HCC: Medium: Collaborative Research: Guiding Folksonomy Development to Enable Novel Tagging Applications

这是一项关于标记、用户将标签分配给信息对象以及由此产生的“大众分类法”分类系统的研究。到了19世纪，越来越多的信息被公布，显然需要有效的组织方法才能使信息可用。作为回应，发明了像国会图书馆分类法和杜威十进制分类法这样的分类方案。整个信息传播系统包含明确的角色和分工：编辑决定发布什么，信息专业人员对发布的作品进行分类，大多数人只是消费结果。互联网颠覆了这一传统方式。没有出版障碍，所以网上可以获得更多数量级的信息，信息专业人士跟不上。然而，在这种情况下工作的新技术已经出现，特别是标记。任何用户都可以将标签与文档、电影或照片等项目相关联，这些标签用作检索的键。由于标签可以由任何用户创建，贡献的标签数量随社区的大小而变化：因此，标签在互联网范围内起作用。标签让用户表达他们自己的观点，这有助于检索。然而，标签是一项年轻的技术，有着巨大的挑战和未被开发的潜力。单个标签的质量往往很差，而且许多标签系统在全球范围内都不连贯。对正在使用的标签系统进行的经验评估很少，也没有与传统方法进行正式比较。标记应用主要局限于搜索。该项目解决了这些挑战。它将对标记作为一种分类方法的优点和缺点有一个更坚定的科学理解。它将探索标记的潜力，使强大的应用超越信息检索。该项目包括三个主要的研究活动：(1)创建一组度量来量化分类结构的价值；将这些度量用于标注系统与传统分类系统的形式和经验比较；(2)设计混合主动交互技术，用于计算主体和人来发现、评估和解决标注系统中的问题；(3)开发新颖的基于标记的应用程序，供用户表达他们的偏好并在复杂的信息空间中导航。本研究将创建基于信息理论和基于使用的度量来度量分类结构的价值。将进行研究，以展示这两种指标之间的关系，让设计师预测，例如，有效的用户搜索每件商品需要多少标签。将对标签系统与传统的专家分类进行系统的成本效益比较，从而为一场以激烈猜测为特征的辩论提供经验数据。一套混合主动交互技术和新应用的实用性和通用性将通过(A)在多个平台上实施，以及(B)在仔细的现场实验中进行评估来建立。提高标记的有效性将帮助数百万用户找到他们所寻找的信息、产品和服务。更直接的是，这个项目的技术将在四个工作的在线社区中实施，面向电影观众、骑自行车的人、伦理研究人员和对政治感兴趣的公民。这些网站总共拥有数以万计的用户，所有这些用户都将直接受益。许多学生将接受培训，学习多种研究方法，并获得真正的在线社区的宝贵经验。最后，该软件将在开放源码许可下开发，并将发布数据集，从而为其他研究人员和网站开发人员的工作提供便利。

This is a study of tagging, the assignment of labels to information objects by users, and the "folksonomy" categorization systems that can result. By the 19th Century, increasing amounts of information were being published, and it was clear that efficient methods of organization were needed for the information to be accessible. In response, categorization schemes like the Library of Congress Classification and the Dewey Decimal System were invented. The overall information dissemination system contained clear roles and divisions of labor: editors decided what got published, information professionals categorized published works, and most people simply consumed the results. The Internet has toppled this traditional approach. There is no publication barrier, so orders of magnitude more information is available online and information professionals cannot keep up. However, new technologies have arisen that work in this context, notably tagging. Any user can associate tags with items such as documents, movies, or photos, and the tags serve as keys for retrieval. Since tags can be created by any user, the number of tags contributed scales with a community's size: thus, tagging works at Internet scale. Tagging lets users represent their own perspectives, which aids retrieval.However, tagging is a young technology, with significant challenges and unmet potential. Individual tags are often of poor quality, and many tagging systems are globally incoherent. Empirical evaluations of tagging systems in use are few, and formal comparisons to traditional approaches have not been done. Tagging applications have been limited mainly to search. This project addresses these challenges. It will develop a firmer scientific understanding of the strengths and weaknesses of tagging as a categorization method. It will explore the potential of tagging to enable powerful applications beyond information retrieval. The project consists of three main research activities: (1) Creating a set of metrics to quantify the value of a categorization structure; using these metrics in formal and empirical comparisons of tagging systems to traditional categorizations; (2) Designing mixed-initiative interaction techniques for computational agents and people to detect, evaluate and resolve problems in tagging systems; (3) Developing novel tag-based applications for users to express their preferences and navigate complex information spaces.This research will create both information-theoretic and usage-based metrics to measure the value of a categorization structure. Studies will be done to show relations between the two types of metric, letting designers predict, for example, how many tags per item are required for effective user search. Systematic cost-benefit comparisons of tagging systems to traditional expert categorizations will be done, thus providing empirical data to a debate that has been characterized by heated conjecture. The utility and generality of a set of mixed-initiative interaction techniques and novel applications will be established by (a) implementing them in multiple platforms, and (b) evaluating them in careful field experiments.Improving the effectiveness of tagging will help millions of users find the information, products, and services they seek. More directly, the techniques of this project will be implemented in four working online communities, for movie viewers, cyclists, ethics researchers, and politically interested citizens. Collectively these sites have tens of thousands of users, all of whom will benefit directly. Many students will be trained, learning multiple research methods and gaining valuable experience with real online communities. Finally, the software will be developed under an open source license and datasets will be published, thus facilitating other researchers and web site developers in their work.