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The Third Man: hierarchy formation in Wikipedia
Wikipedia articles are written by teams of independent volunteers in the absence of formal hierarchical organizational structures. How is coordination achieved under such conditions of extreme decentralization? Building on studies on the organization of dominance relations in animal and human societ...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6214276/ https://www.ncbi.nlm.nih.gov/pubmed/30443579 http://dx.doi.org/10.1007/s41109-017-0043-2 |
Sumario: | Wikipedia articles are written by teams of independent volunteers in the absence of formal hierarchical organizational structures. How is coordination achieved under such conditions of extreme decentralization? Building on studies on the organization of dominance relations in animal and human societies, we theorize that coordination in Wikipedia is made possible by an emergent hierarchical order sustained by self-organizing sequences of text editing events. We propose a new method to turn the editing history of Wikipedia pages into an evolving multiplex network resulting from three types of interaction events: dyadic undo, dyadic redo, and third-party based edit events. We develop new relational event models for signed networks that specify how the probability of observing various types of edit events depends on their embeddedness in sequences of past edit events. Using a random sample of page histories comprising 12,719 revisions produced by 7,657 unique users, we examine the relation between theoretically defined sequences of text editing events, and the emergence of linear dominance hierarchies that regulate production relations within Wikipedia. We find evidence that dyadic interaction gives rise to systematic extra-dyadic dependence structures that are partially consistent with a hierarchical interpretation of the Wikipedia editing network. We support and complement the statistical analysis of multiplex event networks with data visualizations that provide qualitative validation of our main results. |
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