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.

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. The NodeXL Team

3. Problem: No network chart in Excel

4. Problem: No
network chart in
Excel

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. 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. 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

9. The Ties that Blind?
9

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
Darwin Bell

12. The Ties that Blind?
Pajek without modification can
sometimes reveal structures of great interest.

13. Mapping
Newsgroup
Social
Ties
Microsoft.public.windowsxp.server.general
13
Two “answer people” with an emerging 3rd.

14. 14

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. 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. 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. 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. NodeXL:
Network Overview, Discovery and Exploration
for Excel
• Leverage spreadsheet for storage of edge and
vertex data

20. The NodeXL project is
Available via the CodePlex
Open Source Project
Hosting Site:
http://www.codeplex.com/nodexl

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. NodeXL: Import data from multiple sources:
• Multiple network
“spigots” provide
edge lists from
several common
sources and data
formats.

23. Social media platforms are
A source of multiple
Social network data sets:
“Friends”
“Replies”
“Follows”
“Comments”
“Reads”
“Co-edits”
“Co-mentions”
“Hybrids”

25. Export data to alternate file formats:
Prepare data for analysis

26. NodeXL: Import edges from other spreadsheets
• Map data columns from existing spreadsheets

27. 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).

28. NodeXL: Calculate Network Analytics and Metrics
• Starter library of
basic network
measures
• Users may unselect
resource intensive
measures

29. NodeXL: Insert network sub-graph images
• Create “ego-
centric”
networks for
each node in
the network
• Select number
of degrees out
to include

30. NodeXL:
Display nodes
with subgraph
images
sorted by
network
attributes
using Excel
Data|Sort

31. 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

32. NodeXL: Display whole graph
• Toggle display of whole graph display pane
with Show/Hide Graph Pane

33. 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

34. NodeXL: Viewing the whole graph

35. 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

36. NodeXL: Apply dynamic filters to the data

37. NodeXL: Map data to display attributes
• Map Edge
and Vertex
attributes
to size,
width,
color,
opacity,
and shape

38. NodeXL: Decorated Network Graphs

39. NodeXL: filtered, decorated, labeled networks

40. NodeXL: Clustered networks

41. NodeXL: Add URLS to Right-click menu of Nodes

42. NodeXL: Filtered clusters

43. Right click the canvass to control
attributes of selected nodes

44. NodeXL: Import social networks from email

45. NodeXL: Import social networks from email

47. 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

48. Sub Graph Whole
/ Graph
All Time /
All Time
Filtering Network
Diagrams
Sub Graph
/
Narrow
Time Slice
Whole
Graph
/
Narrow
Time Slice

49. Random Layout

50. Fruchterman-Reingold Layout
(Dense)

51. Fruchterman-Reingold Layout
(Loose)

52. Random Layout
(Decorated)

53. X = In-degree, Y = Out-degree

54. 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.

55. NodeXL Partnerships and community
• University of Maryland
• Northwestern University
• Ohio University
• Stanford University
• University of Pennsylvania
7,000 + downloads on Codeplex

56. NodeXL User tasks and goals

57. 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)