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Visualizing large-scale human collaboration in Wikipedia

机译：在Wikipedia中可视化大规模的人类协作

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摘要

Volunteer-driven large-scale human-to-human collaboration has become common in the Web 2.0 era. Wikipedia is one of the foremost examples of such large-scale collaboration, involving millions of authors writing millions of articles on a wide range of subjects. The collaboration on some popular articles numbers hundreds or even thousands of co-authors. We have analyzed the co-authoring across entire Wikipedias in different languages and have found it to follow a geometric distribution in all the language editions we studied. In order to better understand the distribution of co-author counts across different topics, we have aggregated content by category and visualized it in a form resembling a geographic map. The visualizations produced show that there are significant differences of co-author counts across different topics in all the Wikipedia language editions we visualized. In this article we describe our analysis and visualization method and present the results of applying our method to the English, German, Chinese, Swedish and Danish Wikipedias. We have evaluated our visualization against textual data and found it to be superior in usability, accuracy, speed and user preference.
机译：在Web 2.0时代，由志愿者驱动的大规模人与人协作已变得很普遍。维基百科是这种大规模合作的最重要的例子之一，数以百万计的作者参与撰写了涉及广泛主题的数百万篇文章。在一些热门文章上的合作有数百甚至数千位合著者。我们分析了整个Wikipedias中不同语言的合著，发现在我们研究的所有语言版本中，它都遵循几何分布。为了更好地了解不同主题中合著者人数的分布，我们按类别汇总了内容，并以类似于地理地图的形式将其可视化。产生的可视化结果表明，在我们可视化的所有Wikipedia语言版本中，不同主题之间的合著者人数存在显着差异。在本文中，我们描述了我们的分析和可视化方法，并介绍了将该方法应用于英语，德语，中文，瑞典语和丹麦语Wikipedias的结果。我们已经根据文字数据评估了可视化效果，发现它在可用性，准确性，速度和用户偏好方面都非常出色。

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