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10/15/2009 Jure Leskovec, <strong>Stanford</strong> CS322: Network Analysis [Mitzenmacher]
Hierarchical model that produces power‐laws power laws Zipf’s Zipf s law – how does the frequency of a word depend on its rank? Empirically: rank ~1/freq 10/15/2009 Jure Leskovec, <strong>Stanford</strong> CS322: Network Analysis
Page 1 and 2: CS 322: (Social and Information) Ne
Page 3 and 4: What is the relation between the nu
Page 5 and 6: Citations among physics papers 199
Page 7 and 8: Prior work on Power Law graphs hint
Page 9 and 10: Is shrinking diameter just j a cons
Page 11 and 12: [Leskovec et al. TKDD 07] How does
Page 13 and 14: [Leskovec et al. TKDD 07] Densific
Page 15 and 16: Let Let’s s assume the community
Page 17 and 18: n=2k n = 2 nodes reside in the lea
Page 19 and 20: What is expected out‐degree out d
Page 21 and 22: Claim: The Community Guided Attachm
Page 23 and 24: [Leskovec et al. TKDD 07] Communit
Page 25 and 26: Expected degree of a node at height
Page 27 and 28: f ( x) Properties: 1 2 2 1 x e (
Page 29 and 30: Question: Is this distribution logn
Page 31 and 32: Claim: If F t is taken from a logno
Page 33: Consider continuous version of logn
Page 37 and 38: Mandelbrot experiment: design a lan
Page 39 and 40: Each j letter word has frequency (c

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