在协作标记社区中跟踪用户注意力
Tracking User Attention in Collaborative Tagging Communities
摘要：
由于CiteULike、del.icio.us和Flickr等内容共享系统的流行，协作标记最近引起了工业界和学术界的关注。这些系统使用户有机会添加数据项，并将自己的元数据（或标签）附加到存储的数据。其结果是为个人用户提供了一个有效的内容管理工具。然而，最近的研究表明，随着标记社区的增长，由于内容多样性的简化，增加的内容和元数据变得更难管理。因此，应对多样性增加的机制是提高协同标注系统的可扩展性和可用性的基础。本文分析了在不断增长的知识空间中，是否可以利用使用模式来提高可导航性。为此，它提出了两个协作标记社区，目标科学文献：CiteULike和Bibsonomy的特征。我们探索了三个主要方向：首先，我们分析了用户群体中的标签活动分布。其次，我们定义了新的度量用户兴趣的相似性，并使用这些度量来揭示我们研究的标记社区的结构。我们发现的结构表明，兴趣被清晰地划分为大量具有独特偏好的个人和一组具有分散兴趣的核心用户。最后，我们提供了初步的结果表明，基于兴趣的结构的标记社区可以用来促进内容的使用作为社区规模。
英文摘要：
Collaborative tagging has recently attracted the attention of both industry and academia due to the popularity of content-sharing systems such as CiteULike, del.icio.us, and Flickr. These systems give users the opportunity to add data items and to attach their own metadata (or tags) to stored data. The result is an effective content management tool for individual users. Recent studies, however, suggest that, as tagging communities grow, the added content and the metadata become harder to manage due to an ease in content diversity. Thus, mechanisms that cope with increase of diversity are fundamental to improve the scalability and usability of collaborative tagging systems. This paper analyzes whether usage patterns can be harnessed to improve navigability in a growing knowledge space. To this end, it presents a characterization of two collaborative tagging communities that target scientific literature: CiteULike and Bibsonomy. We explore three main directions: First, we analyze the tagging activity distribution across the user population. Second, we define new metrics for similarity in user interest and use these metrics to uncover the structure of the tagging communities we study. The structure we uncover suggests a clear segmentation of interests into a large number of individuals with unique preferences and a core set of users with interspersed interests. Finally, we offer preliminary results that demonstrate that the interest-based structure of the tagging community can be used to facilitate content usage as communities scale.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
