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Transcript of Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman,...
![Page 1: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/1.jpg)
Lecture 12:
Network Visualization
Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris
![Page 2: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/2.jpg)
Outline
What is a network?
How do you analyze networks today?
What are the challenges?
How to integrate with other methods?
![Page 3: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/3.jpg)
What are networks?
Networks are collections of points joined by lines.
“Network” ≡ “Graph”
points lines
vertices edges, arcs math
nodes links computer science
sites bonds physics
actors ties, relations sociology
node
edge
3
![Page 4: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/4.jpg)
Network elements: edges
Directed (also called arcs) A -> B
A likes B, A gave a gift to B, A is B’s child
Undirected A <-> B or A – B
A and B like each other A and B are siblings A and B are co-authors
Edge attributes weight (e.g. frequency of communication) ranking (best friend, second best friend…) type (friend, relative, co-worker) properties depending on the structure of the rest of the graph:
e.g. betweenness
4
![Page 5: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/5.jpg)
Planar graphs
A graph is planar if it can be drawn on a plane without any edges crossing
![Page 6: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/6.jpg)
#s of planar graphs of different sizes
1:1
2:2
3:4
4:11
Every planar graph
has a straight line
embedding
![Page 7: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/7.jpg)
Trees
Trees are undirected graphs that contain no cycles
![Page 8: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/8.jpg)
Cliques and complete graphs
Kn is the complete graph (clique) with K vertices each vertex is connected to every other vertex there are n*(n-1)/2 undirected edges
K5 K8K3
![Page 9: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/9.jpg)
Outline
What is a network?
How do you analyze networks today?
What are the challenges?
How to integrate with other methods?
![Page 10: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/10.jpg)
Why Visualization?
Use the eye for pattern recognition; people are good at scanning recognizing remembering images
Graphical elements facilitate comparisons via length shape orientation texture Animation shows changes across time Color helps make distinctions Aesthetics make the process appealing
http://amaznode.fladdict.net/http://www.touchgraph.com/TGAmazonBrowser.html
![Page 11: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/11.jpg)
Graph Drawing Aesthetics
Minimize edge crossings Draw links as straight as possible Maximize minimum angle Maximize symmetry Minimize longest link Minimize drawing area Centralize high-degree nodes Distribute nodes evenly Maximize convexity (of polygons) Keep multi-link paths as straight as
possible …
Source: Davidson & Harel
![Page 12: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/12.jpg)
Node Placement Methods
Node-link diagrams Force-directed
Geographical maps
Circular layouts One or multiple concentric
Temporal layouts
Clustering
Semantic Substrates
![Page 13: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/13.jpg)
Force-directed Layout
Also known as: Spring Spreads nodes
Minimizes chance of node occlusion
![Page 14: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/14.jpg)
Geographical Map
Familiar location of nodes
![Page 15: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/15.jpg)
Circular Layouts (1 circle)
Ex: Schemaball Database schema Tables connected via foreign keys
![Page 16: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/16.jpg)
Circular Layouts (concentric)
Radial Tree Viewer
![Page 17: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/17.jpg)
Circular (concentric) & Temporal
Hudson Bay Food Web
![Page 18: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/18.jpg)
Temporal Layout
![Page 19: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/19.jpg)
Clustering
![Page 20: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/20.jpg)
Hierarchical Clustering
![Page 21: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/21.jpg)
Semantic Substrates
Group nodes into regions According to an
attribute Categorical, ordinal, or
binned numerical
In each region: Place nodes according
to other attribute(s)
![Page 22: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/22.jpg)
Force-directed
>30%
Familiar Layout
~30%
Circular Layout
~15%
Node layout strategy
First 100 in visualcomplexity.com
Statistics on Strategies
![Page 23: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/23.jpg)
Outline
What is a network?
How do you analyze networks today?
What are the challenges?
How to integrate with other methods?
http://graphexploration.cond.org/index.html
![Page 24: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/24.jpg)
Challenges of Network Visualization
Basic networks: nodes and links Node labels
e.g. article title, book author, animal name
Link labels e.g. Strength of connection, type of link
Directed networks Node attributes
Categorical (e.g. mammal/reptile/bird/fish/insect) Ordinal (e.g. small/medium/large) Numerical (e.g. age/weight)
Link Attributes Categorical (e.g. car/train/boat/plane) Ordinal (e.g. weak/normal/strong) Numerical (e.g. probability/length/time to traverse/strength)
![Page 25: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/25.jpg)
C1) Basic Networks (nodes & links)
Power Law Graph 5000 nodes Uniformly distributed
![Page 26: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/26.jpg)
C1) Basic Networks (continued)
Social friendship network 3 degrees from Heer 47,471 people 432,430 relations
![Page 27: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/27.jpg)
C2) Node Labels
Adding labels Nodes overlap with other nodes Nodes overlap with links
250 nodes
![Page 28: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/28.jpg)
C3) Link Labels
Challenges: Length Space Belongingness Distinction from other labels & other types of labels
![Page 29: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/29.jpg)
C4) Directed Networks
Direction arrows labels Thickness color
SeeNet, Becker et al.
![Page 30: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/30.jpg)
C5 & C6) Node & Link Attributes
Types: Categorical (e.g. mammal/reptile/bird/fish/insect) Ordinal (e.g. small/medium/large) Numerical (e.g. age/weight)
Value of node attribute indicated by node shape Value of link attribute indicated by a letter
![Page 31: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/31.jpg)
C1
~12%C4
~10%
C2
~66%
Challenges
First 100 in visualcomplexity.com
Statistics on Challenges
C5
~10%
C6
~2%
C1) Basic networks
C2) Node labels
C3) Link labels
C4) Directed networks
C5) Node attributes
C6) Link attributes
![Page 32: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/32.jpg)
Outline
What is a network?
How do you analyze networks today?
What are the challenges?
How to integrate with other methods?
![Page 33: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/33.jpg)
Integrating with other methods
Social network analysis is inherently complex Analysts must understand every node's attributes as well
as relationships between nodes. The visualizations are helpful but too messy and
incomprehensible when data is huge.
Statistics are used to detect important individuals, relationships, and clusters,
Integrate this with
Network visualization in which users can easily and dynamically filter nodes and edges.
“Integrating Statistics and Visualization” by Adam Perer, Ben Shneiderman
![Page 34: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/34.jpg)
Overview the network both statistically and visually
Present just sense of the structure, clusters and depth of a network Present some statistics to provide a way to both confirm and quantify the visual findings
![Page 35: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/35.jpg)
Issues:
• Panning and zooming naively is not enough
• Zooming into sections of the network force users to lose the global structure.
Solution
• Allow user-controlled
Statistics to drive the navigation
Filter and Zoom to gain deeper insights
![Page 36: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/36.jpg)
Users can select a node to see all of its attributes.
What do we achieve?
– “the ability to see each node and follow its edges to all other nodes.
Details on Demand
![Page 37: Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.](https://reader035.fdocuments.in/reader035/viewer/2022062804/56649e835503460f94b84953/html5/thumbnails/37.jpg)
Outline
What is a network?
How do you analyze networks today?
What are the challenges?
How to integrate with other methods?