NetVisia: Heat Map & Matrix Visualization of Dynamic Social Network Statistics & Content
| Title | NetVisia: Heat Map & Matrix Visualization of Dynamic Social Network Statistics & Content |
| Publication Type | Conference Papers |
| Year of Publication | 2011 |
| Authors | Gove R, Gramsky N, Kirby R, Sefer E, Sopan A, Dunne C, Shneiderman B, Taieb-Maimon M |
| Conference Name | Privacy, Security, Risk and Trust (PASSAT), 2011 IEEE Third International Conference on and 2011 IEEE Third International Confernece on Social Computing (SocialCom) |
| Date Published | 2011/10/09/11 |
| Publisher | IEEE |
| ISBN Number | 978-1-4577-1931-8 |
| Keywords | business intelligence concept, business intelligence entity, competitive intelligence, data visualisation, dynamic networks, dynamic social network, heat map, Heating, Image color analysis, Information Visualization, Layout, matrix visualization, measurement, NetVisia system, network evolution, network visualization, node-link diagrams, outlier node, social network content, Social network services, social network statistics, social networking (online), social networks, static network visualization, time period, topological similarity, Training, usability, user evaluation, User interfaces |
| Abstract | Visualizations of static networks in the form of node-link diagrams have evolved rapidly, though researchers are still grappling with how best to show evolution of nodes over time in these diagrams. This paper introduces NetVisia, a social network visualization system designed to support users in exploring temporal evolution in networks by using heat maps to display node attribute changes over time. NetVisia's novel contributions to network visualizations are to (1) cluster nodes in the heat map by similar metric values instead of by topological similarity, and (2) align nodes in the heat map by events. We compare NetVisia to existing systems and describe a formative user evaluation of a NetVisia prototype with four participants that emphasized the need for tool tips and coordinated views. Despite the presence of some usability issues, in 30-40 minutes the user evaluation participants discovered new insights about the data set which had not been discovered using other systems. We discuss implemented improvements to NetVisia, and analyze a co-occurrence network of 228 business intelligence concepts and entities. This analysis confirms the utility of a clustered heat map to discover outlier nodes and time periods. |
| DOI | 10.1109/PASSAT/SocialCom.2011.216 |