Position Paper , Tagging , Taxonomy
Position Paper , Tagging , Taxonomy
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立场文件、标签、分类
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
Marc Davis
中科院分区：
文献类型：
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作者：
Cameron A. Marlow;Mor Naaman;D. Boyd;Marc Davis
近年来，标签系统变得越来越流行。这些系统使用户能够向互联网资源（如网页、图像、视频）添加关键字（即“标签”），而不依赖于受控词汇。标签系统具有改进搜索、垃圾邮件检测、声誉系统和个人组织的潜力，同时为社会通信和数据挖掘引入了新的模式。这种潜力很大程度上是由于构成许多现行制度基础的社会结构。尽管支持资源标记的应用程序迅速扩展，但标记系统仍然没有得到很好的研究或理解。在本文中，我们简要介绍了迄今为止的学术相关工作。我们提供了一个标记系统的模型，特别是在基于web的系统环境中，以帮助我们说明这些工具可能带来的好处。由于许多这样的系统已经存在，我们提供了标签系统的分类，以帮助告知他们的分析和设计，从而使研究人员能够构建和比较这些系统的可持续性的证据。我们还提供了激励和贡献模型的简单分类，以告知潜在的评估框架。虽然这项工作没有提供全面的实证结果，但我们对照片共享和标签系统Flickr进行了初步研究，以证明我们的模型，并在一个样本系统中探讨了一些问题。这一分析有助于我们概述和激励未来可能的标签系统研究方向。
In recent years, tagging systems have become increasingly popular. These systems enable users to add keywords (i.e., “tags”) to Internet resources (e.g., web pages, images, videos) without relying on a controlled vocabulary. Tagging systems have the potential to improve search, spam detection, reputation systems, and personal organization while introducing new modalities of social communication and opportunities for data mining. This potential is largely due to the social structure that underlies many of the current systems. Despite the rapid expansion of applications that support tagging of resources, tagging systems are still not well studied or understood. In this paper, we provide a short description of the academic related work to date. We offer a model of tagging systems, specifically in the context of web-based systems, to help us illustrate the possible benefits of these tools. Since many such systems already exist, we provide a taxonomy of tagging systems to help inform their analysis and design, and thus enable researchers to frame and compare evidence for the sustainability of such systems. We also provide a simple taxonomy of incentives and contribution models to inform potential evaluative frameworks. While this work does not present comprehensive empirical results, we present a preliminary study of the photosharing and tagging system Flickr to demonstrate our model and explore some of the issues in one sample system. This analysis helps us outline and motivate possible future directions of research in tagging systems.