Information Visualization for Social Network Analysis,
1. Information Visualization for
Social Network Analysis
Ben Shneiderman ben@cs.umd.edu
Twitter: @benbendc
Founding Director (1983-2000), Human-Computer Interaction Lab
Professor, Department of Computer Science
Member, Institute for Advanced Computer Studies
9. Information Visualization: Data Types
•
SciViz .
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,
•
InfoViz
Temporal LifeLines, TimeSearcher, Palantir, DataMontage
• Tree Cone/Cam/Hyperbolic, SpaceTree, Treemap
• Network Pajek, JUNG, UCINet, SocialAction, NodeXL
10. NSF Workshops: Academics, Industry, Gov’t
Jenny Preece (PI), Peter Pirolli & Ben Shneiderman (Co-PIs)
www.tmsp.umd.edu
11. Cyberinfrastructure: Social Action on National Priorities
- 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
13. UN Millennium Development Goals
To be achieved by 2015 and hunger
• Eradicate extreme poverty
• 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
18. 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
19. 1) NVSS: 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)
• Give users control of link visibility
20. Force Directed Layout
36 Supreme & 13 Circuit Court decisions
268 Citations on Regulatory Takings 1978-2002
24. Network Visualization by Semantic Substrates
• 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
31. 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
35. 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.
55. No Location Philadelphia
Patent
Tech
Navy SBIR (federal)
PA DCED (state)
Related patent
2: Federal agency
Pharmaceutical/Medical 3: Enterprise
Pittsburgh Metro 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
Westinghouse Electric
56. No Location Philadelphia
Innovation Clusters: People, Locations, Companies
Patent
Tech
Navy SBIR (federal)
PA DCED (state)
Related patent
2: Federal agency
Pharmaceutical/Medical 3: Enterprise
Pittsburgh Metro 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
Westinghouse Electric
58. 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
59. 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