Co-authorship 2.0: patterns of collaboration in Wikipedia

David Laniado, Riccardo Tasso
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引用次数: 60

Abstract

The study of collaboration patterns in wikis can help shed light on the process of content creation by online communities. To turn a wiki's revision history into a collaboration network, we propose an algorithm that identifies as authors of a page the users who provided the most of its relevant content, measured in terms of quantity and of acceptance by the community. The scalability of this approach allows us to study the English Wikipedia community as a co-authorship network. We find evidence of the presence of a nucleus of very active contributors, who seem to spread over the whole wiki, and to interact preferentially with inexperienced users. The fundamental role played by this elite is witnessed by the growing centrality of sociometric stars in the network. Isolating the community active around a category, it is possible to study its specific dynamics and most influential authors.
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合作2.0:维基百科的合作模式
对wiki中的协作模式的研究可以帮助阐明在线社区创建内容的过程。为了将wiki的修订历史转化为协作网络,我们提出了一种算法,根据数量和社区的接受程度,将提供最多相关内容的用户识别为页面的作者。这种方法的可扩展性使我们能够将英文维基百科社区作为一个共同作者网络来研究。我们发现了一个非常活跃的贡献者核心存在的证据,他们似乎遍布整个wiki,并且优先与没有经验的用户互动。社会计量学明星在网络中日益占据中心地位,证明了这一精英阶层所发挥的根本作用。孤立一个类别周围活跃的社区,可以研究其具体动态和最有影响力的作者。
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HT '22: 33rd ACM Conference on Hypertext and Social Media, Barcelona, Spain, 28 June 2022- 1 July 2022 HT '21: 32nd ACM Conference on Hypertext and Social Media, Virtual Event, Ireland, 30 August 2021 - 2 September 2021 HT '20: 31st ACM Conference on Hypertext and Social Media, Virtual Event, USA, July 13-15, 2020 Detecting Changes in Suicide Content Manifested in Social Media Following Celebrity Suicides. QualityRank: assessing quality of wikipedia articles by mutually evaluating editors and texts
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