Tag Net Lens: Multiscale Visualization of Knowledge Structures in Social Tags
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 help 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 are derived with 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 can provide users with knowledge structures that are similar to cognitive structures of concepts in peoples minds, and TagNetLens can help people to better explore the space of social tags and may have potentials to facilitate the understanding of the knowledge structure in social tags.
social tags network visualization multiscale tagnetlens
Liang Gou Shaoke Zhang Jing Wang Xiaolong (Luke) Zhang
College of Info.Sci.& Tech.The Penn State Univ.University Park, PA, USA
国际会议
The 3rd Visual Information Communication-International Symposium(第三届视觉信息通信国际研讨会VINCI 2010)
北京
英文
97-105
2010-09-28（万方平台首次上网日期，不代表论文的发表时间）