Models of collaborative tagging

Many have argued that social tagging or collaborative tagging systems can provide navigational cues or “way-finders” for other users to explore information. The notion is that, given that social tags are labels that users create to represent topics extracted from Web documents, interpretation of these tags should allow other users to predict contents of different documents efficiently. Social tags are arguably more important in exploratory search, in which the users may engage in iterative cycles of goal refinement and exploration of new information (as opposed to simple fact-retrievals), and interpretation of information contents by others will provide useful cues for people to discover topics that are relevant. One significant challenge that arises in social tagging systems is the rapid increase in the number and diversity of the tags. As opposed to structured annotation systems, tags provide users an unstructured, open-ended mechanism to annotate and organize web-content. As users are free to create any tag to describe any resource, it leads to what is referred to as the vocabulary problem. Because users may use different words to describe the same document or extract different topics from the same document based on their own background knowledge, the lack of a top-down mediation may lead to an increase in the use of incoherent tags to represent the information resources in the system. In other words, the inherent ""unstructuredness"" of social tags may hinder their potential as navigational cues for searchers because the diversities of users and motivation may lead to diminishing tag-topic relations as the system grows. However, a number of studies have shown that structures do emerge at the semantic level -- indicating that there are cohesive forces that are driving the emergent structures in a social tagging system.