Presentation to Mobile Web Africa 2011 in Johannesburg, South Africa.

1. Charting Collections of
Connections in Social
Media:
Creating Maps and
Measures with NodeXL
A project from the Social Media Research Foundation: http://www.smrfoundation.org

2. About Me
Introductions
Marc A. Smith
Chief Social Scientist
Connected Action Consulting Group
Marc@connectedaction.net
http://www.connectedaction.net
http://www.codeplex.com/nodexl
http://www.twitter.com/marc_smith
http://delicious.com/marc_smith/Paper
http://www.flickr.com/photos/marc_smith
http://www.facebook.com/marc.smith.sociologist
http://www.linkedin.com/in/marcasmith
http://www.slideshare.net/Marc_A_Smith
http://www.smrfoundation.org

3. Location, Location, Location

4. Network of connections among “SharePoint” mentioning Twitter users
Position, Position, Position

5. Hardin, Garrett. 1968/1977. “The tragedy
of the commons.” Science 162: 1243-
48. Pp. 16-30 in Managing the
Commons, edited by G. Hardin and J.
Baden. San Francisco: Freeman.
Wellman, Barry. 1997. “An electronic
group is virtually a social network.” In
S. Kiesler (Ed.), The Culture of the
Internet. Hillsdale, NJ: Lawrence
Erlbaum.
5

6. Collective Action Dilemma Theory
• Central tenet
– Individual rationality leads to collective disaster
• Phenomena of interest
– Provision and/or sustainable consumption of collective
resources
– Public Goods, Common Property, "Free Rider” Problems,
Tragedies
– Signaling intent
• Methods
– Surveys, interviews, participant observation, log file
analysis, computer modeling
(Axelrod, 1984; Hess, 1995; Kollock & Smith, 1996)
Community Computer Mediated Collective Action

7. Common goods that require controlled consumption
http://flickr.com/photos/himalayan-trails/275941886/

8. Common goods that require collective contribution
http://flickr.com/photos/jose1jose2jose3/241450368/

9. Interactionist Sociology
• Central tenet
– Focus on the active effort of
accomplishing interaction
• Phenomena of interest
– Presentation of self
– Claims to membership
– Juggling multiple (conflicting) roles
– Frontstage/Backstage
– Strategic interaction
– Managing one’s own and others’ “face”
• Methods
– Ethnography and participant observation
(Goffman, 1959; Hall, 1990)

11. Whyte, William H. 1971. City: Rediscovering the Center. New York: Anchor Books.

12. Y’all.
Youse.
Yes, youse.
12

13. I wish I knew you I like your picture You are cool
I was paid to link to you I want your reflected glory
Everybody else links to you I’d vote for you Can I date you?
Are you my friend?
We met at a conference and it seemed like the thing to do.
yes no
I like you I kind of like you I really like you
I know you I feel socially obligated to link to you
I beat you on Xbox Live Hi, Mom I have fake alter egos

14. 14

15. Tag Ecologies I
Adamic et al. WWW 2008

16. Networks reveal patterns
HUB-AND-SPOKE OF DECEIT: When Enron employees communicated about legitimate
projects, e-mails were reciprocal and information was shared widely (right), but
communications about an illicit project (left) reveal a sparse network with a central,
informed clique and isolated external players.
Brandy Aven, CMU
http://www.sciencenews.org/view/generic/id/330731/title/Information_flow_can_reveal_d
irty_deeds

17. Social Media
(email, Facebook, Twitter,
YouTube, and more)
is all about
connections
from people to people.
17

18. Patterns are
left
behind
18

19. There are many kinds of ties….
Like, Link, Reply, Rate, Review, Favorite, Friend, Follow, Forward, Edit, Tag, Comment, Check-in…
http://www.flickr.com/photos/stevendepolo/3254238329

20. Each contains one or more
social networks
World Wide Web

21. Hubs

22. Bridges

23. http://www.flickr.com/photos/library_of_congress/3295494976/sizes/o/in/photostream/

24. http://www.flickr.com/photos/amycgx/3119640267/

26. 20111122-NodeXL-Twitter-mwa11 OR mwa2011 OR mwebafrica OR mobilewebafrica

28. 20111121-NodeXL-Twitter-#occupywallstreet

29. #teaparty
15 November 2011
#occupywallstreet
15 November 2011
http://www.newscientist.com/blogs/onepercent/2011/11/occupy-vs-tea-party-what-their.html

30. 20111122-NodeXL-Twitter-malema

31. Won Soon Park, New Mayor of Seoul Korea

32. Social Network Theory
http://en.wikipedia.org/wiki/Social_network
• Central tenet
– Social structure emerges from
– the aggregate of relationships (ties)
– among members of a population
• Phenomena of interest
– Emergence of cliques and clusters
– from patterns of relationships
– Centrality (core), periphery (isolates),
Source: Richards, W.
– betweenness (1986). The NEGOPY
• Methods network analysis
program. Burnaby, BC:
– Surveys, interviews, observations, Department of
Communication, Simon
log file analysis, computational Fraser University. pp.7-
analysis of matrices 16
(Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001)

33. SNA 101
• Node
A
– “actor” on which relationships act; 1-mode versus 2-mode networks
• Edge
B – Relationship connecting nodes; can be directional
C • Cohesive Sub-Group
– Well-connected group; clique; cluster A B D E
• Key Metrics
– Centrality (group or individual measure)
D • Number of direct connections that individuals have with others in the group (usually look at
incoming connections only)
E • Measure at the individual node or group level
– Cohesion (group measure)
• Ease with which a network can connect
• Aggregate measure of shortest path between each node pair at network level reflects
average distance
– Density (group measure)
• Robustness of the network
• Number of connections that exist in the group out of 100% possible
– Betweenness (individual measure)
F G • # shortest paths between each node pair that a node is on
• Measure at the individual node level
• Node roles
– Peripheral – below average centrality C
H – Central connector – above average centrality D
I – Broker – above average betweenness E

34. http://www.flickr.com/photos/marc_smith/sets/72157622437066929/

36. 20110315-NodeXL-Twitter-sxsw graph

37. Welser, Howard T., Eric Gleave, Danyel Fisher,
and Marc Smith. 2007. Visualizing the Signatures
of Social Roles in Online Discussion Groups.
The Journal of Social Structure. 8(2).
Experts and “Answer People” Discussion people, Topic setters
Discussion starters, Topic setters

38. Answer
Person
Signatures
Discussion
People

39. Discussion
Starter
Spammer
Reply oriented
Discussion
Flame
Warrior
39

40. Now Available

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

42. Separate Clusters Are More Comprehensible

43. Twitter Network for “Microsoft Research”
*BEFORE*

44. Twitter Network for “Microsoft Research”
*AFTER*

45. 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

46. Who we are
People Disciplines Institutions
University Computer Science University of Maryland
Faculty
Students HCI, CSCW Oxford Internet Institute
Industry Machine Learning Stanford University
Independent Information Visualization Microsoft Research
Researchers UI/UX Illinois Institute of
Technology
Developers Social Science/Sociology Connected Action
Network Analysis Cornell
Collective Action Morningside Analytics

47. Social Media Research Foundation
http://smrfoundation.org

48. What we are trying to do:
Open Tools, Open Data, Open Scholarship
• Build the “Firefox of GraphML” – open tools for
collecting and visualizing social media data
• Connect users to network analysis – make
network charts as easy as making a pie chart
• Connect researchers to social media data sources
• Archive: Be the “Allen Very Large Telescope Array”
for Social Media data – coordinate and aggregate
the results of many user’s data collection and
analysis
• Create open access research papers & findings
• Make “collections of connections” easy for users
to manage

49. What we have done: Open Tools
• NodeXL
• Data providers (“spigots”)
– ThreadMill Message Board
– Exchange Enterprise Email
– Voson Hyperlink
– SharePoint
– Facebook
– Twitter
– YouTube
– Flickr

50. What we have done: Open Data
• NodeXLGraphGallery.org
– User generated collection
of network graphs,
datasets and annotations
– Collective repository for
the research community
– Published collections of
data from a range of social
media data sources to help
students and researchers
connect with data of
interest and relevance

51. What we have done: Open Scholarship

52. What we have done: Open Scholarship

53. Facebook networks
http://www.connectedaction.net/2010/04/25/bernie-hogans-facebook-social-network-data-provider-and-visualization-toolkit/

54. NodeXL data import sources

55. Example NodeXL data importer for Twitter

56. NodeXL imports “edges” from social media data sources

57. NodeXL Automation makes analysis simple and fast

58. NodeXL Network Metrics

59. NodeXL simplifies mapping data attributes to display attributes

60. NodeXL displays subgraph images along with network metadata

61. NodeXL enables filtering of networks

62. NodeXL Generates Overall Network Metrics

63. What we want to do:
(Build the tools to) map the social web
• Move NodeXL to the web:
– Node for Google Doc Spreadsheets!
– WebGL Canvas
• Connect to more data sources of interest:
– RDF, MediaWikis, Gmail, NYT, Citation Networks
• Solve hard network manipulation UI problems:
– Modal transform, Time series, Automated layouts
• Grow and maintain archives of social media network data sets for
research use.
• Improve network science education:
– Workshops on social media network analysis
– Live lectures and presentations
– Videos and training materials

64. Work Items
Autofill Group Attribute
Merge Edges by Attribute
Modal Transform
Merge Workbooks
Automated Dynamic Filters: Time Series Analysis, contrast
Captions and Legends
Upload to Graph Gallery++: captions, workbook
Graph Gallery++
User Accounts, Reporting, RSS Feeds,
Network Visualization Web Canvas
Import: RDF, Wiki, SharePoint, Keyword networks from text
Metrics: Triad Census
Layouts:
Force Atlas 2, Lin Log, “Bakshy Plots”, Quality Measures
Query-by-example search for network structures

65. How you can help
• Sponsor a feature
• Sponsor Webshop 2012
• Sponsor a student
• Schedule training
• Sponsor the foundation
• Donate your money, code, computation, storage,
bandwidth, data or employee’s time
• Help promote the work of the Social Media
Research Foundation

66. 20111122-NodeXL-Twitter-poib

67. 20111122-NodeXL-Twitter-zuma

68. Social Network Maps Reveal
Key influencers in any topic.
Sub-groups.
Bridges.

69. Why didn’t you just say so?
Identify the key influencers in any topic.
Netbadges awards badges to influential people
and web sites on the Internet. We analyze the
social network of connections among all the
people or web sites that gather around a topic,
issue, or interest and award badges to key
people and sites, highlighting their recent
content.

73. Contact:
Marc A. Smith
Chief Social Scientist
Connected Action Consulting Group
Marc@connectedaction.net
http://www.connectedaction.net
http://www.codeplex.com/nodexl
http://www.twitter.com/marc_smith
http://delicious.com/marc_smith/Paper
http://www.flickr.com/photos/marc_smith
http://www.facebook.com/marc.smith.sociologist
http://www.linkedin.com/in/marcasmith
http://www.slideshare.net/Marc_A_Smith
http://www.smrfoundation.org

74. Upcoming
Full-day social media network analysis workshops
This Friday – Hands on with NodeXL
Next week
Cape Town
28 November 2011 Johannesburg
Protea Hotel 30 November 2011
Breakwater Lodge, Gordon Institute
Waterfront of Business Science,
Illovo
Marc Smith Walter Pike

75. Charting Collections of
Connections in Social
Media:
Creating Maps and
Measures with NodeXL
A project from the Social Media Research Foundation: http://www.smrfoundation.org