New Metrics for New Media Bay Area CIO IT Executives Meetup

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Presentation done by Marc Smith, Chief Social Scientist, Telligent at the Bay Area CIO/IT Executives meetup http://www.meetup.com/CIO-IT-Executives/ run by Tatyana Kanzaveli.

Presentation done by Marc Smith, Chief Social Scientist, Telligent at the Bay Area CIO/IT Executives meetup http://www.meetup.com/CIO-IT-Executives/ run by Tatyana Kanzaveli.

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  • “You can make a mess.”

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  • 1. Telligent Social AnalyticsNew Metrics for New MediaResearch & Tools
    Marc A. SmithChief Social ScientistTelligent Systems
  • 2. E-mail (and more) is from people to people
    2
  • 3. Patterns are left behind
    3
  • 4. Social NetworkTheory
    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
  • 5. Social media platforms are a source of multiple Social network data sets:“Friends”“Replies”“Follows”“Comments”“Reads”“Co-edits”“Co-mentions”“Hybrids”
  • 6. Hardin, Garrett. 1968/1977. “The tragedy of the commons.” Science 162: 1243-48. Pp. 16-30 in Managing the Commons, edited by G. Hardin and J. Baden. San Francisco: Freeman.
    Wellman, Barry. 1997. “An electronic group is virtually a social network.” In S. Kiesler (Ed.), The Culture of the Internet. Hillsdale, NJ: Lawrence Erlbaum.
    6
  • 7. 7
  • 8. 8
  • 9. 9
  • 10. 10
  • 11. AnswerPersonSignatures
    Discussion
    People
    11
  • 12. Discussion Starter
    Spammer
    Reply orientedDiscussion
    Flame
    Warrior
    12
  • 13. The Ties that Blind?
    13
  • 14. Reply-To Network
    Network at distance 2 for the most prolific author of the microsoft.public.internetexplorer.general newsgroup
    The Ties that Blind?
  • 15. 15
    Darwin Bell
  • 16. The Ties that Blind?
    Pajek without modification can sometimes reveal structures of great interest.
  • 17. Mapping Newsgroup Social Ties
    Microsoft.public.windowsxp.server.general
    17
    Two “answer people” with an emerging 3rd.
  • 18. 18
  • 19. Distinguishing attributes:
    Answer person
    Outward ties to local isolates
    Relative absence of triangles
    Few intense ties
    Reply Magnet
    Ties from local isolates
    Often inward only Sparse, few triangles
    Few intense ties
    Reply Magnet
    Ties from local isolates often inward only
    Sparse, few triangles
    Few intense ties
    Journal of Social Structure: “Visualizing the Signatures of Social Roles in Online Discussion Groups” http://www.cmu.edu/joss/content/articles/volume8/Welser/
  • 20. Distinguishing attributes:
    Answer person
    Outward ties to local isolates
    Relative absence of triangles
    Few intense ties
    Discussion person
    Ties from local isolates often inward only
    Dense, many triangles
    Numerous intense ties
    Reply Magnet
    Ties from local isolates often inward only
    Sparse, few triangles
    Few intense ties
    Journal of Social Structure: “Visualizing the Signatures of Social Roles in Online Discussion Groups” http://www.cmu.edu/joss/content/articles/volume8/Welser/
  • 21. Recent publications
    "Visualizing the Signatures of Social Roles in Online Discussion Groups”The Journal of Social Structure.  8(2)
    “Picturing Usenet”
    The Journal of Computer Mediated Communication
    “You are who you talk to”
    HICSS 2007
  • 22. Leading research: Adamic et al. 2008
    Knowledge Sharing and Yahoo Answers: Everyone Knows Something,Adamic, Lada A., Zhang Jun, BakshyEytan, and Ackerman Mark S. , WWW2008, (2008)
  • 23. Use social network analysis measurements in reporting on social media data.Analytics calculates network metrics for all content authors.In-degreeOut-degreeEigenvector centralityClustering coefficientIngredients of User Type Scores
  • 24. Social media usage generatesSocial Networks
  • 25. Display community members sorted by network attributes using Excel Data|Sort
  • 26.
  • 27. User type reports in Telligent Analytics
    Include social network metrics to define different kinds of contributors:
    Answerer: users who reply to many questions from many people.
    Influencer: users who are connected to other well connected users.
    Asker: users who raise questions that get answered by answer people.
    Connector: highly connected users who are replied to or linked to by many other community users.
    Originator: initiates new content in the site that is often linked to by others.
    Commenter: replies or links to content created by others.
    Spectator: reads but tends not to create content.
    Overseer: moderates content created by others.
  • 28. NodeXL: Network Overview, Discovery and Exploration for Excel
    Leverage spreadsheet for storage of edge and vertex data
    http://www.codeplex.com/nodexl
  • 29. The NodeXL Team
  • 30. The NodeXL project is Available via the CodePlexOpen Source Project Hosting Site:
    Site:http://www.codeplex.com/nodexl
  • 31.
  • 32. NodeXL:Display nodes with subgraph images sorted by network attributes using Excel Data|Sort
  • 33. Resources to supportEducational Use ofNodeXLFree Tutorial/Manual
    Data SetsAvailable
  • 34.
  • 35.
  • 36. NodeXL: Filtered clusters
  • 37. NodeXL: Import social networks from email
  • 38. NodeXL: Import social networks from email
  • 39.
  • 40. Social Network Analysis Engine Development: NodeXL
    Extend and apply social network analysis engine:
    Improve layouts and visualizations
    Additional metrics and measures
    Technical architecture shift to the web and cloud
    Scale and performance
    Clustering and time series analysis
  • 41. NodeXL Partnerships and community
    University of Maryland
    Ohio University
    Stanford University
    University of Pennsylvania
    YOU?
    10,000 + downloads on Codeplex
  • 42. Telligent Analytics
    Provides a source of network edge lists and integrates social network metrics in User Type Scores
    Further possible social network analysis applications
    Recommendations: my friend’s edit what documents?
    Search optimization: show documents from “answer people”
    Role discovery: who are the topic starters? The answer people?
  • 43. Telligent Social AnalyticsResearch & Tools
    Marc A. SmithChief Social ScientistTelligent Systems
    Marc.Smith@Telligent.com
    http://www.telligent.com
    http://www.connectedaction.net