![Page 1: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/1.jpg)
Exploring Social Networks with Matrix-Based Representations
Nathalie Henry* &
Jean-Daniel Fekete
IN|SITU / AVIZ Lab.INRIA / Laboratoire de Recherche en Informatique
*Université de [email protected], [email protected]
![Page 2: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/2.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
2
The problem
Using Node-Link diagrams to visualize:
• Tree-like• Small-world• Almost-complete
http://www.infovis-wiki.net/index.php/Social_Network_Generation
![Page 3: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/3.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
3
What social scientistsare looking for
• What are the communities?
• How actors are linkedwithin the community?
• How communities are linked?
• Who is central?
![Page 4: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/4.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
4
Proposing a readablerepresentation for dense graphs
• What are the communities?
• How actors are linkedwithin the community?
• How communities are linked?
• Who is central?
[Ghoniem et al. 05]
?
![Page 5: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/5.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
5
Matrix Visualization A
C
B D
A B C DAB
C
D
X
X
XXX
?
?
![Page 6: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/6.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
6
Matrix vs NodeLink
• Usable without reordering• No node overlapping
No edge crossingReadable for dense graphs
• Fast navigation• Fast manipulation
Usable interactively• More readable for some tasks
• Less intuitive• Use more space• Weak for path following tasks
• Intuitive• Compact• More readable for path following• More effective for small graphs• More effective for sparse graphs
• Useless without layout• Node overlapping
Edge crossingNot readable for dense graphs
• Manipulation requires layoutcomputation
+
-
![Page 7: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/7.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
7
Explore
Communicate
![Page 8: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/8.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
8
Participatory Design• What Social Science researchers
– Use? (representations, software)– Analyze? (datasets)– Do? (tasks, exploration process)– Want? (aspiration)
Observation
Brainstorming
Prototyping
Evaluation
http://insitu.lri.fr/~nhenry/Workshop.html
![Page 9: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/9.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
9
Needs expressedfor an exploratory analysis system
• Multiple representations• Interaction… instead of parameter tuning
[Henry&Fekete06]• Overviews• Connected Components Representation• Global Information on Graph and Social Networks
– Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5 lessconnected, centrality measures.
• Multiples représentations: Nœuds-liens (moreno30’s), Matrices (forsyth40’s)• Layout for node-link, ordering for matrices• Interactions directly on the network
– Filtering, Clustering (multiples), Aggregation• Compare, Confront, Annotate
![Page 10: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/10.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
10
Possible solutions1. Improve one representation
2. Combine both representations
3. Augment one representation
4. Find hybrid representations
Find other representations
Better layout/ordering
MatrixExplorer
MatLink
NodeTrix
TreePlus, Links over Treemap, NetLens, Semantic Substrates…
![Page 11: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/11.jpg)
1. Improve one representation
Layout (Node-Link)Order (Matrix)
![Page 12: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/12.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
12
Reorder to understand• Why?
• Survey in progress– Interactive techniques– Algorithms for reordering tables– Algorithms for graphs linearization
Bertin, 1967
v1 v2 v3 v4 v5 v6 v7 v8
![Page 13: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/13.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
13
Identifying Visual Patterns
![Page 14: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/14.jpg)
2. Combine both representations
MatrixExplorer
![Page 15: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/15.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
15
MatrixExplorer [Henry&Fekete06]
• Matrices to explore• Node-Link diagrams to present findings
![Page 16: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/16.jpg)
3. Augment one representation
MatLink
![Page 17: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/17.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
17
MatLink[Henry&Fekete07]
• Solving the path-related tasks problemfor matrices
• Augmenting matrices with interactive links
![Page 18: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/18.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
18
MatLink: significantly improvingmatrices
• Controlled experiment– 3 vis. x 6 datasets x 5 tasks
Matrix , Node-Link, MatLink
Data: From almost-treesTo complete-graphs Including small-world networks
Tasks: 1. CommonNeighbour, 2. ShortestPath, 3. MostConnected, 4. ArticulationPoint, 5. LargestClique
![Page 19: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/19.jpg)
4. Find a hybrid representation
NodeTrix
![Page 20: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/20.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
20
NodeTrix[Henry et al.07]
• Designed for small-world networks– Globally sparse– Locally dense
• Visualizing dense sub-graphs as matrices
• Interact to create, editand remove the matrices
![Page 21: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/21.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
21
NodeTrix
VIDEO : http://insitu.lri.fr/~nhenry/nodetrix/nodetr
ix.mov
![Page 22: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/22.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
22
NodeTrix: the NetVis Nirvana?Can you see every node?Can you count each node’s degree?Can follow every link from its source to
its destination?Can you idenfity clusters and outliers?
• Node Labels• Link Labels (excentric labels?!)• … even clusters labels• Node Attributes• Link Attributes• … even clusters attributes• Directed Graph (links width?!)… But… It’s gonna be crowded here !
![Page 23: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/23.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
23
Visual Patterns
Cross Pattern Block Pattern Mixte Pattern
![Page 24: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/24.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
24
Visual Patterns
Infovis Coauthorship (133 actors)
![Page 25: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/25.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
25
Using Interaction for Story-telling
![Page 26: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/26.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
26
Future Directions
• Scaling up to very large network...…the problem of reordering
• Provide usable tools to sociologists...…the problem of bug fixing
• Navigating and aggregating [Zame]
• Towards collaborative exploration• From exploration to story telling
![Page 27: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/27.jpg)
La Fin
![Page 28: Exploring Social Networks with Matrix-Based Representations · 2007. 6. 3. · – Data, Attributes, SNA: actors, relationship, degree distribution, diameter, 5 most connected, 5](https://reader035.vdocuments.us/reader035/viewer/2022081410/60a4138c91e10948ca4df107/html5/thumbnails/28.jpg)
June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations
28
References• N. Henry, J-D. Fekete, M. Mcguffin. NodeTrix: Hybrid Representation for
Analyzing Social Networks, Research Report 6183, INRIA, 2007. https://hal.inria.fr/inria-00144496
• N. Henry and J-D. Fekete. MatLink: Enhanced Matrix Visualization for AnalyzingSocial Networks. In Processding of the eleventh IFIP TC13 International Conference on Human-Computer Interaction (Interact 2007), September 2007. Springer Verlag. 14 pages, to be published.
• N. Henry and J-D. Fekete. MatrixExplorer: a Dual-Representation System to Explore Social Networks. IEEE Transactions on Visualization and Computer Graphics (Proceedings Visualization / Information Visualization 2006), 12(5):677-684, September-October 2006.
• M. Ghoniem, J-D. Fekete and P. Castagliola. Readability of Graphs Using Node-Link and Matrix-Based Representations: Controlled Experiment and Statistical Analysis. Information Visualization Journal, 4(2):114–135, 2005.