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Presentation at the 2013 PASSBAC SQL Server Business Analytics Conference on NodeXL SNA Maps and Reports for social media networks.
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April 10-12, Chicago, IL
Charting Collections of Social Media Connections with NodeXLMaps and reports for social media networks
April 10-12, Chicago, IL
Please silence cell phones
April 10-12, Chicago, IL
About Me
Marc A. SmithChief Social ScientistConnected Action Consulting Group
[email protected]://www.connectedaction.nethttp://www.codeplex.com/nodexlhttp://www.twitter.com/marc_smithhttp://delicious.com/marc_smith/Paper http://www.flickr.com/photos/marc_smithhttp://www.facebook.com/marc.smith.sociologisthttp://www.linkedin.com/in/marcasmithhttp://www.slideshare.net/Marc_A_Smithhttp://www.smrfoundation.org
April 10-12, Chicago, IL
http://smrfoundation.org
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Social Media (email, Facebook, Twitter, YouTube, and more) is all about connections
from people
to people. 5
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Patterns are
left behind
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There are many kinds of ties…. Send, Mention, Like, Link,
http://www.flickr.com/photos/stevendepolo/3254238329
Reply, Rate, Review, Favorite, Friend, Follow, Forward, Edit, Tag, Comment, Check-in…
Internet Verbs!
http://www.flickr.com/photos/fullaperture/81266869/
Strength of Weak ties
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“Think Link”Nodes & Edges
Is related to
A B
World Wide Web
Each contains one or more social networks
Vertex1 Vertex 2 “Edge” Attribute
“Vertex1” Attribute
“Vertex2” Attribute
@UserName1 @UserName2 value value value
A network is born whenever two GUIDs are joined.Username Attributes
@UserName1 Value, value
Username Attributes
@UserName2 Value, value
A B
NodeXL imports “edges” from social media data sources
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http://byobi.com/blog/2013/03/analyzing-sql-server-object-dependencies-with-nodexl/Bill Anton (@SQLbyoBI)
HOW TO BUILD a table of all the object dependencies in a database.
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Social Networks
History: from the dawn of time!Theory and method: 1934 ->Jacob L. Moreno
Jacob Moreno’s early social network diagram of positive and negative relationships among members of a football team.
Originally published in Moreno, J. L. (1934). Who shall survive? Washington, DC: Nervous and Mental Disease Publishing Company.
http://en.wikipedia.org/wiki/Jacob_L._Moreno
Social network diagram of relationships among workers in a factory illustrates the positions different workers occupy within the workgroup.
Originally published in Roethlisberger, F., and Dickson, W. (1939). Management andthe worker. Cambridge, UK: Cambridge University Press.
Location, Location, Location
Position, Position, Position
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Introduction to NodeXL
Like MSPaint™ for network graphs.
PublicationVisualizationAnalysisContainerProviders
Network Analysis Data Flow
http://www.flickr.com/photos/badgopher/3264760070/
Data Providers
Providers
http://www.flickr.com/photos/druclimb/2212572259/in/photostream/
Data Container
Container
Data Analysis
http://www.flickr.com/photos/hchalkley/47839243/
Analysis
Data Visualization
http://www.flickr.com/photos/rvwithtito/4236716778
Visualization
http://www.flickr.com/photos/62693815@N03/6277208708/
Data Publication
Publication
Social Network Maps Reveal
Key influencers in any topic.
Sub-groups.
Bridges.
Hubs
Bridges
Islands
http://www.flickr.com/photos/storm-crypt/3047698741
http://www.flickr.com/photos/library_of_congress/3295494976/sizes/o/in/photostream/
Clusters
http://www.flickr.com/photos/amycgx/3119640267/
Crowds
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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 &“Answer People”
Discussion startersTopic setters
Discussion peopleTopic setters
42D
iane
has
hi
gh
degr
ee
Hea
ther
has
hig
h
betw
eenn
ess
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
#occupywallstreet15 November 2011
#teaparty15 November 2011
http://www.newscientist.com/blogs/onepercent/2011/11/occupy-vs-tea-party-what-their.html
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6 kinds of Twitter social media networks
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#My2K
Polarized
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#CMgrChat
In-group / Community
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Lumia
Brand / Public Topic
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#FLOTUS
Bazaar
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New York Times ArticlePaul Krugman
Broadcast: Audience + Communities
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Dell Listens/Dellcares
Support
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1. What does my topic network look like?2. What does the topic I aspire to be look like?3. What is the difference between #1 and #2?4. How does my map change as I intervene?
What do #SQLPass and #PASSBAC look like?
SNA questions for social media:
Top 10 Vertices, Ranked by Betweenness Centrality:@sqlpass@BrentO@PaulRandal@ClerisyDatabase@SQLRockstar@jenstirrup@SQLChicken@SQLSocialite@MicrosoftBI@kekline
http://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=3965
http://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=3966
Top 10 Vertices, Ranked by Betweenness Centrality:@passbac@MicrosoftBI@dennylee@impetustech@sqlpass@ExtendedResults@StaciaMisner@marcorus@SQLRockstar@jenstirrup
http://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=3982
Top 10 Vertices, Ranked by Betweenness Centrality:@SQLServer@eric_kavanagh@DBA_MAN@confio@DZone@SQLRockstar@YvesMulkers@BrentO@SQL_By_Joey@zymasesystems
http://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=3983
Top 10 Vertices, Ranked by Betweenness Centrality:@timoreilly@hortonworks@cloudera@YvesMulkers@TDWI@IBMbigdata@eric_kavanagh@furrier@benjguin@andreisavu
http://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=3984
Top 10 Vertices, Ranked by Betweenness Centrality:@neo4j@peterneubauer@emileifrem@jimwebber@DZone@Neo4jFr@al3xandru@volkantufekci@ajlopez@p3rnilla
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Central tenet Social structure emerges from the aggregate of relationships (ties) among members of a population
Phenomena of interestEmergence of cliques and clusters from patterns of relationshipsCentrality (core), periphery (isolates), betweenness
MethodsSurveys, 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 Theoryhttp://en.wikipedia.org/wiki/Social_network
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
ED
F
A
CB
H
G
IC
DE
A B D E
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NodeXL: Free/Open Social Network Analysis add-in for Excel 2007/2010 makes graph theory as easy as a pie chart, with integrated analysis of social media sources. See: http://nodexl.codeplex.com
http://www.youtube.com/watch?v=0M3T65Iw3Ac
NodeX
L V
ideo
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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
Twitter Network for “Microsoft Research”*BEFORE*
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Twitter Network for “Microsoft Research”
*AFTER*
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Network Motif Simplification
Cody Dunne, University of Maryland
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NodeXL calculates network metrics and word pairs
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The Content summary spreadsheet displays the
most frequently used URLs, hashtags, and user names
within the network as a whole and within each calculated sub-group.
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NodeXL Ribbon in Excel
NodeXL imports “edges” from social media data sources
NodeXL creates a list of “vertices” from imported social media edges
NodeXL displays subgraph images along with network metadata
Automate
NodeXL Automation
makes analysis
simple and fast
Perform collections of
common operations
with a single click
NodeXL Generates Overall Network Metrics
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Social Media Research FoundationPeople Disciplines Institutions
University Faculty Computer Science University of Maryland
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
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What we are trying to do:Open Tools, Open Data, Open ScholarshipBuild the “Firefox of GraphML” – open tools for collecting and visualizing social media dataConnect users to network analysis – make network charts as easy as making a pie chartConnect researchers to social media data sourcesArchive: Be the “Allen Very Large Telescope Array” for Social Media data – coordinate and aggregate the results of many user’s data collection and analysisCreate open access research papers & findingsMake “collections of connections” easy for users to manage
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What we have done: Open ToolsNodeXLData providers (“spigots”)• ThreadMill Message Board• Exchange Enterprise Email• Voson Hyperlink• SharePoint• Facebook• Twitter• YouTube• Flickr
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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
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What we have done: Open Scholarship
UMD: Webshop 2011, 2012, DSST 2013: NSF, Google, Intel, YahooOther Workshops: • LINKS’13, PAWCON, Purdue,
IEEE CTS
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What we have done: Open Scholarship
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What we want to do: (Build the tools to) map the social web
Move NodeXL to the web: (Node[NOT]XL)• Node for Google Doc Spreadsheets? • WebGL Canvas? D3.JS? Sigma.JS
Connect to more data sources of interest:• RDF, 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
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How you can help
Sponsor a featureSponsor workshopsSponsor a studentSchedule trainingSponsor the foundationDonate your money, code, computation, storage, bandwidth, data or employee’s timeHelp promote the work of the Social Media Research Foundation
April 10-12, Chicago, IL
Charting Collections of Social Media Connections with NodeXLMaps and reports for social media networks
84
Win a Microsoft Surface Pro!
Complete an online SESSION EVALUATION to be entered into the draw.
Draw closes April 12, 11:59pm CTWinners will be announced on the PASS BA Conference website and on Twitter.
Go to passbaconference.com/evals or follow the QR code link displayed on session signage throughout the conference venue.
Your feedback is important and valuable. All feedback will be used to improve and select sessions for future events.
April 10-12, Chicago, IL
Thank you!Diamond Sponsor Platinum Sponsor
http://www.connectedaction.nethttp://www.codeplex.com/nodexlhttp://www.twitter.com/marc_smithhttp://nodexlgraphgallery.orghttp://www.slideshare.net/Marc_A_Smithhttp://www.smrfoundation.org
