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Information Propagation in Online Social Network Based on Human Dynamics

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  • Qiang Yan
  • Lianren Wu
  • Chao Liu
  • Xiye Li

Abstract

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.

Suggested Citation

  • Qiang Yan & Lianren Wu & Chao Liu & Xiye Li, 2013. "Information Propagation in Online Social Network Based on Human Dynamics," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-6, May.
    • Handle: RePEc:hin:jnlaaa:953406
    DOI: 10.1155/2013/953406
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    Cited by:

    1. Zhang, Mingli & Qin, Simeng & Zhu, Xiaoxia, 2021. "Information diffusion under public crisis in BA scale-free network based on SEIR model — Taking COVID-19 as an example," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    2. Zhao, Danling & Sun, Jianbin & Tan, Yuejin & Wu, Jianhong & Dou, Yajie, 2018. "An extended SEIR model considering homepage effect for the information propagation of online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1019-1031.

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