:1707.05150},
year = {2017}
}
Comments
5-9 March 2017. arXiv admin note: substantial text overlap with arXiv:1602.04854