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GraphDiceA System for Exploring

Multivariate Social Networks

Anastasia Bezeriano

s

Anastasia Bezeriano

s

Fanny Chevali

er

Fanny Chevali

er

Pierre Dragicev

ic- The Good -

Pierre Dragicev

ic- The Good -

Jean-Daniel Fekete

- The Ugly -

Jean-Daniel Fekete

- The Ugly -

NiklasElmqvist- The Bad -

NiklasElmqvist- The Bad -

Dagstuhl edition

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Social Network AnalysisIntrinsic attributes

• # publications

• # citations• year• authoring position• …

Computed attributes

• degree• betweeness centrality• clustering coefficient• …

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Social Network AnalysisIntrinsic attributes

• # publications

• # citations• year• authoring position• …

Computed attributes

• degree• betweeness centrality• clustering coefficient• …

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Motivation

Target Users: Social network analysts

Design Rationale:

Consistent and simple representation and interaction

Edge and node attribute visualization

Link between tabular data and vis

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GraphDice Interface

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GraphDice Interface

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GraphDice Interface

Control Menu

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Dynamic Queries

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Selection History

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Transient Buttons

Jitter

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Zoom

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Zoom

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User Feedback

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“have all combinations of attributes immediately

available to quickly explore hypothesis”

“animation helps to compare attributes”

“tables give security and confidence that I am looking at the correct

data”

“Easy to use, but it took a bit to

understand edge attributes”

“can be used to communicat

e findings”

Directed Networks

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Data Tables

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Conclusion

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Unified representation of- topology-based layout / cartographic positions

- intrinsic attributes- computed measures-edge attributes

Consistent and visible interaction

History management

Coordinated visual and tabular representations

Thank you

www.aviz.fr/graphdice19