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IEEE SocialCom 2009: NetViz Nirvana (NodeXL Learnability)
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IEEE SocialCom 2009: NetViz Nirvana (NodeXL Learnability)

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NodeXL presentation for SocialCom and for Microsoft Research (social analytics) 2009. Describes the NodeXL study with information/library science students and computer science students on the social …

NodeXL presentation for SocialCom and for Microsoft Research (social analytics) 2009. Describes the NodeXL study with information/library science students and computer science students on the social network analysis tool, NodeXL. The study was sponsored by Microsoft Research and designed by Dr. Derek Hansen, Dana Rotman, Cody Dunne, Dr. Ben Shneiderman and Elizabeth Bonsignore.

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  • 1. First Steps to NetViz Nirvana: Evaluating Social Network Analysis with NodeXL
    1
  • 2. Motivation & Goals for Study
    NodeXL evaluation
    NetViz Nirvana & Readability Metrics
    Research Methods
    Samples of Student Work
    Lessons Learned
    Educators
    Designers
    Researchers
    2
  • 3. SNA Tools are not just for scientists anymore
    Long-term Goal: Accessible Tools and Educational Strategies
    How can we support practitioners to cultivate
    sustainable online communities?
    Create Your Own
    Social Network Site
    Images courtesy of: Luc Legay’s twitter & facebook network visualizations (http://www.flickr.com/photos/luc/1824234195/in/set-72157605210232207/)
    and http://prblog.typepad.com,
  • 4. Focus for this talk
    • Evaluation of NodeXL
    • 5. For teaching SNA concepts
    • 6. For diverse user set
    • 7. NetViz Nirvana principles &
    Readability Metrics (RMs)
    4
  • 8. Focus for this talk
    • Evaluation of NodeXL
    • 9. For teaching SNA concepts
    • 10. For diverse user set
    • 11. NetViz Nirvana principles &
    Readability Metrics (RMs)
    5
  • 12. 6
    Network Overview, Discovery and Exploration for Excel
  • 13. 7
    Network Overview, Discovery and Exploration for Excel
    • Import network data
    from existing spreadsheets
    • …Or, from several common
    social network data sources
  • 14. 8
    Network Overview, Discovery and Exploration for Excel
    • Library of basic network metrics
    • 15. Select as Needed
  • 9
    Network Overview, Discovery and Exploration for Excel
    • Multiple ways to map data
    to display properties
  • 16. Focus for this talk
    • Evaluation of NodeXL
    • 17. For teaching SNA concepts
    • 18. For diverse user set
    • 19. NetViz Nirvana principles &
    Readability Metrics (RMs)
    10
  • 20. NetViz Nirvana
    • Every node is visible
    • 21. Every node’s degree is countable
    • 22. Every edge can be followed from source to destination
    • 23. Clusters and outliers are identifiable
    11
  • 24. Readability Metrics
    • How understandable is the network drawing?
    • 25. Continuous scale [0,1]
    • 26. Also called aesthetic metrics
    • 27. Global metrics are not sufficient to guide users
    • 28. Node and edge readability metrics
    12
  • 29. 13
    Node Occlusion RM
    • Proportional to the lost node area when ‘flattening’ all overlapping nodes
    • 30. 1: No area is lost
    • 31. 0: All nodes overlap completely (N-1 node areas lost)
    C
    B
    A
    D
  • 32. 14
    A
    Edge Crossing RM
    • Number of crossings scaled by approximate upper bound
    C
    B
    D
  • 33. 15
    Edge Tunnel RM
    • Number of tunnels scaled by approximate upper bound
    • 34. Local Edge Tunnels
    • 35. Triggered Edge Tunnels
    C
    B
    A
    D
  • 36. 16
    Label Height RMs
    • Text height should have a visual angle within 20-22 minutes of arc
  • 17
    Label Distinctiveness
    • Every label should be uniquely identifiable
    • 37. Prefix trees find all identical labels at any truncation length
  • Qualitative Theoretical Foundation
    Multi-Dimensional In-depth Long-term Case Studies Approach (MILCs)
    Ideal for studying how users explore complex data sets
    Two-Pronged User Survey
    Core Set of Data Collection Methods
    Length & Focus tailored to background of each group
    18
  • 38. 19
  • 39. 20
  • 40. Salient issues: Learning & Teaching SNA
    Students enjoy mapping display properties for nodes & edges that reflect the actors & relations they represent
    NodeXL effectively supports this integration of data & visualization
    Students strove to achieve NetViz Nirvana
    21
  • 41. 22
    Use of NodeXL to
    • Identify Boundary Spanners across sub-groups of Ravelry community
    • 42. Gain insight on factors leading to high # of completed projects
  • 23
    Node Color == Betweenness Centrality
    Node Size == Eigenvector Centrality
    Use of NodeXL to
    • Confirm hypotheses about key characteristics for listserv admin
    • 43. Model a potential management problem with ease
  • 24
    Lessons Learned for Educators
    • Promote awareness of layout considerations (NetViz Nirvana)
    • 44. Scaffold learning with interaction history & “undo” actions
    • 45. Pacing issues
    • 46. Higher level of Excel experience desirable
  • 25
    Lessons Learned for Researchers
    • MILCs more representative of exploratory analysis than traditional usability tests
    • 47. MILCs also more representative of the learning process
    • 48. MILCs require more intensive data collection & analysis
  • 26
    Lessons Learned for Designers
    • Multiple coordinated views (data, visualization, statistics)
    • 49. Encode visual elements with individual & community attributes
    • 50. Add RM interactions (based on NetViz Nirvana)
    • 51. Extensible data manipulation
    • 52. Track interaction history & “undo” actions
    • 53. Improved edge & node aggregation
  • Research Methods
    User pool represented diversity & depth
    SNA Education
    IS user results showcased NodeXL’s power as a learning & teaching tool for SNA
    NodeXL Usability and Design
    CS user feedback enabled rapid implementation of requested features & fixes during the study & beyond
    27
  • 54. Questions?
    http://casci.umd.edu/NodeXL_Teaching
    http://www.codeplex.com/NodeXL
    http://www.cs.umd.edu/hcil/research/visualization.shtml
    Thank you!
    28
    Cody Dunne cdunne@cs.umd.edu
    Elizabeth Bonsignore ebonsign@umd.edu
  • 55. 29
    backup slides follow
    (extra student graph for MSR talk)
  • 56. 30
    KEY
    Sub-Groups
    Community Leaders
    Hosts
    Use of NodeXL to
    • Identify Boundary Spanners in the
    Subaru Owners’ sub-group
    • Show levels of participation in different forums (edge width)
    Carspace community logo courtesy of Edmund’s CarSpace: http://www.carspace.com/
  • 57. First Steps to NetViz Nirvana: Evaluating Social Network Analysis with NodeXL
    Elizabeth Bonsignore, Cody Dunne
    Dana Rotman, Marc Smith, Tony Capone, Derek L. Hansen, Ben Shneiderman
    31

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