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Table 15 Realism results for the Schwimmer Taro Exchange social network

From: Heuristic methods for synthesizing realistic social networks based on personality compatibility

Metrics T \( \overline{F} \) |T- \( \overline{F} \) | L1(F) L2(F) \( \overline{P} \) |T-\( \overline{P} \)| L1(P) L2(P) \( \overline{M} \) |T-\( \overline{M} \)| L1(M) L2(M)
Nodes 22.00 22.00 0.00 0.00 0.00 22.00 0.00 0.00 0.00 22.00 0.00 0.00 0.00
Links 39.00 35.47 3.53 106.0 20.98 39.00 0.00 0.00 0.00 39.00 0.00 0.00 0.00
Components 1.00 1.00 0.00 0.00 0.00 1.30 0.30 9.00 3.32 1.23 0.23 7.00 2.65
Network density 0.17 0.15 0.02 0.46 0.09 0.17 0.00 0.00 0.00 0.17 0.00 0.00 0.00
Average degree 3.55 3.22 0.32 9.64 1.91 3.55 0.00 0.00 0.00 3.55 0.00 0.00 0.00
Standard deviation degree 0.96 0.96 0.00 2.90 0.69 2.65 1.69 50.71 9.33 2.69 1.73 51.78 9.49
Global cluster coefficient 0.28 0.11 0.17 4.99 0.96 0.33 0.06 1.77 0.37 0.32 0.05 1.35 0.29
Average cluster coefficient 0.34 0.11 0.23 6.88 1.30 0.72 0.38 11.43 2.10 0.72 0.38 11.29 2.08
Mean path length 2.49 2.66 0.16 5.03 1.22 2.91 0.42 20.68 6.67 2.78 0.29 18.58 5.91
Communities 5.00 4.97 0.03 17.00 4.58 5.23 0.23 17.00 4.36 5.33 0.33 20.00 5.10
Gini coefficient 0.13 0.20 0.07 2.43 0.53 0.20 0.08 2.29 0.51 0.21 0.08 2.48 0.55
Average betweenness 15.68 17.41 1.73 52.77 12.79 12.95 2.73 81.91 17.33 12.86 2.82 84.64 17.09
Maximum betweenness 46.38 53.76 7.38 319.93 80.14 157.15 110.76 3322.93 613.21 157.83 111.44 3343.28 615.46
Average closeness 0.02 0.02 0.00 0.03 0.01 0.02 0.00 0.09 0.02 0.02 0.00 0.09 0.02
Minimum closeness 0.02 0.01 0.00 0.07 0.02 0.02 0.00 0.03 0.01 0.02 0.00 0.02 0.01
Average eigencentrality 0.62 0.51 0.10 3.08 0.64 0.33 0.29 8.69 1.59 0.33 0.29 8.67 1.58
Minimum eigencentrality 0.32 0.15 0.16 4.92 1.01 0.07 0.24 7.28 1.34 0.08 0.23 7.00 1.28
Network radius 3.00 3.40 0.40 12.00 3.46 2.17 0.83 25.00 5.00 2.20 0.80 24.00 4.90
Average eccentricity 4.09 4.40 0.31 11.14 2.86 3.32 0.77 23.32 4.59 3.32 0.77 23.00 4.45
Network diameter 5.00 5.40 0.40 16.00 4.47 4.17 0.83 25.00 5.00 4.20 0.80 24.00 4.90
  1. Boldfaced numbers indicate which algorithm performed better for a particular metric