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Charting Collections of Social
Media Connections with NodeXL
Maps and reports for social media networks



                                    April 10-12, Chicago, IL
Please silence
cell phones
            April 10-12, Chicago, IL
About Me

                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            April 10-12, Chicago, IL
  http://www.smrfoundation.org
http://smrfoundation.org
                           April 10-12, Chicago, IL
Social Media (email,
Facebook, Twitter,
YouTube, and more)
is all about
       connections

  from people

                   to people.
                                 5
                                5
Patterns are



               left behind

                              6
                             6
There are many kinds of ties….                                  Send, Mention, Like, Link,
Reply, Rate, Review, Favorite, Friend, Follow, Forward, Edit, Tag, Comment, Check-in…




                                  http://www.flickr.com/photos/stevendepolo/3254238329
Strong ties
Weak ties
http://www.flickr.com/photos/fullaperture/81266869/




                    Strength of Weak ties
“Think Link”
    Nodes & Edges


        Is related to




A                       B
                            11
Each contains one or more
                      social networks




World Wide Web
A network is born whenever two GUIDs are joined.
Username               Attributes                            Username             Attributes
@UserName1             Value, value                          @UserName2           Value, value




             A                          B
             Vertex1                Vertex 2     “Edge”      “Vertex1”    “Vertex2”
                                                 Attribute   Attribute    Attribute
             @UserName1             @UserName2   value       value        value
NodeXL imports “edges” from social media data sources
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.




                                                                              15
Social
   Networks
                                                                       Jacob Moreno ’ s early
                                                                       social network diagram of

History:
                                                                       positive    and   negative
                                                                       relationships      among

from the dawn of time!
                                                                       members of a football
                                                                       team.

Theory and method:                                                     Originally published in

1934 ->
                                                                       Moreno, J. L. (1934). Who
                                                                       shall survive? Washington,

Jacob L. Moreno
                                                                       DC: Nervous and Mental
                                                                       Disease         Publishing
                                                                       Company.




                         http://en.wikipedia.org/wiki/Jacob_L._Moren                   16
2013 passbac-marc smith-node xl-sna-social media-formatted
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 and
                 the worker. Cambridge, UK: Cambridge University Press.
Location, Location, Location
Position, Position, Position
Introduction to NodeXL




                         Like MSPaint™ for network graphs.
                                                   21
2013 passbac-marc smith-node xl-sna-social media-formatted
Communities in
Cyberspace
2013 passbac-marc smith-node xl-sna-social media-formatted
http://www.flickr.com/photos/badgopher/3264760070/
2013 passbac-marc smith-node xl-sna-social media-formatted
http://www.flickr.com/photos/druclimb/2212572259/in/photostrea
                               m/
2013 passbac-marc smith-node xl-sna-social media-formatted
http://www.flickr.com/photos/hchalkley/47839243/
2013 passbac-marc smith-node xl-sna-social media-formatted
http://www.flickr.com/photos/rvwithtito/4236716778
2013 passbac-marc smith-node xl-sna-social media-formatted
http://www.flickr.com/photos/62693815@N03/6277208708/
2013 passbac-marc smith-node xl-sna-social media-formatted
Social Network Maps Reveal

     Key influencers in any topic.

              Sub-groups.

                Bridges.
Hubs
Bridges
http://www.flickr.com/photos/storm-
http://www.flickr.com/photos/library_of_congress/3295494976/sizes/o/in/photostream/
http://www.flickr.com/photos/amycgx/3119640267/
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 &                                             Discussion people
                           Discussion starters
“Answer People”                                             Topic setters
                              Topic setters


                                                                          41
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


                                                                                42
2013 passbac-marc smith-node xl-sna-social media-formatted
http://www.newscientist.com/blogs/onepercent/2011/11/occupy-vs-tea-party-what-their.html




                                                                                  #teaparty
                                                                          15 November 2011




#occupywallstreet
15 November 2011
6 kinds of Twitter social media networks




                                       45
#My2K




Polarized   46
#CMgrChat




In-group / Community
                       47
Lumia




Brand / Public Topic
                       48
#FLOTUS




  Bazaar
           49
New York Times Article
       Paul Krugman




  Broadcast: Audience + Communities   50
Dell Listens/Dellcares




         Support
                         51
SNA questions for social media:


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?



                                                        52
http://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=3965

Top 10 Vertices, Ranked by Betweenness Centrality:
@sqlpass
@BrentO
@PaulRandal
@ClerisyDatabase
@SQLRockstar
@jenstirrup
@SQLChicken
@SQLSocialite
@MicrosoftBI
@kekline
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
2013 passbac-marc smith-node xl-sna-social media-formatted
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), betweenness                  Source: Richards, W.
                                                                      (1986). The NEGOPY
                                                                      network analysis
Methods                                                               program. Burnaby, BC:
                                                                      Department of
Surveys, interviews, observations, log file analysis, computational   Communication, Simon
analysis of matrices                                                  Fraser University. pp.7-
                                                                      16
(Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001)


                                                                                                 59
SNA 101                         • Node
                                   – “actor” on which relationships act; 1-mode versus 2-mode networks
                                • Edge
                A                  – Relationship connecting nodes; can be directional
                                • Cohesive Sub-Group
                                   – Well-connected group; clique; cluster                  A B D E
B                       C       • Key Metrics
                                   – Centrality (group or individual measure)
                                         • Number of direct connections that individuals have with others in the group (usually look at
    D                                      incoming connections only)
                                         • Measure at the individual node or group level
                E                  – 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
        F                   G      – Betweenness (individual measure)
                                         • # shortest paths between each node pair that a node is on
                                         • Measure at the individual node level
            H       I           • Node roles
                                   – Peripheral – below average centrality        C
                                   – Central connector – above average centrality                       D
                                   – Broker – above average betweenness           E
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




                                                                           61
http://www.youtube.com/watch?v=0M3T65Iw3Ac
NodeXL Video
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




                                                                    63
Twitter Network for “Microsoft Research”
              *BEFORE*
Twitter Network for “Microsoft Research”
*AFTER*




                                           65
Network Motif Simplification




                        Cody Dunne, University of Maryland
                                                   66
NodeXL calculates
network metrics and word
pairs

                           67
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.




                          68
69
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
NodeXL             Perform
                   collections of
  Automation         common
                  operations with
makes analysis     a single click
simple and fast
NodeXL Generates Overall Network Metrics
Social Media Research Foundation
         People                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



                                                                                    75
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
                                                                   76
What we have done: Open Tools
NodeXL
Data providers (“spigots”)
•   ThreadMill Message Board
•   Exchange Enterprise Email
•   Voson Hyperlink
•   SharePoint
•   Facebook
•   Twitter
•   YouTube
•   Flickr




                                77
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




                                             78
What we have done: Open Scholarship




                                      79
What we have done: Open Scholarship




                                      80
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


                                                                                 81
How you can help
Sponsor a feature
Sponsor workshops
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



                                                                    82
Charting Collections of Social
Media Connections with NodeXL
Maps and reports for social media networks



                                    April 10-12, Chicago, IL
Win a Microsoft Surface Pro!
Complete an online SESSION EVALUATION
to be entered into the draw.

Draw closes April 12, 11:59pm CT
Winners 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.

                                                                           84
Marc@connectedaction.net

http://www.connectedaction.net
http://www.codeplex.com/nodexl
http://www.twitter.com/marc_smith
http://nodexlgraphgallery.org
http://www.slideshare.net/Marc_A_Smith
http://www.smrfoundation.org




                    Platinum Sponsor
                                         Thank you!
  Diamond Sponsor




                                                 April 10-12, Chicago, IL

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2013 passbac-marc smith-node xl-sna-social media-formatted

Editor's Notes

  1. http://www.flickr.com/photos/lizjones/1571656758/sizes/o/
  2. http://www.flickr.com/photos/kjander/3123883124/sizes/o/
  3. http://www.flickr.com/photos/badgopher/3264760070/
  4. http://www.flickr.com/photos/library_of_congress/3295494976/sizes/o/in/photostream/
  5. http://www.flickr.com/photos/amycgx/3119640267/
  6. A tutorial on analyzing social media networks is available from: casci.umd.edu/NodeXL_TeachingDifferent positions within a network can be measured using network metrics.
  7. http://www.newscientist.com/blogs/onepercent/2011/11/occupy-vs-tea-party-what-their.html
  8. The network of connections among people who tweeted “#My2K” over the 1-day, 21-hour, 39-minute period from Sunday, 06 January 2013 at 03:30 UTC to Tuesday, 08 January 2013 at 01:09 UTC.
  9. The graph represents a network of 268 Twitter users whose recent tweets contained "#cmgrchat OR #smchat. The network was obtained on Friday, 18 January 2013 at 15:44 UTC. There is an edge for each follows relationship. There is an edge for each "replies-to" relationship in a tweet. There is an edge for each "mentions" relationship in a tweet. There is a self-loop edge for each tweet that is not a "replies-to" or "mentions". The tweets were made over the 3-day, 21-hour, 15-minute period from Monday, 14 January 2013 at 18:23 UTC to Friday, 18 January 2013 at 15:38 UTC.
  10. The graph represents a network of 1,227 Twitter users whose recent tweets contained "lumia. The network was obtained on Saturday, 12 January 2013 at 19:52 UTC. There is an edge for each follows relationship. There is an edge for each "replies-to" relationship in a tweet. There is an edge for each "mentions" relationship in a tweet. There is a self-loop edge for each tweet that is not a "replies-to" or "mentions". The tweets were made over the 5-hour, 1-minute period from Saturday, 12 January 2013 at 14:36 UTC to Saturday, 12 January 2013 at 19:37 UTC.
  11. The graph represents a network of 1,260 Twitter users whose recent tweets contained "flotus". The network was obtained on Friday, 18 January 2013 at 18:26 UTC. There is an edge for each follows relationship. There is an edge for each "replies-to" relationship in a tweet. There is an edge for each "mentions" relationship in a tweet. There is a self-loop edge for each tweet that is not a "replies-to" or "mentions". The tweets were made over the 3-hour, 3-minute period from Friday, 18 January 2013 at 15:16 UTC to Friday, 18 January 2013 at 18:20 UTC.
  12. The graph represents a network of 399 Twitter users whose recent tweets contained "http://www.nytimes.com/2013/01/11/opinion/krugman-coins-against-crazies.html. The network was obtained on Friday, 11 January 2013 at 14:27 UTC. There is an edge for each follows relationship. There is an edge for each "replies-to" relationship in a tweet. There is an edge for each "mentions" relationship in a tweet. There is a self-loop edge for each tweet that is not a "replies-to" or "mentions". The tweets were made over the 12-hour, 32-minute period from Friday, 11 January 2013 at 01:52 UTC to Friday, 11 January 2013 at 14:24 UTC.
  13. The graph represents a network of 388 Twitter users whose recent tweets contained "delllistens OR dellcares”. The network was obtained on Tuesday, 19 February 2013 at 17:44 UTC. There is an edge for each follows relationship. There is an edge for each "replies-to" relationship in a tweet. There is an edge for each "mentions" relationship in a tweet. There is a self-loop edge for each tweet that is not a "replies-to" or "mentions". The tweets were made over the 6-day, 21-hour, 58-minute period from Tuesday, 12 February 2013 at 19:34 UTC to Tuesday, 19 February 2013 at 17:33 UTC.
  14. http://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=3983