information visualization for social network analysis,
DESCRIPTION
Information Visualization for Social Network Analysis, NVSS semantic substrates, Social Action, NodeXL (slide file: Info vis socialnetworkanalysis-v1)TRANSCRIPT
Information Visualization for
Social Network Analysis
Ben Shneiderman [email protected]
Twitter: @benbendc
Founding Director (1983-2000), Human-Computer Interaction Lab
Professor, Department of Computer Science Member, Institute for Advanced Computer Studies
Interdisciplinary research community
- Computer Science & Info Studies
- Psych, Socio, Poli Sci & MITH
(www.cs.umd.edu/hcil)
Design Issues
• Input devices & strategies
• Keyboards, pointing devices, voice
• Direct manipulation
• Menus, forms, commands
• Output devices & formats
• Screens, windows, color, sound
• Text, tables, graphics
• Instructions, messages, help
• Collaboration & Social Media
• Help, tutorials, training
• Search
www.awl.com/DTUI
Fifth Edition: 2010
• Visualization
HCI Pride: Serving 5B Users
Mobile, desktop, web, cloud
Diverse users: novice/expert, young/old, literate/illiterate,
abled/disabled, cultural, ethnic & linguistic diversity, gender,
personality, skills, motivation, ...
Diverse applications: E-commerce, law, health/wellness,
education, creative arts, community relationships, politics,
IT4ID, policy negotiation, mediation, peace studies, ...
Diverse interfaces: Ubiquitous, pervasive, embedded, tangible,
invisible, multimodal, immersive/augmented/virtual, ambient,
social, affective, empathic, persuasive, ...
Using Vision to Think
• Visual bandwidth is enormous
• Human perceptual skills are remarkable
• Trend, cluster, gap, outlier...
• Color, size, shape, proximity...
• Human image storage is fast and vast
• Opportunities
• Spatial layouts & coordination
• Information visualization
• Scientific visualization & simulation
• Telepresence & augmented reality
• Virtual environments
Spotfire: DC natality data
Information Visualization: Mantra
• Overview, zoom & filter, details-on-demand
• Overview, zoom & filter, details-on-demand
• Overview, zoom & filter, details-on-demand
• Overview, zoom & filter, details-on-demand
• Overview, zoom & filter, details-on-demand
• Overview, zoom & filter, details-on-demand
• Overview, zoom & filter, details-on-demand
• Overview, zoom & filter, details-on-demand
• Overview, zoom & filter, details-on-demand
• Overview, zoom & filter, details-on-demand
Information Visualization: Data Types
• 1-D Linear Document Lens, SeeSoft, Info Mural
• 2-D Map GIS, ArcView, PageMaker, Medical imagery
• 3-D World CAD, Medical, Molecules, Architecture
• Multi-Var Spotfire, Tableau, GGobi, TableLens, ParCoords,
• Temporal LifeLines, TimeSearcher, Palantir, DataMontage
• Tree Cone/Cam/Hyperbolic, SpaceTree, Treemap
• Network Pajek, JUNG, UCINet, SocialAction, NodeXL
Info
Viz
Sci
Viz
.
Jenny Preece (PI), Peter Pirolli & Ben Shneiderman (Co-PIs) www.tmsp.umd.edu
NSF Workshops: Academics, Industry, Gov’t
- Scientific Foundations
- Advancing Design of
Social Participation Systems
- Visions of What is Possible With Sharable
Socio-technical Infrastructure
- Participating in Health 2.0
- Educational Priorities for
Technology Mediated Social Participation
- Engaging the Public in Open Government:
Social Media Technology and
Policy for Government Transparency
Cyberinfrastructure: Social Action on National Priorities
Summer Social Webshop: August 23-26, 2011
UN Millennium Development Goals
• Eradicate extreme poverty and hunger
• Achieve universal primary education
• Promote gender equality and empower women
• Reduce child mortality
• Improve maternal health
• Combat HIV/AIDS, malaria and other diseases
• Ensure environmental sustainability
• Develop a global partnership for development
To be achieved by 2015
State-of-the-art network visualization
Node Placement Methods
• Node-link diagrams
• Force-directed layout
• Geographical map
• Circular layout
• Temporal layout
• Clustering
• Layouts based on node attributes
• Matrix-based
• Tabular textual
Node Placement Methods
• Node-link diagrams
• Force-directed layout
• Geographical map
• Circular layout
• Temporal layout
• Clustering
• Layouts based on node attributes
• Matrix-based
• Tabular textual
Node Placement Methods
• Node-link diagrams
• Force-directed layout
• Geographical map
• Circular layout
• Temporal layout
• Clustering
• Layouts based on node attributes
• Matrix-based
• Tabular textual
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
• Group nodes into regions According to an attribute
Categorical, ordinal, or binned numerical
• In each region: Place nodes according to other attribute(s)
• Give users control of link visibility
1) NVSS: Semantic Substrates
Force Directed Layout
36 Supreme & 13 Circuit Court decisions
268 Citations on Regulatory Takings 1978-2002
Network Visualization by Semantic Substrates
NVSS 1.0
Filtering links by source-target
Filtering links by time attribute (1)
• Meaningful
layout of nodes
• User controlled
visibility of links
• Cross refs in
11 Circuit Courts
(green) + few refs to
District Court cases
www.cs.umd.edu/hcil/nvss
Network Visualization by Semantic Substrates
NVSS 2.0
with Substrate Designer
Network Visualization by Semantic Substrates
Senate 2007: 180 out of 310 Votes in Common
2) SocialAction:
Integrating Statistics & Visualization
290 out of 310 Votes in Common
Social Action: 2007 Senate Votes
NodeXL: Network Overview for Discovery & Exploration in Excel
www.codeplex.com/nodexl
NodeXL: Import Dialogs
www.codeplex.com/nodexl
Tweets at #WIN09 Conference: 2 groups
Twitter discussion of #GOP
Red: Republicans, anti-Obama,
mention Fox
Blue: Democrats, pro-Obama,
mention CNN
Green: non-affiliated
Node size is number of followers
Politico is major bridging group
CHI2010 Twitter Community
www.codeplex.com/nodexl/
Flickr networks
Flickr clusters for “mouse”
Computer Mickey
Animal
Figure 7.11. : Lobbying Coalition Network connecting organizations (vertices) that have jointly filed
comments on US Federal Communications Commission policies (edges). Vertex Size represents
number of filings and color represents Eigenvector Centrality (pink = higher). Darker edges connect
organizations with many joint filings. Vertices were originally positioned using Fruchterman-
Rheingold and hand-positioned to respect clusters identified by NodeXL’s Find Clusters algorithm.
WWW2010 Twitter Community
WWW2011 Twitter Community: Grouped
Analogy: Clusters Are Occluded Hard to count nodes, clusters
Separate Clusters Are More Comprehensible
Twitter Network for “msrtf11 OR techfest ”
Twitter Network for “msrtf11 OR techfest ”
US Senate Co-Voting Network 2007
South
Midwest
Northeast
Mountain
Paci
fic
US Senate Co-Voting Network 2007, Clustered
Small-World Graph with 5 Clusters
Small-World Graph with 5 Clusters
Small-World Graph with 5 Clusters
Pseudo-Random Graph with 5 Clusters
Pseudo-Random Graph with 5 Clusters
Scale-free Network with 10 Clusters
Scale-free Network with 10 Clusters
Scale-free Network with 10 Clusters
Scale-free Network with 10 Clusters
Scale-free Network with 10 Clusters
Innovation Patterns: 11,000 vertices, 26,000 edges
Patent
Tech
SBIR (federal)
PA DCED (state)
Related patent
2: Federal agency
3: Enterprise
5: Inventors
9: Universities
10: PA DCED
11/12: Phil/Pitt metro cnty
13-15: Semi-rural/rural cnty
17: Foreign countries
19: Other states
Pittsburgh Metro
Westinghouse Electric
Pharmaceutical/Medical
No Location Philadelphia
Navy
Patent
Tech
SBIR (federal)
PA DCED (state)
Related patent
2: Federal agency
3: Enterprise
5: Inventors
9: Universities
10: PA DCED
11/12: Phil/Pitt metro cnty
13-15: Semi-rural/rural cnty
17: Foreign countries
19: Other states
Pittsburgh Metro
Westinghouse Electric
Pharmaceutical/Medical
No Location Philadelphia
Navy
Innovation Clusters: People, Locations, Companies
Discussion Group Postings, color by topic
www.cs.umd.edu/hcil/non
nationofneighbors.net
Analyzing Social Media Networks with NodeXL
I. Getting Started with Analyzing Social Media Networks
1. Introduction to Social Media and Social Networks
2. Social media: New Technologies of Collaboration
3. Social Network Analysis
II. NodeXL Tutorial: Learning by Doing
4. Layout, Visual Design & Labeling
5. Calculating & Visualizing Network Metrics
6. Preparing Data & Filtering
7. Clustering &Grouping
III Social Media Network Analysis Case Studies
8. Email
9. Threaded Networks
10. Twitter
11. Facebook
12. WWW
13. Flickr
14. YouTube
15. Wiki Networks
http://www.elsevier.com/wps/find/bookdescription.cws_home/723354/description
Social Media Research Foundation
Social Media Research Foundation smrfoundation.org
We are a group of researchers who want to create
open tools, generate and host open data, and
support open scholarship related to social media.
smrfoundation.org
29th Annual Symposium
May 22-23, 2012
www.cs.umd.edu/hcil