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Impact of Bursty Human Activity Patterns on the Popularity of Online Content

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  • Qiang Yan
  • Lianren Wu

Abstract

The dynamics of online content popularity has attracted more and more researches in recent years. In this paper, we provide a quantitative, temporal analysis about the dynamics of online content popularity in a massive system: Sina Microblog. We use time-stamped data to investigate the impact of bursty human comment patterns on the popularity of online microblog news. Statistical results indicate that the number of news and comments exhibits an exponential growth. The strength of forwarding and comment is characterized by bursts, displaying fat-tailed distribution. In order to characterize the dynamics of popularity, we explore the distribution of the time interval Δ 𠑡 between consecutive comment bursts and find that it also follows a power-law. Bursty patterns of human comment are responsible for the power-law decay of popularity. These results are well supported by both the theoretical analysis and empirical data.

Suggested Citation

  • Qiang Yan & Lianren Wu, 2012. "Impact of Bursty Human Activity Patterns on the Popularity of Online Content," Discrete Dynamics in Nature and Society, Hindawi, vol. 2012, pages 1-11, September.
    • Handle: RePEc:hin:jnddns:872908
    DOI: 10.1155/2012/872908
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    Cited by:

    1. Peng Zhang & Menghui Li & Liang Gao & Ying Fan & Zengru Di, 2014. "Characterizing and Modeling the Dynamics of Activity and Popularity," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-9, February.
    2. Wu, Lianren & Qi, Jiayin & Shi, Nan & Li, Jinjie & Yan, Qiang, 2022. "Revealing the relationship of topics popularity and bursty human activity patterns in social temporal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).

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