predictive analytics world 2020 - social data: advanced methods social (media) network ... ·...
TRANSCRIPT
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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
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About Me
Introductions Marc A. Smith Chief Social Scientist Connected Action Consulting Group [email protected] 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
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http://www.flickr.com/photos/library_of_congress/3295494976/sizes/o/in/photostream/
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http://www.flickr.com/photos/amycgx/3119640267/
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Collaboration networks are social networks
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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
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Location, Location, Location
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Network of connections among “SharePoint” mentioning Twitter users
Position, Position, Position
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#SxSW Twitter Network
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#SxSW Twitter Network
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#Analytics Twitter Network
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#Analytics Twitter Network
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#SPSS Twitter Network
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#SPSS Twitter Network
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#SAS Twitter Network
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#SAS Twitter Network
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#PAWCON Twitter Network
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#PAWCON Twitter Network
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#ARM Twitter Network
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#PwC Twitter Network
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#WDW Twitter Network
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Introduction to NodeXL
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NodeXL: Network Overview, Discovery and Exploration for Excel
Leverage spreadsheet for storage of edge
and vertex data http://www.codeplex.com/nodexl
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For GraphML
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Social Media Research Foundation Open Tools, Open Data, Open Scholarship
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Now Available
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Communities in Cyberspace
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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!
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Links!
• Download NodeXL: – http://nodexl.codeplex.com/
• Images of social media networks: – http://www.flickr.com/photos/marc_smith/sets/72157622437066929/
• Social Media Research Foundation: – http://www.smrfoundation.org/
• Connected Action Group: – http://www.connectedaction.net/
• Slides! – http://www.slideshare.net/Marc_A_Smith
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There are many kinds of ties….
http://www.flickr.com/photos/stevendepolo/3254238329
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“Think Link” Nodes & Edges
Is related to
A B In and Out Degree
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“Think Link” Nodes & Edges
Is related to
A B Ties of different types
Edits
Shares membership
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“Think Link” Nodes & Edges
Is related to
Person Document
Nodes of different types
Edits
Shares membership
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Collections of Connections Centralities
• Degree • Closeness • Betweenness • Eigenvector
http://en.wikipedia.org/wiki/Centrality
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Import from multiple social media network
sources
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World Wide Web
Each contains one or more social networks
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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
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Social Networks
• History: from the dawn of time!
• Theory and method: 1934 ->
• Jacob L. Moreno
• http://en.wikipedia.org/wiki/Jacob_L._Moreno
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• 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
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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
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http://www.youtube.com/watch?v=0M3T65Iw3Ac
No
deX
L V
ideo
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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
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2010 - May - 7 - NodeXL - twitter global warming
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2010 - May - 7 - NodeXL - twitter climate change
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Social media looks like...
http://www.cmu.edu/joss/content/articles/volume8/Welser/
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Which contains subgraphs
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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”?
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Contact:
Marc A. Smith Chief Social Scientist Connected Action Consulting Group [email protected] 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
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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