exploring social networks with matrix-based representations · 2007. 6. 3. · – data,...

Exploring Social Networks with Matrix-Based Representations

Nathalie Henry* &

Jean-Daniel Fekete

IN|SITU / AVIZ Lab.INRIA / Laboratoire de Recherche en Informatique

*Université de SydneyNathalie.Henry@lri.fr, Jean-Daniel.Fekete@inria.fr

June 3, 2007 Nathalie HenryExploring Social Networks with Matrix-Based Representations

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The problem

Using Node-Link diagrams to visualize:

• Tree-like• Small-world• Almost-complete

http://www.infovis-wiki.net/index.php/Social_Network_Generation

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What social scientistsare looking for

• What are the communities?

• How actors are linkedwithin the community?

• How communities are linked?

• Who is central?

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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]

?

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Matrix Visualization A

C

B D

A B C DAB

C

D

X

X

XXX

?

?

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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

+

-

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Explore

Communicate

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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

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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

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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…

1. Improve one representation

Layout (Node-Link)Order (Matrix)

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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

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Identifying Visual Patterns

2. Combine both representations

MatrixExplorer

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MatrixExplorer [Henry&Fekete06]

• Matrices to explore• Node-Link diagrams to present findings

3. Augment one representation

MatLink

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MatLink[Henry&Fekete07]

• Solving the path-related tasks problemfor matrices

• Augmenting matrices with interactive links

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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

4. Find a hybrid representation

NodeTrix

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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

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NodeTrix

VIDEO : http://insitu.lri.fr/~nhenry/nodetrix/nodetr

ix.mov

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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 !

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Visual Patterns

Cross Pattern Block Pattern Mixte Pattern

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Visual Patterns

Infovis Coauthorship (133 actors)

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Using Interaction for Story-telling

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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

La Fin

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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.