Community Fabric: Visualizing communities and structure in dynamic networks

Autor: David Anderson, Seung-Hwan Lim, Evan Ezell, Robert N. Stewart
Rok vydání: 2021
Předmět:
Zdroj: Information Visualization. 21:130-142
ISSN: 1473-8724
1473-8716
DOI: 10.1177/14738716211056036
Popis: We present Community Fabric, a novel visualization technique for simultaneously visualizing communities and structure within dynamic networks. In dynamic networks, the structure of the network is continuously evolving throughout time and these underlying topological shifts tend to lead to communal changes. Community Fabric helps the viewer more easily interpret and understand the interplay of structural change and community evolution in dynamic graphs. To achieve this, we take a new approach, hybridizing two popular network and community visualizations. Community Fabric combines the likes of the Biofabric static network visualization method with traditional community alluvial flow diagrams to visualize communities in a dynamic network while also displaying the underlying network structure. Our approach improves upon existing state-of-the-art techniques in several key areas. We describe the methodologies of Community Fabric, implement the visualization using modern web-based tools, and apply our approach to three example data sets.
Databáze: OpenAIRE