Some temporal visualizations from different networks, using techniques such as Recurrent Neighbors (RN), Temporal Activity Map (TAM) and Community-based Node Ordering (CNO).
All images were generated in the DyNetVis System.
L. Isella, J. Stehl e, A. Barrat, C. Cattuto, J.-F. Pinton, W. Van den Broeck, What's in a crowd? Analysis of face-to-face behavioral networks. J. Theor. Biol. 271 166-180 (2011).
2. MSV with Appearance ordering and colored nodes and edges:
3. MSV with Recurrent Neighbors ordering and colored nodes and edges:
4. MSV with Community-based node ordering (CNO) and colored nodes and edges, only showing the Intra edges:
5. MSV with Community-based node ordering (CNO) and different color for the nodes and edges, using the Temporal Activity Map (TAM):
6. TAM with black background, highlighting the nodes activity:
7. Coordination between layouts, selecting some nodes from a node-link diagram perspective and the respective nodes and links in the MSV:
L. Isella, M. Romano, A. Barrat, C. Cattuto, V. Colizza, W. Van den Broeck, F. Gesualdo, E. Pandol , L. Rav a, C. Rizzo, A.E. Tozzi, Close encounters in a pediatric ward: measuring face-to-face proximity and mixing patterns with wearable sensors. PLoS ONE 6(2): e17144 (2011).
MSV layout, with CNO (Infomap, RN, RN) in level 1, only showing Intra edges:
MSV layout, with CNO (Louvain, RN, RN) in level 1, only showing Intra edges:
TAM layout, with CNO (Louvain, RN, RN):
Pereira, FS, Amo, Sd, Gama, J. Detecting Events in Evolving Social Networks through Node Centrality Analysis. In: Workshop on Largescale Learning from Data Streams in Evolving Environments of ECML PKDD. p. 83–93. (2016).
This is a scalability solution to very large networks. See more about CNO.
Museum and Hospital networks can be found at: http://www.sociopatterns.org/