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来自维基百科编辑数据的社会群体规模的因果证据。

Causal evidence for social group sizes from Wikipedia editing data.

作者信息

Burgess M, Dunbar R I M

机构信息

ChiTek-i AS, Oslo, Norway.

Department of Experimental Psychology, University of Oxford, Radcliffe Quarter, Oxford OX2 6GG, UK.

出版信息

R Soc Open Sci. 2024 Oct 2;11(10):240514. doi: 10.1098/rsos.240514. eCollection 2024 Oct.

Abstract

Human communities have self-organizing properties in which specific Dunbar Numbers may be invoked to explain group attachments. By analysing Wikipedia editing histories across a wide range of subject pages, we show that there is an emergent coherence in the size of transient groups formed to edit the content of subject texts, with two peaks averaging at around for the size corresponding to maximal contention, and at around as a regular team. These values are consistent with the observed sizes of conversational groups, as well as the hierarchical structuring of Dunbar graphs. We use a model of bipartite trust to derive a scaling law that fits the data and may apply to all group size distributions when these are based on attraction to a seeded group process. In addition to providing further evidence that even spontaneous communities of strangers are self-organizing, the results have important implications for the governance of the Wikipedia commons and for the security of all online social platforms and associations.

摘要

人类社群具有自组织特性,其中特定的邓巴数可用于解释群体依恋。通过分析维基百科广泛主题页面的编辑历史,我们发现,为编辑主题文本内容而形成的临时群体规模存在一种涌现的连贯性,对应最大争议的规模有两个峰值,平均约为[具体数值1],作为常规团队的规模平均约为[具体数值2]。这些值与观察到的对话群体规模以及邓巴图的层次结构一致。我们使用二分信任模型推导出一个符合数据的标度律,当所有群体规模分布基于对种子群体过程的吸引力时,该标度律可能适用于所有群体规模分布。除了进一步证明即使是陌生人的自发社群也具有自组织性外,这些结果对维基百科 Commons 的治理以及所有在线社交平台和协会的安全具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1df6/11444758/3be99cddc7ba/rsos.240514.f001.jpg

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