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Wikipedia is a free Internet encyclopedia with an enormous amount of content. This encyclopedia is written by volunteers with various backgrounds in a collective fashion; anyone can access and edit most of the articles. This open-editing nature may give us prejudice that Wikipedia is an unstable and unreliable source; yet many studies suggest that Wikipedia is even more accurate and self-consistent than traditional encyclopedias. Scholars have attempted to understand such extraordinary credibility, but usually used the number of edits as the unit of time, without consideration of real time. In this work, we probe the formation of such collective intelligence through a systematic analysis using the entire history of 34,534,110 English Wikipedia articles, between 2001 and 2014. From this massive data set, we observe the universality of both timewise and lengthwise editing scales, which suggests that it is essential to consider the real-time dynamics. By considering real time, we find the existence of distinct growth patterns that are unobserved by utilizing the number of edits as the unit of time. To account for these results, we present a mechanistic model that adopts the article editing dynamics based on both editor-editor and editor-article interactions. The model successfully generates the key properties of real Wikipedia articles such as distinct types of articles for the editing patterns characterized by the interrelationship between the numbers of edits and editors, and the article size. In addition, the model indicates that infrequently referred articles tend to grow faster than frequently referred ones, and articles attracting a high motivation to edit counterintuitively reduce the number of participants. We suggest that this decay of participants eventually brings inequality among the editors, which will become more severe with time.
A number of human activities exhibit a bursty pattern, namely periods of very high activity that are followed by rest periods. Records of this process generate time series of events whose inter-event times follow a probability distribution that displ
It is generally accepted that neighboring nodes in financial networks are negatively assorted with respect to the correlation between their degrees. This feature would play an important damping role in the market during downturns (periods of distress
We perform an in-depth analysis on the inequality in 863 Wikimedia projects. We take the complete editing history of 267,304,095 Wikimedia items until 2016, which not only covers every language edition of Wikipedia, but also embraces the comple
In their recent work Scale-free networks are rare, Broido and Clauset address the problem of the analysis of degree distributions in networks to classify them as scale-free at different strengths of scale-freeness. Over the last two decades, a multit
A model for the probabilistic function followed in Wikipedia edition is presented and compared with simulations and real data. It is argued that the probability to edit is proportional to the editors number of previous editions (preferential attachme