Visual Analysis of Complex Temporal Networks Supported by Analytic Provenance
Yuhan Guo - Peking University, Beijing, China. Peking University, Beijing, China
Yuchu Luo - Peking University, Beijing, China. Peking University, Beijing, China
Xinyue Chen - Peking University, Beijing, China. Peking University, Beijing, China
Hanning Shao - Peking University, Beijing, China. Peking University, Beijing, China
Xiaoru Yuan - Peking University, Beijing, China. Peking University, Beijing, China
Kai Xu - University of Nottingham, Nottingham, United Kingdom. University of Nottingham, Nottingham, United Kingdom
Room: Bayshore II
2024-10-13T12:30:00ZGMT-0600Change your timezone on the schedule page
2024-10-13T12:30:00Z
Full Video
Abstract
We present an interactive visual analysis tool to explore large dynamic graphs. Our system provides users with multiple perspectives to analyze the network. The graph view presents the node-link structure and offers various layout options. To complement, a temporal view shows both the overall temporal distribution and detailed event timelines. The system also supports flexible filtering to reduce the graph size and identify interesting entities. One bonus feature of our system is the provenance map, which visualizes the automatically captured user interactions and allows users to record their findings. The provenance map is helpful for organizing the exploration process and synthesizing analysis results.