TopicPanorama: a Full Picture of Relevant Topics


Shixia Liu1    Xiting Wang1,2     Jianfei Chen2     Jun Zhu2     Baining Guo1,2    
1Microsoft Research Asia             2Tsinghua University

Teaser Image
Teaser Image

TopicPanorama visualization: (a) a full picture of topics related to Google, Microsoft, and Yahoo; (b) government related topics; (c) NSA Prism spying scandal shared by Google and Yahoo; (d) NSA Prism spying scandal shared by the three companies. Notations A-I represent different groups of topics and J-N represent different topics.


We present a visual analytics approach to developing a full picture of relevant topics discussed in multiple sources such as news, blogs, or micro-blogs. The full picture consists of a number of common topics among multiple sources as well as distinctive topics. The key idea behind our approach is to jointly match the topics extracted from each source together in order to interactively and effectively analyze common and distinctive topics. We start by modeling each textual corpus as a topic graph. These graphs are then matched together with a consistent graph matching method. Next, we develop an LOD-based visualization for better understanding and analysis of the matched graph. The major feature of this visualization is that it combines a radially stacked tree visualization with a density-based graph visualization to facilitate the examination of the matched topic graph from multiple perspectives. To compensate for the deficiency of the graph matching algorithm and meet different users’ needs, we allow users to interactively modify the graph matching result. We have applied our approach to various data including news, tweets, and blog data. Qualitative evaluation and a real-world case study with domain experts demonstrate the promise of our approach, especially in support of analyzing a topic-graph-based full picture at different levels of detail.

Paper and Video

Paper: Download

Video: Download English Video    Download Chinese Video

Source Code and Packages

Input Topic Graphs: Download Scalable CTM (0.36 MB)    GitHub

TopicPanorama Package: coming soon...