Content clouds: classifying content in Web 2.0
Kenneth Cosh, Robert Burns, Toby Daniel · Library Review · 2008
Purpose With increasing amounts of user generated content being produced electronically in the form of wikis, blogs, forums etc. the purpose of this paper is to investigate a new approach to classifying ad hoc content. Design/methodology/approach The approach applies natural language processing (NLP) tools to automatically extract the content of some text, visualizing the results in a content cloud. Findings Content clouds share the visual simplicity of a tag cloud, but display the details of an article at a different level of abstraction, providing a complimentary classification. Research limitations/implications Provides the general approach to creating a content cloud. In the future, the process can be refined and enhanced by further evaluation of results. Further work is also required to better identify closely related articles. Practical implications Being able to automatically classify the content generated by web users will enable others to find more appropriate content. Originality/value The approach is original. Other researchers have produced a cloud, simply by using skiplists to filter unwanted words, this paper's approach improves this by applying appropriate NLP techniques.