The document outlines the principles and applications of information visualization in social network analysis, highlighting the interdisciplinary nature of the field and the diverse user base. It discusses design considerations, data types, and methods for effective visualization, as well as specific tools like NodeXL for analyzing social media networks. It also emphasizes the importance of visual perception and the various contexts in which visualizations can be applied across different sectors.

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

2. Interdisciplinary research community
- Computer Science & Info Studies
- Psych, Socio, Poli Sci & MITH
(www.cs.umd.edu/hcil)

3. 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 www.awl.com/DTUI
• Help, tutorials, training
Fifth Edition: 2010
• Search • Visualization

4. 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, ...

5. 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

6. Spotfire: DC natality data

8. 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

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

12. Summer Social Webshop: August 23-26, 2011

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

14. State-of-the-art network visualization

15. 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

16. 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

17. 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

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

21. Network Visualization by Semantic Substrates
NVSS 1.0

22. Filtering links by source-target

23. Filtering links by time attribute (1)

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

25. Network Visualization by Semantic Substrates
NVSS 2.0
with Substrate Designer

26. 2) SocialAction:
Integrating Statistics & Visualization
Senate 2007: 180 out of 310 Votes in Common

27. Social Action: 2007 Senate Votes
290 out of 310 Votes in Common

28. NodeXL:
Network Overview for Discovery & Exploration in Excel
www.codeplex.com/nodexl

29. NodeXL: Import Dialogs
www.codeplex.com/nodexl

30. Tweets at #WIN09 Conference: 2 groups

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

32. CHI2010 Twitter Community
www.codeplex.com/nodexl/

33. Flickr networks

34. Flickr clusters for “mouse”
Computer Mickey
Animal

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.

36. WWW2010 Twitter Community

37. WWW2011 Twitter Community: Grouped

38. Analogy: Clusters Are Occluded
Hard to count nodes, clusters

39. Separate Clusters Are More Comprehensible

40. Twitter Network for “msrtf11 OR techfest ”

41. Twitter Network for “msrtf11 OR techfest ”

42. US Senate Co-Voting Network 2007

43. US Senate Co-Voting Network 2007,
Clustered
South
Northeast
Mountain
Paci
fic
Midwest

44. Small-World Graph with 5 Clusters

45. Small-World Graph with 5 Clusters

46. Small-World Graph with 5 Clusters

47. Pseudo-Random Graph with 5 Clusters

48. Pseudo-Random Graph with 5 Clusters

49. Scale-free Network with 10 Clusters

50. Scale-free Network with 10 Clusters

51. Scale-free Network with 10 Clusters

52. Scale-free Network with 10 Clusters

53. Scale-free Network with 10 Clusters

54. Innovation Patterns: 11,000 vertices, 26,000 edges

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

57. Discussion Group Postings, color by topic
www.cs.umd.edu/hcil/non
nationofneighbors.net

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

60. 29th Annual Symposium
May 22-23, 2012
www.cs.umd.edu/hcil