Information diffusion in interconnected heterogeneous networks
Shahin Mahdizadehaghdam, Han Wang, Hamid Krim, Liyi Dai
Abstract
In this paper, we are interested in modeling the diffusion of information in a multilayer network of agents using a thermodynamic diffusion approach. The state of each agent is viewed as a topic mixture, to describe his/her resources, and represented by a distribution over multiple topics. We observe and learn diffusion-related thermodynamical patterns in the training data set, and we use the estimated diffusion structure to predict the future states of the agents. With a priori knowledge of a fraction of the state of all agents, the problem is shown to turn into a Kalman predictor problem that refines the predicted system states using the estimation error of the agents' states. A real world Twitter data set is then used to evaluate and validate our information diffusion model.
BibTeX
@inproceedings{icassp2017_informationdiffu,
title = {Information diffusion in interconnected heterogeneous networks},
author = {Shahin Mahdizadehaghdam and Han Wang and Hamid Krim and Liyi Dai},
booktitle = {ICASSP 2017},
year = {2017}
}