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Table 1 Graph properties of the real network datasets

From: The risk of node re-identification in labeled social graphs

Network |N| |E| p τ \(\hspace {-2pt}\bar {d}\) C r κ
  R(%) B(%) RR(%) BB(%) RB(%)       
polblogs 1224 16718    0.02 0.22 −0.22 2.49
(party) 48 52 44 48 8 0.48 0.84     
fb-caltech 769 16656    0.05 0.29 −0.06 1.33
(gender) 91.5 8.5 92.8 0.2 7 0.08 0.52     
(occupation) 72 28 69 8 23 0.28 0.42     
fb-dartmouth 7694 304076    0.01 0.15 0.04 2.76
(gender) 86.5 13.5 83.2 0.9 15.9 0.14 0.34     
(occupation) 62 38 58 18 24 0.38 0.5     
fb-michigan 30147 1176516    0.0026 0.13 0.115 3.05
(gender) 92.2 7.8 90.5 0.2 9.3 0.08 0.37     
(occupation) 77.5 22.5 72 9 19 0.22 0.46     
pokec-1 265388 700352 0.46 0 2×10−5 0.0068 −0.044 5.66
(gender) 46 54 18.6 22.4 59       
amazon-products 303551 835326 0.18 0.99 1.8×10−5 0.21 −0.06 17.42
(category) 82 18 83.4 16.4 0.2       
  1. All graphs are undirected, and nodes are annotated with a binary valued attribute. E.g., nodes in the polblogs network have the attribute party with values; conservative and liberal. For simplicity, binary values are presented using the notation of R and B, together with the distributions of such values over nodes and edges. p and τ present the estimated parameter values of the attraction model. Density \((\bar {d})\) is the fraction of all possible edges, transitivity (C) is the fraction of triangles of all possible triangle in the network. degree-assortativity (r) measures the similarity of relations depending on the associated node degree. Average path length (κ) depicts the average shortest path length between any pairs of nodes
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