Name
Abstract | ||
|---|---|---|
The visualization and analysis of dynamic social networks are challenging problems, demanding the simultaneous consideration of relational and temporal aspects. In order to follow the evolution of a network over time, we need to detect not only which nodes and which links change and when these changes occur, but also the impact they have on their neighbourhood and on the overall relational structure. Aiming to enhance the perception of structural changes at both the micro and the macro level, we introduce the change centrality metric. This novel metric, as well as a set of further metrics we derive from it, enable the pair wise comparison of subsequent states of an evolving network in a discrete-time domain. Demonstrating their exploitation to enrich visualizations, we show how these change metrics support the visual analysis of network dynamics. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ASONAM.2012.39 | Advances in Social Networks Analysis and Mining |
Keywords | Field | DocType |
change centrality,visual analysis,discrete-time domain,change metrics,structural change,change centrality metric,dynamic networks,overall relational structure,novel metric,macro level,network dynamic,dynamic social network,data analysis,social sciences,data visualisation | Network science,Data mining,Data visualization,Social network,Network dynamics,Visualization,Computer science,Visual analytics,Centrality,Artificial intelligence,Macro,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-4673-2497-7 | 7 | 0.49 |
References | Authors | |
16 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paolo Federico | 1 | 49 | 3.51 |
| Jürgen Pfeffer | 2 | 346 | 26.57 |
| wolfgang aigner | 3 | 842 | 51.72 |
| Silvia Miksch | 4 | 2212 | 174.85 |
| Lukas Zenk | 5 | 29 | 2.03 |