Understanding Open Collaboration of Wikipedia Good Articles with Factor Analysis

H. Chou, Donghui Lin, T. Ishida
{"title":"Understanding Open Collaboration of Wikipedia Good Articles with Factor Analysis","authors":"H. Chou, Donghui Lin, T. Ishida","doi":"10.1142/s0219649222500307","DOIUrl":null,"url":null,"abstract":"This research aims at understanding the open collaboration involved in producing Wikipedia Good Articles (GA). To achieve this goal, it is necessary to analyse who contributes to the collaborative creation of GA and how they are involved in the collaboration process. We propose an approach that first employs factor analysis to identify editing abilities and then uses these editing abilities scores to distinguish editors. Then, we generate sequence of editors participating in the work process to analyse the patterns of collaboration. Without loss of generality, we use GA of three Wikipedia categories covering two general topics and a science topic to demonstrate our approach. The result shows that we can successfully generate editor abilities and identify different types of editors. Then we observe the sequence of different editor involved in the creation process. For the three GA categories examined, we found that GA exhibited the characteristic of highly scored content-shaping ability editors involved in the later stage of the collaboration process. The result demonstrates that our approach provides a clearer understanding of how Wikipedia GA are created through open collaboration.","PeriodicalId":127309,"journal":{"name":"J. Inf. Knowl. Manag.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Inf. Knowl. Manag.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s0219649222500307","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This research aims at understanding the open collaboration involved in producing Wikipedia Good Articles (GA). To achieve this goal, it is necessary to analyse who contributes to the collaborative creation of GA and how they are involved in the collaboration process. We propose an approach that first employs factor analysis to identify editing abilities and then uses these editing abilities scores to distinguish editors. Then, we generate sequence of editors participating in the work process to analyse the patterns of collaboration. Without loss of generality, we use GA of three Wikipedia categories covering two general topics and a science topic to demonstrate our approach. The result shows that we can successfully generate editor abilities and identify different types of editors. Then we observe the sequence of different editor involved in the creation process. For the three GA categories examined, we found that GA exhibited the characteristic of highly scored content-shaping ability editors involved in the later stage of the collaboration process. The result demonstrates that our approach provides a clearer understanding of how Wikipedia GA are created through open collaboration.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用因子分析法理解维基百科好文章的开放合作
本研究旨在了解维基百科好文章(GA)制作过程中的开放合作。为了实现这一目标,有必要分析谁为GA的协作创建做出了贡献,以及他们如何参与协作过程。我们提出了一种方法,首先使用因子分析来识别编辑能力,然后使用这些编辑能力得分来区分编辑。然后,我们生成参与工作过程的编辑序列,以分析协作模式。在不失去一般性的情况下,我们使用三个维基百科类别的遗传算法,涵盖两个一般主题和一个科学主题来演示我们的方法。结果表明,我们可以成功地生成编辑能力并识别不同类型的编辑。然后我们观察不同编辑器在创建过程中所涉及的顺序。对于三个被检查的GA类别,我们发现GA表现出高得分的内容塑造能力编辑参与协作过程的后期阶段的特征。结果表明,我们的方法提供了一个更清晰的理解维基百科GA是如何通过开放协作创建的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Knowledge Management in Higher Education in Vietnam: Insights from Higher Education Leaders - An Exploratory Study The Organisation's Size-Innovation Performance Relationship: The Role of Human Resource Development Mechanisms A Comparative Review of Sentimental Analysis Using Machine Learning and Deep Learning Approaches Vocational Education Information Technology Based on Cross-Attention Fusion Knowledge Map Recommendation Algorithm Redesigning Knowledge Management Through Corporate Sustainability Strategy in the Post-Pandemic Era
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1