A time-based visualization for web user classification in social networks

This paper presents a new visual analytics framework for analyzing health-related physical activity data. Existing techniques mostly rely on node-links visualizations to represent the usage patterns as social networks. This work takes a different approach that provides interactive scatter-plot visualizations on classified and time-based data. By providing a flexible visualization that can provide different angles on the multidimensional and classified data, the analyst could have better understanding and insight on web user behavior compared to the traditional social network methods. The effectiveness of our method has been demonstrated with a case study on an online portal system for tracking passive physical activity, called Walk 2.0.