introduction: network visualization workshop · 2007. 6. 4. · introduction: network visualization...
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![Page 1: Introduction: Network Visualization Workshop · 2007. 6. 4. · Introduction: Network Visualization Workshop Ben Shneiderman ben@cs.umd.edu Human-Computer Interaction Lab & Dept of](https://reader033.vdocuments.mx/reader033/viewer/2022060909/60a4138b91e10948ca4df105/html5/thumbnails/1.jpg)
Introduction:Network Visualization Workshop
Ben Shneiderman [email protected]
Human-Computer Interaction Lab &Dept of Computer Science
University of MarylandCollege Park, MD 20742
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State-of-the-art network visualization
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Node Placement Methods
• Node-link diagrams• Force-directed layout• Geographical map• Circular layout• Temporal layout• Clustering• Layouts based on node
attributes (later)• Matrix-based• Tabular textual
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Node Placement Methods
• Node-link diagrams• Force-directed layout• Geographical map• Circular layout• Temporal layout• Clustering• Layouts based on node
attributes (later)• Matrix-based• Tabular textual
![Page 6: Introduction: Network Visualization Workshop · 2007. 6. 4. · Introduction: Network Visualization Workshop Ben Shneiderman ben@cs.umd.edu Human-Computer Interaction Lab & Dept of](https://reader033.vdocuments.mx/reader033/viewer/2022060909/60a4138b91e10948ca4df105/html5/thumbnails/6.jpg)
Node Placement Methods
• Node-link diagrams• Force-directed layout• Geographical map• Circular layout• Temporal layout• Clustering• Layouts based on node
attributes (later)• Matrix-based• Tabular textual
![Page 7: Introduction: Network Visualization Workshop · 2007. 6. 4. · Introduction: Network Visualization Workshop Ben Shneiderman ben@cs.umd.edu Human-Computer Interaction Lab & Dept of](https://reader033.vdocuments.mx/reader033/viewer/2022060909/60a4138b91e10948ca4df105/html5/thumbnails/7.jpg)
Node Placement Methods
• Node-link diagrams• Force-directed layout• Geographical map• Circular layout• Temporal layout• Clustering• Layouts based on node
attributes (later)• Matrix-based• Tabular textual
![Page 8: Introduction: Network Visualization Workshop · 2007. 6. 4. · Introduction: Network Visualization Workshop Ben Shneiderman ben@cs.umd.edu Human-Computer Interaction Lab & Dept of](https://reader033.vdocuments.mx/reader033/viewer/2022060909/60a4138b91e10948ca4df105/html5/thumbnails/8.jpg)
Node Placement Methods
• Node-link diagrams• Force-directed layout• Geographical map• Circular layout• Temporal layout• Clustering• Layouts based on node
attributes (later)• Matrix-based• Tabular textual
![Page 9: Introduction: Network Visualization Workshop · 2007. 6. 4. · Introduction: Network Visualization Workshop Ben Shneiderman ben@cs.umd.edu Human-Computer Interaction Lab & Dept of](https://reader033.vdocuments.mx/reader033/viewer/2022060909/60a4138b91e10948ca4df105/html5/thumbnails/9.jpg)
Node Placement Methods
• Node-link diagrams• Force-directed layout• Geographical map• Circular layout• Temporal layout• Clustering• Layouts based on node
attributes (later)• Matrix-based• Tabular textual
![Page 10: Introduction: Network Visualization Workshop · 2007. 6. 4. · Introduction: Network Visualization Workshop Ben Shneiderman ben@cs.umd.edu Human-Computer Interaction Lab & Dept of](https://reader033.vdocuments.mx/reader033/viewer/2022060909/60a4138b91e10948ca4df105/html5/thumbnails/10.jpg)
Node Placement Methods
• Node-link diagrams• Force-directed layout• Geographical map• Circular layout• Temporal layout• Clustering• Layouts based on node
attributes (later)• Matrix-based• Tabular textual
![Page 11: Introduction: Network Visualization Workshop · 2007. 6. 4. · Introduction: Network Visualization Workshop Ben Shneiderman ben@cs.umd.edu Human-Computer Interaction Lab & Dept of](https://reader033.vdocuments.mx/reader033/viewer/2022060909/60a4138b91e10948ca4df105/html5/thumbnails/11.jpg)
Node Placement Methods
• Node-link diagrams• Force-directed layout• Geographical map• Circular layout• Temporal layout• Clustering• Layouts based on node
attributes (later)• Matrix-based• Tabular textual
![Page 12: Introduction: Network Visualization Workshop · 2007. 6. 4. · Introduction: Network Visualization Workshop Ben Shneiderman ben@cs.umd.edu Human-Computer Interaction Lab & Dept of](https://reader033.vdocuments.mx/reader033/viewer/2022060909/60a4138b91e10948ca4df105/html5/thumbnails/12.jpg)
NetViz Nirvana
?? ?? ??
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NetViz Nirvana
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NetViz Nirvana
1) Every node is visible
2) For every node you can count its degree
3) For every link you can follow it from source to destination
4) Clusters and outliers are identifiable
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NetViz Nirvana
How to attain NetViz Nirvana?
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Challenges of Network Visualization
• C1) Basic networks: nodes and links
• C2) Node labels• e.g. article title, book author, animal name
• C3) Link labels• e.g. Strength of connection, type of link
• C4) Directed networks
• C5) Node attributes• Categorical, Ordinal, Numerical
• C6) Link attributes• Categorical, Ordinal, Numerical
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Tasks of Network Visualization
• T1) count number of nodes and links• T2) for every node, count degree• T3) for every node, find the nodes that are distance 1, 2, 3 …away• T4) for every node, find betweenness centrality• T5) for every node, find structural prestige• T6) find diameter of the network• T7) identify strongly connected or compact clusters• T8) for a given pair of nodes, find shortest path between them
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Tasks of Network Visualization
• T9) for every node/link, read the label• T10) find all nodes/links with a given label/attribute
• T11) find links between nodes with different attribute values (e.g. journal articles that cite conference articles or
mammals that eat fish)• T12) find the proportion of links from a node that go to each category for
every node(e.g. for a given article, what fraction of the citations go to each category of articles or for a given animal what fraction of its diet comes from eating each category of animal)
• T13) for a pair of nodes, find paths with the lowest cost• T14) find links with connection strength greater than 0.5
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Tasks (TreePlus, TVCG 2006)
Find: Find a person that is already displayed. The person might be off screen (Do not use search).
Adjacency: Among all those who communicate witha specific person, count those with a givencharacteristic.
Accessibility: Count people with a given characteristic within two links (distance 2) of a given person.
Common Connection: Find all people who have been in direct email communication with two given people.
Connectivity: Find who has the most email
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