Information Visualization for    Social Network Analysis          Ben Shneiderman       ben@cs.umd.edu                  Tw...
Interdisciplinary research community  - Computer Science & Info Studies    - Psych, Socio, Poli Sci & MITH         (www.cs...
Design Issues•   Input devices & strategies     • Keyboards, pointing devices, voice     • Direct manipulation     • Menus...
HCI Pride: Serving 5B UsersMobile, desktop, web, cloud Diverse users: novice/expert, young/old, literate/illiterate,   ab...
Using Vision to Think•   Visual bandwidth is enormous    • Human perceptual skills are remarkable      • Trend, cluster, g...
Spotfire: DC natality data
Information Visualization: Mantra•   Overview, zoom & filter, details-on-demand•   Overview, zoom & filter, details-on-dem...
Information Visualization: Data Types           •SciViz .               1-D Linear   Document Lens, SeeSoft, Info Mural   ...
NSF Workshops: Academics, Industry, Gov’t Jenny Preece (PI), Peter Pirolli & Ben Shneiderman (Co-PIs)                     ...
Cyberinfrastructure: Social Action on National Priorities                           - Scientific Foundations              ...
Summer Social Webshop: August 23-26, 2011
UN Millennium Development GoalsTo be achieved by 2015 and hunger• Eradicate extreme poverty • Achieve universal primary ed...
State-of-the-art network visualization
Node Placement Methods• Node-link diagrams    • Force-directed layout    • Geographical map    • Circular layout    • Temp...
Node Placement Methods• Node-link diagrams    • Force-directed layout    • Geographical map    • Circular layout    • Temp...
Node Placement Methods• Node-link diagrams    • Force-directed layout    • Geographical map    • Circular layout    • Temp...
NetViz Nirvana1) Every node is visible2) For every node  you can count its degree3) For every link  you can follow it  fro...
1) NVSS: Semantic Substrates• Group nodes into regions   According to an attribute     Categorical, ordinal, or binned num...
Force Directed Layout 36 Supreme & 13 Circuit Court decisions268 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)
Network Visualization by Semantic Substrates                                        • Meaningful                          ...
Network Visualization by Semantic Substrates NVSS 2.0 with Substrate Designer
2) SocialAction:Integrating Statistics & VisualizationSenate 2007: 180 out of 310 Votes in Common
Social Action: 2007 Senate Votes   290 out of 310 Votes in Common
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        ...
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 Feder...
WWW2010 Twitter Community
WWW2011 Twitter Community: Grouped
Analogy: Clusters Are OccludedHard 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
US Senate Co-Voting Network 2007,           Clustered  South                        Northeast                         Moun...
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
No Location              Philadelphia                                                 Patent                              ...
No Location                     Philadelphia 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 M...
Social Media Research Foundation               Social Media Research Foundation                       smrfoundation.org   ...
29th Annual Symposium    May 22-23, 2012 www.cs.umd.edu/hcil
 Information Visualization for Social Network Analysis,
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Information Visualization for Social Network Analysis, NVSS semantic substrates, Social Action, NodeXL
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Information Visualization for Social Network Analysis,

  1. 1. Information Visualization for Social Network Analysis Ben Shneiderman ben@cs.umd.edu Twitter: @benbendcFounding Director (1983-2000), Human-Computer Interaction Lab Professor, Department of Computer Science Member, Institute for Advanced Computer Studies
  2. 2. Interdisciplinary research community - Computer Science & Info Studies - Psych, Socio, Poli Sci & MITH (www.cs.umd.edu/hcil)
  3. 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. 4. HCI Pride: Serving 5B UsersMobile, 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. 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. 6. Spotfire: DC natality data
  7. 7. 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
  8. 8. 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
  9. 9. NSF Workshops: Academics, Industry, Gov’t Jenny Preece (PI), Peter Pirolli & Ben Shneiderman (Co-PIs) www.tmsp.umd.edu
  10. 10. 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
  11. 11. Summer Social Webshop: August 23-26, 2011
  12. 12. UN Millennium Development GoalsTo 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
  13. 13. State-of-the-art network visualization
  14. 14. 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
  15. 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. 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. 17. NetViz Nirvana1) Every node is visible2) For every node you can count its degree3) For every link you can follow it from source to destination4) Clusters and outliers are identifiable
  18. 18. 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
  19. 19. Force Directed Layout 36 Supreme & 13 Circuit Court decisions268 Citations on Regulatory Takings 1978-2002
  20. 20. Network Visualization by Semantic Substrates NVSS 1.0
  21. 21. Filtering links by source-target
  22. 22. Filtering links by time attribute (1)
  23. 23. 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
  24. 24. Network Visualization by Semantic Substrates NVSS 2.0 with Substrate Designer
  25. 25. 2) SocialAction:Integrating Statistics & VisualizationSenate 2007: 180 out of 310 Votes in Common
  26. 26. Social Action: 2007 Senate Votes 290 out of 310 Votes in Common
  27. 27. NodeXL:Network Overview for Discovery & Exploration in Excel www.codeplex.com/nodexl
  28. 28. NodeXL: Import Dialogs www.codeplex.com/nodexl
  29. 29. Tweets at #WIN09 Conference: 2 groups
  30. 30. 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
  31. 31. CHI2010 Twitter Community www.codeplex.com/nodexl/
  32. 32. Flickr networks
  33. 33. Flickr clusters for “mouse” Computer Mickey Animal
  34. 34. Figure 7.11. : Lobbying Coalition Network connecting organizations (vertices) that have jointly filed comments on US Federal Communications Commission policies (edges). Vertex Size representsnumber 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.
  35. 35. WWW2010 Twitter Community
  36. 36. WWW2011 Twitter Community: Grouped
  37. 37. Analogy: Clusters Are OccludedHard to count nodes, clusters
  38. 38. Separate Clusters Are More Comprehensible
  39. 39. Twitter Network for “msrtf11 OR techfest ”
  40. 40. Twitter Network for “msrtf11 OR techfest ”
  41. 41. US Senate Co-Voting Network 2007
  42. 42. US Senate Co-Voting Network 2007, Clustered South Northeast Mountain Paci fic Midwest
  43. 43. Small-World Graph with 5 Clusters
  44. 44. Small-World Graph with 5 Clusters
  45. 45. Small-World Graph with 5 Clusters
  46. 46. Pseudo-Random Graph with 5 Clusters
  47. 47. Pseudo-Random Graph with 5 Clusters
  48. 48. Scale-free Network with 10 Clusters
  49. 49. Scale-free Network with 10 Clusters
  50. 50. Scale-free Network with 10 Clusters
  51. 51. Scale-free Network with 10 Clusters
  52. 52. Scale-free Network with 10 Clusters
  53. 53. Innovation Patterns: 11,000 vertices, 26,000 edges
  54. 54. No Location Philadelphia Patent Tech Navy SBIR (federal) PA DCED (state) Related patent 2: Federal agencyPharmaceutical/Medical 3: EnterprisePittsburgh 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 statesWestinghouse Electric
  55. 55. No Location Philadelphia Innovation Clusters: People, Locations, Companies Patent Tech Navy SBIR (federal) PA DCED (state) Related patent 2: Federal agencyPharmaceutical/Medical 3: EnterprisePittsburgh 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 statesWestinghouse Electric
  56. 56. Discussion Group Postings, color by topic www.cs.umd.edu/hcil/non nationofneighbors.net
  57. 57. 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 Networkshttp://www.elsevier.com/wps/find/bookdescription.cws_home/723354/description
  58. 58. 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
  59. 59. 29th Annual Symposium May 22-23, 2012 www.cs.umd.edu/hcil

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