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20120622 web sci12-won-marc smith-semantic and social network analysis of …

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  • 1. Semantic and Social Network Analysis of Social Media with NodeXLA project from the Social Media Research Foundation: http://www.smrfoundation.org
  • 2. Social Media Research Foundation http://smrfoundation.org
  • 3. Social Media Research Foundation People Disciplines Institutions University Computer Science University of Maryland Faculty 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
  • 4. About MeIntroductionsMarc A. SmithChief Social ScientistConnected Action Consulting GroupMarc@connectedaction.nethttp://www.connectedaction.nethttp://www.codeplex.com/nodexlhttp://www.twitter.com/marc_smithhttp://delicious.com/marc_smith/Paperhttp://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
  • 5. Like MSPaint™ for graphs
  • 6. 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
  • 7. What we have done: Open Tools• NodeXL• Data providers (“spigots”) – ThreadMill Message Board – Exchange Enterprise Email – Voson Hyperlink – SharePoint – Facebook – Twitter – YouTube – Flickr
  • 8. 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
  • 9. Now Available
  • 10. Group-in-a-box Layout
  • 11. #teaparty 15 November 2011#occupywallstreet15 November 2011http://www.newscientist.com/blogs/onepercent/2011/11/occupy-vs-tea-party-what-their.html
  • 12. This graph represents a directed network of 1,360 Twitter users whose recent tweetscontained "contraceptive OR contraception". The network was obtained on Friday, 08 June 2012 at 13:22 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 2-day period from Thursday, 07 June 2012 at 18:46 UTC to Friday, 08 June 2012 at 13:06 UTC. The graphsvertices were grouped bycluster using the Clauset- Newman-Moore cluster algorithm. The edge colors are based on relationship values. Thevertex sizes are based on each user’s number of followers. Table 1 reports the summary network metrics that describe the graph.
  • 13. Summary network metrics Table 1. Summary network metrics for the graph in Figure 1 Network Metric Value Graph Type Directed Vertices 1360 Unique Edges 5641 Edges With Duplicates 771 Total Edges 6412 Self-Loops 1096 Connected Components 427 Single-Vertex Connected Components 395 Maximum Vertices in a Connected Component 880 Max Edges in a Connected Component 5818 Maximum Geodesic Distance (Diameter) 12 Average Geodesic Distance 3.557807 Graph Density 0.002705817 Modularity 0.446145
  • 14. The Vertices spreadsheet lists users who contributed a tweet containing the terms “contraception ORcontraceptives” over two days in early June 2012. Users are ranked by their computed betweenness centrality within the network of follows, replies, and mentions edges. The top 10 vertices, ranked by betweenness centrality are the accounts at the center of the network. These include: @thinkprogress, @gatesfoundation, @SandraFluke, @maleeek, @Change, @foxandfriends, @melindagates, @AshleyJudd, @cnalive, and @SOHLTC.
  • 15. NodeXL calculatesnetwork metrics and word pairs
  • 16. Contrasting groups
  • 17. The Content summary spreadsheet displays the mostfrequently used URLs, hashtags, and user names within the network as a whole and within each calculated sub-group.
  • 18. Contrast hashtags in Groups 2 & 4
  • 19. Contrasting URL references
  • 20. Word Pair Contrasts
  • 21. Semantic and Social Network Analysis of Social Media with NodeXLA project from the Social Media Research Foundation: http://www.smrfoundation.org