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所有维基媒体项目中协作知识形成过程中的结构性不平等的早期出现。

Early onset of structural inequality in the formation of collaborative knowledge in all Wikimedia projects.

机构信息

Future Technology Analysis Center, Korea Institute of Science and Technology Information, Seoul, Korea.

Department of Liberal Arts, Gyeongnam National University of Science and Technology, Jinju, Korea.

出版信息

Nat Hum Behav. 2019 Feb;3(2):155-163. doi: 10.1038/s41562-018-0488-z. Epub 2018 Dec 17.

Abstract

The Wikimedia project, including Wikipedia, is one of the largest communal data sets and has served as a representative medium to convey collective knowledge in the twenty-first century. Researchers have believed that the analysis of these collaborative digital data sets provides a unique window into the processes of collaborative knowledge formation; yet, in reality, most previous studies have usually focused on its narrow subsets. Here, by analysing all 863 Wikimedia projects (various types and in different languages), we find evidence for a universal growth pattern in communal data formation. We observe that inequality arises early in the development of Wikimedia projects and stabilizes at high levels. To understand the mechanism behind the observed structural inequality, we develop an agent-based model that considers the characteristics of the editors and successfully reproduces the empirical results. Our findings from the Wikimedia projects data, along with other types of collaboration data, such as patents and academic papers, show that a small number of editors have a disproportionately large influence on the formation of collective knowledge. This analysis offers insights into how various collaboration environments can be sustained in the future.

摘要

维基媒体项目,包括维基百科,是最大的公共数据集之一,它已成为在 21 世纪传播集体知识的代表性媒介。研究人员认为,对这些协作式数字数据集的分析为协作式知识形成过程提供了一个独特的窗口;然而,在现实中,大多数先前的研究通常集中在其狭窄的子集上。在这里,通过分析所有 863 个维基媒体项目(各种类型和不同语言),我们发现公共数据形成存在普遍的增长模式。我们观察到,不平等在维基媒体项目的早期发展中就出现了,并在高水平上稳定下来。为了了解观察到的结构性不平等背后的机制,我们开发了一个基于代理的模型,该模型考虑了编辑者的特征,并成功地再现了经验结果。我们从维基媒体项目数据以及其他类型的合作数据(如专利和学术论文)中发现,少数编辑者对集体知识的形成有着不成比例的巨大影响。这项分析深入了解了未来如何维持各种协作环境。

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