Udell Blogroll exploration

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Udell Blogroll exploration

I adapted Jon Udell's Blogroll data and program to whack out a similarity matrix that could be analyzed by a social network analysis program called ucinet.

I'm hoping that Jon (who knows the data, will comment on the plausibility of the results).

Ucinet's 2D multidimensional scaling routine generates this graph

A factor analysis produces three factors loadings that do look good in 3D (via Visual Python) especially if (only if) you make the picture rotate (by Right-Dragging on the screen. We need an auto-rotate routine).

To see this, run this visual python program:

People=[
("Thierry Lalinne",   -0.57,   0.24, -0.18),
("Paul Snively",    0.42,    0.02, -0.07),
("CE Granier",     0.56,    0.44,   0.05),
("David Brown",    0.44,    0.41,   0.00),
("Joe Jennet",    -0.45,    0.38,   0.11),
("Jim McGee",    -0.11,    0.20,   0.58),
("Jenny Levine",    0.44,    0.28,   0.48),
("Sam Ruby",    -0.09,   -0.78, -0.14),
("Jiri Ludvik" ,   0.17,    0.09, -0.60),
("Jon's Radio",   -0.49, -0.07,   0.12),
("Olivier Travers", 0.07,   -0.02,   0.57),
("Gordon Weakliem",   -0.08, -0.86, -0.19),
("Peter Drayton",    0.04,   -0.76,   0.01),
("Dann Sheridan",    0.44,     0.34, -0.08),
("Marc Barrot",    0.04,   -0.11, -0.60)
]

from visual import *

for p in People:
(name,x,y,z)=p
label(pos=(x,y,z),text=name,height=14,box=0,opacity=0,color=(0,1,1))
sphere(pos=(x,y,z),label=name,radius=0.05)

More detail and ucinet data can be found in Udell Exploration.htm.

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