Human comment dynamics in on-line social systems

Ye Wu*, Changsong ZHOU, Maoying Chen, Jinghua Xiao, Jürgen Kurths

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

Human comment is studied using data from 'tianya' which is one of the most popular on-line social systems in China. We found that the time interval between two consecutive comments on the same topic, called inter-event time, follows a power-law distribution. This result shows that there is no characteristic decay time on a topic. It allows for very long periods without comments that separate bursts of intensive comments. Furthermore, the frequency of a different ID commenting on a topic also follows a power-law distribution. It indicates that there are some "hubs" in the topic who lead the direction of the public opinion. Based on the personal comments habit, a model is introduced to explain these phenomena. The numerical simulations of the model fit well with the empirical results. Our findings are helpful for discovering regular patterns of human behavior in on-line society and the evolution of the public opinion on the virtual as well as real society.

Original languageEnglish
Pages (from-to)5832-5837
Number of pages6
JournalPhysica A: Statistical Mechanics and its Applications
Volume389
Issue number24
DOIs
Publication statusPublished - 15 Dec 2010

Scopus Subject Areas

  • Statistics and Probability
  • Condensed Matter Physics

User-Defined Keywords

  • Human dynamics
  • On-line social systems
  • Power-law distribution

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