Slides - SNAP - Stanford University
Slides - SNAP - Stanford University
Slides - SNAP - Stanford University
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How to characterize networks?<br />
Degree distribution P(k)<br />
Clustering Coefficient C<br />
Diameter (avg. shortest path length) h<br />
How to model networks?<br />
Erdös-Renyi Random Graph [Erdös-Renyi, ‘60]<br />
G n,p: undirected graph on n nodes where each<br />
edge (u,v) appears independently with prob. P<br />
Degree distribution: Binomial(n, p)<br />
Clustering coefficient:<br />
Diameter: (next)<br />
k<br />
C ≅<br />
p =<br />
n<br />
10/4/2011 Jure Leskovec, <strong>Stanford</strong> CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 2<br />
P(k)<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
i<br />
1 2 3 4<br />
k<br />
C i=1/3
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