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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
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Control Menu
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Dynamic Queries
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Selection History
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Transient Buttons
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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”
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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
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Thank you
www.aviz.fr/graphdice19