Tagnet: Supporting the Exploration of Knowledge Structures of Social Tags with Multiscale Network Visualization

Social tags reflect personal and shared vocabulary, and provide opportunities for people to organize and search information. However, tags are usually not structured. To find relevant tags and associated documents, people often need to invest significant amount of cognitive resources to make sense of the relationships among tags. To facilitate the sensemaking of social tags and exploration of knowledge structure of them, we propose an approach of tag networks, TagNet, in which tags are linked by their corresponding documents and a multiscale tag hierarchy is derived from network clustering and aggregation techniques. We also present TagNetLens, an interactive tool that allows users to explore a tag network and its tag hierarchy. We report a case study of TagNet and TagNetLens based on social tags and documents from CiteULike. The results indicate that our TagNet approach provides users with knowledge structures that are isomorphic to cognitive structures of concepts in people’s minds, and TagNetLens supports exploring the space of social tags and facilitates the understanding of the knowledge structure in social tags.