Unfolding large-scale online collaborative human dynamics

Significance This paper uncovered a universal double–power-law distribution of interupdate times for articles in Wikipedia and unfolded the seemingly complex collaborative patterns into three generic modules related to individual behavior, interaction among individuals, and population growth. The model is analytically solved and fully supported by the real data. As this model does not depend on any specific rules of Wikipedia, it is highly applicable for other online collaborative systems like software development and email communication. Similar scaling properties and models were reported for earthquake recurrence times, suggesting that interacting natural and social systems share universal collective mechanisms. Large-scale interacting human activities underlie all social and economic phenomena, but quantitative understanding of regular patterns and mechanism is very challenging and still rare. Self-organized online collaborative activities with a precise record of event timing provide unprecedented opportunity. Our empirical analysis of the history of millions of updates in Wikipedia shows a universal double–power-law distribution of time intervals between consecutive updates of an article. We then propose a generic model to unfold collaborative human activities into three modules: (i) individual behavior characterized by Poissonian initiation of an action, (ii) human interaction captured by a cascading response to previous actions with a power-law waiting time, and (iii) population growth due to the increasing number of interacting individuals. This unfolding allows us to obtain an analytical formula that is fully supported by the universal patterns in empirical data. Our modeling approaches reveal “simplicity” beyond complex interacting human activities.

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