A Large-Scale Characterization of How Readers Browse Wikipedia

IF 2.6 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Tiziano Piccardi, Martin Gerlach, Akhil Arora, Robert West
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引用次数: 0

Abstract

Despite the importance and pervasiveness of Wikipedia as one of the largest platforms for open knowledge, surprisingly little is known about how people navigate its content when seeking information. To bridge this gap, we present the first systematic large-scale analysis of how readers browse Wikipedia. Using billions of page requests from Wikipedia’s server logs, we measure how readers reach articles, how they transition between articles, and how these patterns combine into more complex navigation paths. We find that navigation behavior is characterized by highly diverse structures. Although most navigation paths are shallow, comprising a single pageload, there is much variety, and the depth and shape of paths vary systematically with topic, device type, and time of day. We show that Wikipedia navigation paths commonly mesh with external pages as part of a larger online ecosystem, and we describe how naturally occurring navigation paths are distinct from targeted navigation in lab-based settings. Our results further suggest that navigation is abandoned when readers reach low-quality pages. Taken together, these insights contribute to a more systematic understanding of readers’ information needs and allow for improving their experience on Wikipedia and the Web in general.

读者如何浏览维基百科的大规模表征
尽管维基百科作为最大的开放知识平台之一具有重要性和普遍性,但令人惊讶的是,人们在寻找信息时如何浏览其内容却知之甚少。为了弥补这一差距,我们提出了第一个系统的大规模分析读者如何浏览维基百科。使用维基百科服务器日志中的数十亿个页面请求,我们测量读者如何访问文章,他们如何在文章之间转换,以及这些模式如何组合成更复杂的导航路径。我们发现导航行为具有高度多样化的结构特征。虽然大多数导航路径都很浅,只包含一个页面负载,但路径的深度和形状会随着主题、设备类型和一天中的时间而系统性地变化。我们展示了维基百科导航路径通常与外部页面相啮合,作为更大的在线生态系统的一部分,我们描述了自然发生的导航路径与基于实验室设置的目标导航的区别。我们的研究结果进一步表明,当读者到达低质量的页面时,就会放弃导航。总的来说,这些见解有助于更系统地了解读者的信息需求,并改善他们在维基百科和网络上的总体体验。
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来源期刊
ACM Transactions on the Web
ACM Transactions on the Web 工程技术-计算机:软件工程
CiteScore
4.90
自引率
0.00%
发文量
26
审稿时长
7.5 months
期刊介绍: Transactions on the Web (TWEB) is a journal publishing refereed articles reporting the results of research on Web content, applications, use, and related enabling technologies. Topics in the scope of TWEB include but are not limited to the following: Browsers and Web Interfaces; Electronic Commerce; Electronic Publishing; Hypertext and Hypermedia; Semantic Web; Web Engineering; Web Services; and Service-Oriented Computing XML. In addition, papers addressing the intersection of the following broader technologies with the Web are also in scope: Accessibility; Business Services Education; Knowledge Management and Representation; Mobility and pervasive computing; Performance and scalability; Recommender systems; Searching, Indexing, Classification, Retrieval and Querying, Data Mining and Analysis; Security and Privacy; and User Interfaces. Papers discussing specific Web technologies, applications, content generation and management and use are within scope. Also, papers describing novel applications of the web as well as papers on the underlying technologies are welcome.
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