Mdst 3559-04-05-networks-and-graphs

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  • Data Source: Louisa Co. Burnley Slave ListsApplication: GephiLayout algorithm: Dual CircleContent: Slaves, Owners, and PurchasersNotes: This shows the graph at a zoomed out level, where clusterings can be seen, but no specific data points. The four central densely linked nodes are slave owners or purchasers.
  • Data Source: Louisa Co. Burnley Slave ListsApplication: GephiLayout algorithm: Dual CircleContent: Slaves, Owners, and PurchasersNotes: This shows the same graph as the previous slide but zoomed in to show details of data points.

Transcript

  • 1. Modeling Narrative with Networks, Graphs, and Matrices
    MDST 3559: DataestheticsProf. Alvarado04/05/2011
  • 2. Business
    Problems with some comments being classified as spam
    Permissions for posting have been reset …
    Final projects to be announced next Tuesday
    Optional readings posted … see blog
  • 3. Review
    Text vs. Image
    Views of Rustam
    Implicit structures
  • 4. Text vs. Image
    The Images show that Zimmern’s translation is flawed
  • 5. Views of Rustam
    Compassionate but badass Hero; Batman
    Somewhere between King and peasant
    “He needs God to be with him, so he doesn’t appear to be a religious figure.” (?)
    Fears nothing
    Resourceful
    Part human, part animal
    Arrogant
    Quick-witted
    Chivalric Hero
    A Prince (?)
    “he had not of his own choice chosen this adventure”
    Bound by Destiny
    Agency is might
    His sword is badass, it “cleaves / Not the armour of jousting knights, / But the skulls of dragons and Deevs.”
  • 6. Rustamas Liminal Hero
    SON OF
    RUSTAM
    AGENT OF
    SUB FOR
  • 7. Structure?
    Rustam= PowerPuff Girls
    Kai Kaus = Mayor
    Zal = Father (kind of)
    King of M = Mojo Jojo
    White Deev = One of MJ's minions
    Lions, etc. = Fuzzy Lumpkins?
  • 8. Structure
    Frodo = Dorothy
    Ring = Slippers
    Sam = Tin Man, etc.
    Gandalf = Good Witch
    Sauron = Bad Witch
    Gollum = Toto -> mediator
  • 9. Structure
  • 10. http://oceansunfish.org/evolution.php
  • 11. Structuralist “Prosopography”
    Recurring patterns and structures imply cultural models
    Political Organization
    KING / COUNCILLOR (PRIEST) / WARRIOR
    Nature of Power
    Royal Power is fragile and dependent
    Now, How to Describe and Represent?
  • 12. http://www.nature.com/nrg/journal/v7/n5/fig_tab/nrg1835_F3.html
  • 13. Overview
    Discuss Ramsay, “In Praise of Pattern,” to explore ways of modeling and visualizing narrative
    Look at some other examples
    Discuss graphablepatterns in the Shahnameh, in preparation for hands-on work Thursday
  • 14. In Praise of Pattern
    Ramsay argues that, in addition to the quantitative theorems of graph theory, graphs make good visualizations
    They help you notice things, patterns
    See version with images
    http://studio1.shanti.virginia.edu/~rca2t/dataesthetics/04-05/ramsay-2005.html
  • 15. Graph Theory
    The Geometry of Posistion (actually coined by Leibniz)
    Reduces things to “vertices” and “edges”
    Or “nodes” and “links” (dots and lines)
    Theorems concern features such
    number of nodes
    number of edges
    number of edges per node
    “degrees” of separation between nodes, etc.
  • 16. Euler’s Solution to the Seven Bridges Problem
    3
    It becomes clear that nodes with with odd numbered links are a problem – if you come back to it, and aren’t finished, you are stuck …
    Vizualized in this way, the problem becomes one of drawing the picture without retracing any line and without picking up the pencil.
    3
    5
    3
    http://mathforum.org/isaac/problems/bridges2.html
  • 17. Shaded Similarity Matrices
    “You take a set of data measurements for a set of classes and use it to create another table that expresses degrees of proximity among those measurements. . .
    “You then reorganize those values so that “more similar” values are adjacent to one another, assign each value a color, and arrange them in a grid.”
  • 18.
  • 19. Ramsay’s Application
    Correlate graph properties with genre for plays
    5 properties: Distinct, Total, Singles, Loops, and Switches
    4 genres: Romance, Tragedy, History, and Comedy
    “Low-level” vs. “high-level” properties
    Method
    X and Y axes both show plays, colored by genre
    Each cell in the matrix is shaded according to similarity in terms of low-level properties
    Low-level properties are added successively and the order of plays is changed to find clustering
  • 20.
  • 21.
  • 22.
  • 23.
  • 24. PROTOVIS
    “Adjacency matrix” of characters in Les Misérables
    http://vis.stanford.edu/protovis/ex/matrix.html
  • 25.
  • 26.
  • 27. The Charrette Project
    A database of manuscripts, the critical edition, and poetic and grammatical data associated with Chrétien de Troyes's Le Chevalier de la Charrette (Lancelot, ca. 1180)
    Home page:
    http://www.princeton.edu/~lancelot/ss/index.shtml
    Interactive database:
    http://gravitas.princeton.edu/charrette/figura/index.php
  • 28. http://studio1.shanti.virginia.edu/~rca2t/dataesthetics/CASES/Charrette/hg/
  • 29.
  • 30. Data Models
    http://studio1.shanti.virginia.edu/~rca2t/dataesthetics/04-05/example-01.php
  • 31. Patterns in the Shahnameh
    Characteristic events (event types) and sequences
    E.g. drinking wine
    Implied social networks
    Next week, we will look at these patterns and explore tools to visualize them