This document introduces Marc Smith and his work analyzing social networks. It provides biographical information on Smith and describes some of the tools he has created for social network analysis, including NodeXL. NodeXL is a free social network analysis plugin for Excel that allows users to import and analyze data from social media sources. The document also provides examples of NodeXL network maps and analyses that Smith has conducted on social media discussions around topics like the 2010 Gulf oil spill.
5. 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
7. Network of connections among “ecomm” mentioning Twitter users ecomm
Position, Position, Position
8. Social
Networks
• History:
from the
dawn of
time!
• Theory and
method:
1934 ->
• Jacob L.
Moreno
• http://en.wiki
pedia.org/wiki
/Jacob_L._Mor
eno
9. 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
10. 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)
12. 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). [Local copy]
Experts and “Answer People” Discussion people, Topic setters
Discussion starters, Topic setters
13. Friends, foes, and
fringe: norms and
structure in political
discussion
networks.
Proceedings of the
2006 International
Conference on
Digital Government
Research.
John Kelly, Danyel
Fisher, and Marc
Smith.
14. Himelboim, Itai, Eric Gleave, and Marc Smith.
2009. Discussion catalysts in online
political discussions: Content importers
and conversation starters.
The Journal of Computer-Mediated
Communication, Vol. 14.
16. NodeXL: Network
Overview, Discovery and Exploration
for Excel
Leverage spreadsheet for storage of
edge
and vertex data
http://www.codeplex.com/nodexl
19. NodeXL
Network Overview Discovery and Exploration add-in for Excel 2007
A minimal network can illustrate
the ways different locations have
different values for centrality and
degree
30. NodeXL
Free/Open Social Network Analysis add-in for Excel 2007 makes graph theory
as easy as a bar chart, integrated analysis of social media sources.
http://nodexl.codeplex.com
39. Scott Golder (@redlog) is a graduate student in Sociology at Cornell University. He was
previously a researcher at HP Labs, and holds an A.B. in Linguistics with Computer Science from
Harvard University and an M.S. in Media Arts and Sciences from the MIT Media Laboratory. His
research interests broadly include network and social identity effects online, which he has
examined in a variety of environments including usenet, online poker, social bookmarking and
social network services. His website is www.redlog.net.
Vladimir Barash (@vlad43210) is a graduate student in Information Science at Cornell
University. He holds a BA in Cognitive Science from Yale University. His research interests
include social media, online communities and diffusion, and his thesis topic is on the
structural properties of diffusion in social networks. His websited is www.vlad43210.com
42. 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