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A project from the Social Media Research Foundation: http://www.smrfoundation.org

Social data: Advanced Methods –

Social (Media) Network

Analysis with NodeXL

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

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

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

Collaboration networks are social networks

SNA 101 • Node

– “actor” on which relationships act; 1-mode versus 2-mode networks

• Edge – Relationship connecting nodes; can be directional

• Cohesive Sub-Group – Well-connected group; clique; cluster

• Key Metrics – Centrality (group or individual measure)

• Number of direct connections that individuals have with others in the group (usually look at incoming connections only)

• 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) • # shortest paths between each node pair that a node is on • Measure at the individual node level

• Node roles – Peripheral – below average centrality – Central connector – above average centrality – Broker – above average betweenness

E

D

F

A

C B

H

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C D

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A B D E

Location, Location, Location

Network of connections among “SharePoint” mentioning Twitter users

Position, Position, Position

#SxSW Twitter Network

#SxSW Twitter Network

#Analytics Twitter Network

#Analytics Twitter Network

#SPSS Twitter Network

#SPSS Twitter Network

#SAS Twitter Network

#SAS Twitter Network

#PAWCON Twitter Network

#PAWCON Twitter Network

#ARM Twitter Network

#PwC Twitter Network

#WDW Twitter Network

Introduction to NodeXL

NodeXL: Network Overview, Discovery and Exploration for Excel

Leverage spreadsheet for storage of edge

and vertex data http://www.codeplex.com/nodexl

For GraphML

Social Media Research Foundation Open Tools, Open Data, Open Scholarship

Social Media Research Foundation http://smrfoundation.org

Now Available

Communities in Cyberspace

Social Media Research Foundation

• Tools:

– NodeXL

– ThreadMill

• Data

– Twitter networks

• Scholarship

– Publications

Help us: Join the data collection federation! Upload data sets to our archive! Try the tools!

There are many kinds of ties….

http://www.flickr.com/photos/stevendepolo/3254238329

“Think Link” Nodes & Edges

Is related to

A B Ties of different types

Edits

Shares membership

“Think Link” Nodes & Edges

Is related to

Person Document

Nodes of different types

Edits

Shares membership

Collections of Connections Centralities

• Degree • Closeness • Betweenness • Eigenvector

http://en.wikipedia.org/wiki/Centrality

Import from multiple social media network

sources

World Wide Web

Each contains one or more social networks

NodeXL Network Overview Discovery and Exploration add-in for Excel 2007/2010

A minimal network can illustrate the ways different

locations have different values for centrality and degree

• 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), – betweenness

• Methods – Surveys, interviews, observations,

log file analysis, computational analysis of matrices

(Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001)

Source: Richards, W. (1986). The NEGOPY network analysis program. Burnaby, BC: Department of Communication, Simon Fraser University. pp.7-16

Social Network Theory http://en.wikipedia.org/wiki/Social_network

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 starters, Topic setters

Discussion people, Topic setters

http://www.youtube.com/watch?v=0M3T65Iw3Ac

No

deX

L V

ideo

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

2010 - May - 7 - NodeXL - twitter global warming

2010 - May - 7 - NodeXL - twitter climate change

Social media looks like...

http://www.cmu.edu/joss/content/articles/volume8/Welser/

Which contains subgraphs

That result in “Badges” Markers of social status

Thanks to 3ones.com

Summary: SNA tells you:

• Macro:

– What is the “shape” of the crowd?

– Are there sub-groups/clusters?

• Micro:

– Who is at the “center”?

– Who is at the “edge”?

– Who is the “bridge”?

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

A project from the Social Media Research Foundation: http://www.smrfoundation.org

Social data: Advanced Methods –

Social (Media) Network

Analysis with NodeXL

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