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Abstract and Applied Analysis
Volume 2013, Article ID 953406, 6 pages
Research Article

Information Propagation in Online Social Network Based on Human Dynamics

1School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China
2Department of Electrical Engineering, Arizona State University, Tempe, AZ 85287, USA
3Department of Applied Mathematics, Shanghai University of Finance and Economics, Shanghai 200433, China

Received 16 January 2013; Revised 10 April 2013; Accepted 18 April 2013

Academic Editor: Bo Shen

Copyright © 2013 Qiang Yan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We investigate the impact of human dynamics on the information propagation in online social networks. First, statistical properties of the human behavior are studied using the data from “Sina Microblog,” which is one of the most popular online social networks in China. We find that human activity patterns are heterogeneous and bursty and are often described by a power-law interevent time distribution . Second, we proposed an extended Susceptible-Infected (SI) propagation model to incorporate bursty and limited attention. We unveil how bursty human behavior and limited attention affect the information propagation in online social networks. The result in this paper can be useful for optimizing or controlling information propagation in online social networks.