Simplifying Social Network Diagrams
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Simplifying Social Network Diagrams

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Some tips on how to simplify a hairball network diagram using social network stats, especially in Gephi (or NetworkX).

Some tips on how to simplify a hairball network diagram using social network stats, especially in Gephi (or NetworkX).

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Simplifying Social Network Diagrams Presentation Transcript

  • 1. Simplifying Social Network Visualizations
    Lynn Cherny, Ph.D.
  • 2. Why Care? Network (data) is everywhere now…
    1.
    Lynn Cherny, Ghostweather R&D LLC
  • 3. Lynn Cherny, Ghostweather R&D LLC
    A social network is a social structuremade up of individuals (or organizations) called "nodes", which are tied (connected) by one or more specific types of interdependency, such as friendship, kinship, common interest, financial exchange, dislike, sexual relationships, or relationships of beliefs, knowledge or prestige. [--Wikipedia]
    Postdoc at Indiana University ad:
    “Areas of focus will include information diffusion patterns, epidemic models for the spread of ideas, interactions between network traffic and structure dynamics, and agent-based models to explain the emergence of viral bursts of attention.
  • 4. Lynn Cherny, Ghostweather R&D LLC
    And then Moritz Stefaner posted this during the summer…
  • 5. How can we untangle the hairball?
    Using social network analysis metrics and filtering the data set…
    Lynn Cherny, Ghostweather R&D LLC
  • 6. Tools I Used
    Lynn Cherny, Ghostweather R&D LLC
    (free) R
    (free) Python (NetworkX)
    (free) Gephi (www.gephi.org)
    Tableau Desktop
    Excel
    Illustrator and Photoshop
  • 7. Lynn Cherny, Ghostweather R&D LLC
    Gephi – Network vis and analysis
    Statistics Tab
    Color -By…
    Graph Preview
    Layout Method
    Filter Rules
  • 8. Calculate Stats (Gephi and NetworkX)
    Lynn Cherny, Ghostweather R&D LLC
  • 9. Some Important Stats – Degree, Authority, Betweenness…
    Lynn Cherny, Ghostweather R&D LLC
  • 10. R – find correlations among stats
    Lynn Cherny, Ghostweather R&D LLC
  • 11. Lynn Cherny, Ghostweather R&D LLC
  • 12. Lynn Cherny, Ghostweather R&D LLC
  • 13. Betweenness
    Lynn Cherny, Ghostweather R&D LLC
    A measure of connectedness between (sub)components of the graph
    http://en.wikipedia.org/wiki/Centrality#Betweenness_centrality
  • 14. Lynn Cherny, Ghostweather R&D LLC
  • 15. Use “Degree” to scale size of node label in Gephi… still a mess! Not enough yet.
    Lynn Cherny, Ghostweather R&D LLC
  • 16. Detecting Sub-Communities-and then filtering.
    Lynn Cherny, Ghostweather R&D LLC
  • 17. Community Detection Algorithms
    Lynn Cherny, Ghostweather R&D LLC
    Louvain method, implemented in both Gephi and NetworkX
    Outputs a classification for each node in the list – 1, 2, 3… corresponding to the “community” they are closest to.
    http://en.wikipedia.org/wiki/File:Network_Community_Structure.png
  • 18. Lynn Cherny, Ghostweather R&D LLC
  • 19. Lynn Cherny, Ghostweather R&D LLC
  • 20. Lynn Cherny, Ghostweather R&D LLC
    “The Authorities”
    “The Researchers”
  • 21. Summary
    Lynn Cherny, Ghostweather R&D LLC
    You can go from a hairball to an analysis…
    With free tools (plus some standards or extras to make the results pretty)
    Network analysis is another form of data literacy now – think of these methods as similar to other stats, but specific to graphs.
  • 22. Lynn Cherny, Ph.D.lynn@ghostweather.com
    Lynn Cherny, Ghostweather R&D LLC
    Need data help? Have a hairball? Contact me.
    See my blog post on this for more info and links:
    http://blogger.ghostweather.com/