Models of collaborative tagging

Collaborative tagging, also known as social tagging or folksonomy, allows users to apply public tags to online items, typically to make those items easier for themselves or others to find later. It has been argued that these 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 users create to represent topics extracted from online documents, the interpretation of these tags should allow other users to predict the 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 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 any 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 lack of structure inherent in social tags may hinder their potential as navigational cues for searchers because the diversities of users and their 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 driving the emergent structures in a social tagging system.