Information Propagation in Online Social Network Based on Human Dynamics

被引：16
|
作者：
Yan, Qiang [1 ]
Wu, Lianren [1 ]
Liu, Chao [2 ,3 ]
Li, Xiye [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Sch Econ & Management, Beijing 100876, Peoples R China
[2] Arizona State Univ, Dept Elect Engn, Tempe, AZ 85287 USA
[3] Shanghai Univ Finance & Econ, Dept Appl Math, Shanghai 200433, Peoples R China
来源：
ABSTRACT AND APPLIED ANALYSIS | 2013年
关键词：
D O I：
10.1155/2013/953406
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
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. P(tau) similar to tau(-alpha). 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.
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页数：6
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