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

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 Δ𝑡 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.

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