Spatially and temporally relevant text data generated on the Internet by users worldwide is of great value for investigating and understanding emerging trends of user interests and how they may evolve over time and space. However, exploring the spatiotemporal text data and characterizing the evolution of topics over time and space are challenging due to the complexity of such data and associated activities. This paper proposes a new approach to exploring the spatiotemporal text data with visual filters. We introduce a notion of topic trajectory to depict the spatiotemporal evolution of topics. Multiple coordinated visualizations provided in our visualization system enable users to explore topic trajectories and develop their contextual awareness in terms of how information flows across different regions. We demonstrate the use of our system with an analysis of a dataset contributed by users of widely used science mapping software CiteSpace.
['Jiangen He', 'Chaomei Chen']
Spatiotemporal Analytics of Topic Trajectory