  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 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 others with a power-law waiting time, and (iii)
population growth due to increasing number of interacting individuals. This
unfolding allows us to obtain analytical formula that is fully supported by the
universal patterns in empirical data. Our modeling approaches reveal
"simplicity" beyond complex interacting human activities.
