2009 - Node XL v.84+ - Social Media Network Visualization Tools For Excel 2007

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Overview of the NodeXL project (Network Overview, Discovery and Exploration) that adds social network metrics and visualization features to Excel 2007. Contains updated images from version .84 of the NodeXL project.

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  • “You can make a mess.”
  • 2009 - Node XL v.84+ - Social Media Network Visualization Tools For Excel 2007

    1. 1. NodeXL Network overview, discovery and exploration for Microsoft Excel 2007 http://www.codeplex.com/nodexl Dan Fay (Microsoft Research - Redmond) Cody Dunne (U Maryland) Marc Smith (Telligent) Vladimir Barash (MSR Silicon Valley/Cornell) Tony Capone (Microsoft Research - Redmond) Natasa Milic-Frayling (Microsoft Research - Cambridge) Eduarda Mendes Rodrigues (Microsoft Research - Cambridge) Eric Gleave (U Washington) Adam Perer (U Maryland) Ben Shneiderman (U Maryland)
    2. 2. The NodeXL Team
    3. 3. Problem: No network chart in Excel
    4. 4. Problem: No network chart in Excel
    5. 5. NodeXL: Network analysis and visualization tool • Cyclic Graph data structures have limited support in existing Office tools • Network analysis is of growing importance in academic, commercial, and Internet social media contexts • Existing network analysis tools have command line interfaces or demand steep learning curves • Many network data sets already live in Excel!
    6. 6. NodeXL: Goal: Make SNA easier • Existing Social Network Tools are challenging for many novice users • Tools like Excel are widely used • Leveraging a spreadsheet as a host for SNA lowers barriers to network data analysis and display
    7. 7. Social Network Analysis Toolkit Tools to support the study of the social network structure of social media and other directed graph structures User Experience Computer Scientist Sociologist Information Visualization Algorithmicist for Social Network Measures “What are the “What are the best UI/UX structures of workflows for network “What are the measures communication in analysis tools?” and algorithms needed for scientific understanding networks?” discussions?”
    8. 8. 8
    9. 9. The Ties that Blind? 9
    10. 10. The Ties that Blind? Reply-To Network Network at distance 2 for the most prolific author of the microsoft.public.internetexplorer.general newsgroup
    11. 11. 11 Darwin Bell
    12. 12. The Ties that Blind? Pajek without modification can sometimes reveal structures of great interest.
    13. 13. Mapping Newsgroup Social Ties Microsoft.public.windowsxp.server.general 13 Two “answer people” with an emerging 3rd.
    14. 14. 14
    15. 15. Distinguishing attributes: • Answer person – Outward ties to local isolates – Relative absence of triangles – Few intense ties • Reply Magnet – Ties from local isolates often inward only – Sparse, few triangles – Few intense ties 15
    16. 16. Distinguishing attributes: • Answer person – Outward ties to local isolates – Relative absence of triangles – Few intense ties • Discussion person – Ties from local isolates often inward only – Dense, many triangles – Numerous intense ties 16
    17. 17. Clear and consistent signatures of an “Answer Person” 100 10 1 0 1 2 4 8 16 32 64 • Light touch to numerous threads initiated by someone else • Most ties are outward to local isolates • Many more ties to small fish than big fish 17
    18. 18. Roles Project • Using Netscan Answer Person, microsoft.public.windows.server.general data to derive social roles in Usenet Discussion, rec.kites • Next steps: quantify & Flame, alt.flame explore in more depth Social Support, alt.support.divorce PUBLISHED in HICSS, JCMC, JoSS, IEEE Internet Communications (special issue on Social Networks) 18
    19. 19. NodeXL: Network Overview, Discovery and Exploration for Excel • Leverage spreadsheet for storage of edge and vertex data
    20. 20. The NodeXL project is Available via the CodePlex Open Source Project Hosting Site: http://www.codeplex.com/nodexl
    21. 21. NodeXL workflow data importation > processing > calculation > refinement > a network graph that tells a useful story These steps include: • Import data from several sources and file formats • Scrub data: Merge duplicate edges • Calculate network metrics • Insert sub-graph images • Auto-fill columns (and map data to display attributes): - Set shape, color, opacity, size, and label/tooltip • Create clusters • Show graph • Read workbook • Adjust layout • Layout Again • Dynamic Filters – selectively hide edges and nodes
    22. 22. NodeXL: Import data from multiple sources: • Multiple network “spigots” provide edge lists from several common sources and data formats.
    23. 23. Social media platforms are A source of multiple Social network data sets: “Friends” “Replies” “Follows” “Comments” “Reads” “Co-edits” “Co-mentions” “Hybrids”
    24. 24. Export data to alternate file formats: Prepare data for analysis
    25. 25. NodeXL: Import edges from other spreadsheets • Map data columns from existing spreadsheets
    26. 26. NodeXL: Merge Duplicate Edges (if any) • Aggregate duplicate edges and add a “Tie Strength Column” to store the count of “duplicates” (edges could be from multiple time slices).
    27. 27. NodeXL: Calculate Network Analytics and Metrics • Starter library of basic network measures • Users may unselect resource intensive measures
    28. 28. NodeXL: Insert network sub-graph images • Create “ego- centric” networks for each node in the network • Select number of degrees out to include
    29. 29. NodeXL: Display nodes with subgraph images sorted by network attributes using Excel Data|Sort
    30. 30. NodeXL: Get reports of Metric Value Graph Type Directed global network Unique Edges 7,852 metrics Edges With Duplicates 0 Total Edges 7,852 Self-Loops 10 Vertices 174 Graph Density 0.260514259
    31. 31. NodeXL: Display whole graph • Toggle display of whole graph display pane with Show/Hide Graph Pane
    32. 32. NodeXL: Create a new whole graph display • Select “Read Workbook” to load the graph into the Display Pane. • The title “Document Actions” is imposed by Excel
    33. 33. NodeXL: Viewing the whole graph
    34. 34. NodeXL: Using Dynamic Filters to simplify the graph • Each data column (including dates) associated with an edge or vertex is exposed with a slider filter. • Filtered nodes and edges turn gray or become invisible
    35. 35. NodeXL: Apply dynamic filters to the data
    36. 36. NodeXL: Map data to display attributes • Map Edge and Vertex attributes to size, width, color, opacity, and shape
    37. 37. NodeXL: Decorated Network Graphs
    38. 38. NodeXL: filtered, decorated, labeled networks
    39. 39. NodeXL: Clustered networks
    40. 40. NodeXL: Add URLS to Right-click menu of Nodes
    41. 41. NodeXL: Filtered clusters
    42. 42. Right click the canvass to control attributes of selected nodes
    43. 43. NodeXL: Import social networks from email
    44. 44. NodeXL: Import social networks from email
    45. 45. Systematic Yet Flexible Network Analysis Tasks 1. Overall network metrics (e.g. number of nodes, number of edges, density, diameter) 2. Node rankings (e.g. degree, betweenness, closeness centrality) 3. Edge rankings (e.g. weight, betweenness centrality) 4. Node rankings in pairs (e.g. degree vs. betweenness, plotted on a scatter gram) 5. Edge rankings in pairs 6. Cohesive subgroups (e.g. finding communities in networks) 7. Multiplexity (e.g. analyzing comparisons between different edge types, such as friends vs. enemies) Shneiderman, Perer, Dunne
    46. 46. Sub Graph Whole / Graph All Time / All Time Filtering Network Diagrams Sub Graph / Narrow Time Slice Whole Graph / Narrow Time Slice
    47. 47. Random Layout
    48. 48. Fruchterman-Reingold Layout (Dense)
    49. 49. Fruchterman-Reingold Layout (Loose)
    50. 50. Random Layout (Decorated)
    51. 51. X = In-degree, Y = Out-degree
    52. 52. NodeXL Next Steps • Enhanced layout controls – Smart selection of nodes • Clustering and composite nodes – Add/remove a node to/from a cluster – Add/remove a node to/from a composite • Add social network data sources: – Twitter, YouTube, Facebook, Outlook, Messenger, etc.
    53. 53. NodeXL Partnerships and community • University of Maryland • Northwestern University • Ohio University • Stanford University • University of Pennsylvania 7,000 + downloads on Codeplex
    54. 54. NodeXL User tasks and goals
    55. 55. NodeXL Network overview, discovery and exploration for Microsoft Excel 2007 http://www.codeplex.com/nodexl Dan Fay (Microsoft Research - Redmond) Cody Dunne (U Maryland) Marc Smith (Telligent) Vladimir Barash (MSR Silicon Valley/Cornell) Tony Capone (Microsoft Research - Redmond) Natasa Milic-Frayling (Microsoft Research - Cambridge) Eduarda Mendes Rodrigues (Microsoft Research - Cambridge) Eric Gleave (U Washington) Adam Perer (U Maryland) Ben Shneiderman (U Maryland)

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