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Using big data and network analysis to understand Wikipedia article quality

机译:使用大数据和网络分析来了解Wikipedia的文章质量

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摘要

The research reported in this paper focuses on the question of why Wikipedia articles are different in quality. Since these articles are developed in an open and social environment, our work investigates if the social capital of contributors plays a role in determining the quality of the articles. We focus on three major types of social capital with respect to teams of contributors working on Wikipedia articles: internal bonding, external bridging and functional diversity. Through a social network analysis of these articles based on a dataset extracted from its edit history, our research finds that all three types of social capital have a significant impact on their quality. In addition, we found that internal bonding interacts positively with external bridging resulting in a multiplier effect on article quality. The findings of our research have implications for developing automated techniques for quality assessment of Wikipedia and also provide insights into improving quality of these articles.
机译:本文报道的研究集中在为什么维基百科的文章质量不同的问题上。由于这些文章是在开放的社交环境中开发的,因此我们的工作将调查参与者的社会资本是否在确定文章的质量方面发挥作用。关于致力于维基百科文章的贡献者团队,我们关注社会资本的三种主要类型:内部联系,外部桥接和功能多样性。通过基于从其编辑历史记录中提取的数据集对这些文章进行的社交网络分析,我们的研究发现,所有三种类型的社会资本均对其质量产生重大影响。此外,我们发现内部粘合与外部桥接正向相互作用,从而对制品质量产生倍增效应。我们研究的结果对开发自动化的维基百科质量评估技术具有启示意义,并且也为提高这些文章的质量提供了见识。

著录项

  • 来源
    《Data & Knowledge Engineering》 |2018年第5期|80-93|共14页
  • 作者

    Liu Jun; Ram Sudha;

  • 作者单位

    Dakota State Univ, Madison, SD USA;

    Univ Arizona, Tucson, AZ 85721 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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