danah boyd, Cameron Marlow, Marc Davis and Mor Naaman, all of Yahoo, explore social tagging in detail in their paper presented to ACM/Hypertext06 in Denmark.
Of particular note are the sections on system design and user incentives which cover the differing types of systems and methods behind different implementations of tagging. They also suggest that considerably more research is required into the different ‘lects’ used in tagging and the phenomenon of ‘vocabularly overlap’ between random users’ tags in a short Flickr case study.
Essential reading.
ABSTRACT
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 photo- sharing 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.