Visualizing social interaction data has been of booming interest as the recent availability of social traces, ranging from the conversations left in social media to groups' collaborations archived in publications. The key challenges of visualizing social interaction data including the difficulties of (1) understanding the general structure of social interactions and (2) representing the data in the context of different user activities for revealing different behavior patterns. In this paper, we present, Episogram, for visualizing social interaction data. Our design is based on an anatomy of social interaction process in which the actors and objects involved can be formally represented as a time-varying tripartite network. In Episogram, we display and aggregate such tripartite networks along multiple temporal dimensions, from different actors' egocentric perspectives. We show the effectiveness of the proposed technique via case studies and user studies. The results indicate that our design provides non-trivial insights from social interaction data.
- Nan Cao, Yu-Ru Lin, Fan Du, and Dashun Wang, Episogram: Visual Summarization of Egocentric Social Interactions, IEEE Computer Graphics and Applications (CG&A) (paper)