Be the Data: Social Meetings with Visual Analytics
Xin Chen, Jessica Zeitz Self, Maoyuan Sun, Leanna L. House, Chris North
Social meetings provide important venues for people to get connected. However, it is challenging to explore reasons of social gathering, identify its key impact factors, and further use it to support people's social activities. In this paper, we present an embodied visual analytics system, which highlights analyzing and displaying social-cluster related information in real time. In the system, each user represents a data point in a high-dimensional dataset, and their positions reflect a 2D projection of the dataset, by using weighted multidimensional scaling. As users move and socialize with others, the 2D projection is dynamically updated, and relevant information of user clusters is visually analyzed and presented through dimension reduction techniques. We conducted informal social meetings with participants who were a mix of strangers and friends. We found that there are 3 stages of social gathering, corresponding to different interactions in the system. Our results also suggest that the system assists social gathering with dimension reduction visualizations.
Professor of Computer Science
Associate Professor of Statistics
- Date of publication:
- October 31, 2016
- International Conference on Collaboration Technologies and Systems (CTS)