我们vs.他们:用回归图可视化来理解维基百科中的社会动态

B. Suh, Ed H. Chi, Bryan A. Pendleton, A. Kittur
{"title":"我们vs.他们:用回归图可视化来理解维基百科中的社会动态","authors":"B. Suh, Ed H. Chi, Bryan A. Pendleton, A. Kittur","doi":"10.1109/VAST.2007.4389010","DOIUrl":null,"url":null,"abstract":"Wikipedia is a wiki-based encyclopedia that has become one of the most popular collaborative on-line knowledge systems. As in any large collaborative system, as Wikipedia has grown, conflicts and coordination costs have increased dramatically. Visual analytic tools provide a mechanism for addressing these issues by enabling users to more quickly and effectively make sense of the status of a collaborative environment. In this paper we describe a model for identifying patterns of conflicts in Wikipedia articles. The model relies on users' editing history and the relationships between user edits, especially revisions that void previous edits, known as \"reverts\". Based on this model, we constructed Revert Graph, a tool that visualizes the overall conflict patterns between groups of users. It enables visual analysis of opinion groups and rapid interactive exploration of those relationships via detail drill- downs. We present user patterns and case studies that show the effectiveness of these techniques, and discuss how they could generalize to other systems.","PeriodicalId":227910,"journal":{"name":"2007 IEEE Symposium on Visual Analytics Science and Technology","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"96","resultStr":"{\"title\":\"Us vs. Them: Understanding Social Dynamics in Wikipedia with Revert Graph Visualizations\",\"authors\":\"B. Suh, Ed H. Chi, Bryan A. Pendleton, A. Kittur\",\"doi\":\"10.1109/VAST.2007.4389010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wikipedia is a wiki-based encyclopedia that has become one of the most popular collaborative on-line knowledge systems. As in any large collaborative system, as Wikipedia has grown, conflicts and coordination costs have increased dramatically. Visual analytic tools provide a mechanism for addressing these issues by enabling users to more quickly and effectively make sense of the status of a collaborative environment. In this paper we describe a model for identifying patterns of conflicts in Wikipedia articles. The model relies on users' editing history and the relationships between user edits, especially revisions that void previous edits, known as \\\"reverts\\\". Based on this model, we constructed Revert Graph, a tool that visualizes the overall conflict patterns between groups of users. It enables visual analysis of opinion groups and rapid interactive exploration of those relationships via detail drill- downs. We present user patterns and case studies that show the effectiveness of these techniques, and discuss how they could generalize to other systems.\",\"PeriodicalId\":227910,\"journal\":{\"name\":\"2007 IEEE Symposium on Visual Analytics Science and Technology\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"96\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE Symposium on Visual Analytics Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VAST.2007.4389010\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE Symposium on Visual Analytics Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VAST.2007.4389010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 96

摘要

维基百科是一个基于维基百科的百科全书,它已经成为最受欢迎的协作在线知识系统之一。与任何大型协作系统一样,随着维基百科的发展,冲突和协调成本也急剧增加。可视化分析工具为解决这些问题提供了一种机制,使用户能够更快、更有效地理解协作环境的状态。在本文中,我们描述了一个识别维基百科条目中冲突模式的模型。该模型依赖于用户的编辑历史和用户编辑之间的关系,尤其是那些使以前的编辑无效的修改,即所谓的“回复”。基于这个模型,我们构建了Revert Graph,这是一个可视化用户组之间整体冲突模式的工具。它可以对意见群体进行可视化分析,并通过细节钻取对这些关系进行快速互动探索。我们提供了用户模式和案例研究,展示了这些技术的有效性,并讨论了如何将它们推广到其他系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Us vs. Them: Understanding Social Dynamics in Wikipedia with Revert Graph Visualizations
Wikipedia is a wiki-based encyclopedia that has become one of the most popular collaborative on-line knowledge systems. As in any large collaborative system, as Wikipedia has grown, conflicts and coordination costs have increased dramatically. Visual analytic tools provide a mechanism for addressing these issues by enabling users to more quickly and effectively make sense of the status of a collaborative environment. In this paper we describe a model for identifying patterns of conflicts in Wikipedia articles. The model relies on users' editing history and the relationships between user edits, especially revisions that void previous edits, known as "reverts". Based on this model, we constructed Revert Graph, a tool that visualizes the overall conflict patterns between groups of users. It enables visual analysis of opinion groups and rapid interactive exploration of those relationships via detail drill- downs. We present user patterns and case studies that show the effectiveness of these techniques, and discuss how they could generalize to other systems.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信