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Table 19 Realism results for the Bernard & Killworth Office 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 40.00 40.00 0.00 0.00 0.00 40.00 0.00 0.00 0.00 40.00 0.00 0.00 0.00
Links 238.00 197.60 40.40 1212.00 223.29 238.00 0.00 0.00 0.00 238.00 0.00 0.00 0.00
Components 1.00 1.00 0.00 0.00 0.00 1.00 0.00 0.00 0.00 1.00 0.00 0.00 0.00
Network density 0.31 0.25 0.05 1.55 0.29 0.31 0.00 0.00 0.00 0.31 0.00 0.00 0.00
Average degree 11.90 9.88 2.02 60.60 11.16 11.90 0.00 0.00 0.00 11.90 0.00 0.00 0.00
Standard deviation degree 4.48 3.39 1.09 32.72 6.03 5.11 0.63 19.40 3.83 5.05 0.57 17.59 3.61
Global cluster coefficient 0.41 0.27 0.14 4.08 0.75 0.41 0.00 0.30 0.06 0.42 0.01 0.34 0.08
Average cluster coefficient 0.43 0.28 0.15 4.58 0.84 0.46 0.03 0.96 0.20 0.46 0.03 0.87 0.19
Mean path length 1.76 1.83 0.06 1.93 0.36 1.73 0.03 0.96 0.19 1.74 0.03 0.84 0.17
Communities 4.00 5.50 1.50 55.00 12.12 4.80 0.80 42.00 10.86 5.13 1.13 54.00 13.64
Gini coefficient 0.35 0.36 0.01 1.51 0.35 0.32 0.03 2.42 0.60 0.34 0.01 2.75 0.60
Average betweenness 14.90 16.15 1.25 37.63 7.10 14.28 0.62 18.70 3.65 14.41 0.49 16.45 3.26
Maximum betweenness 46.13 47.39 1.27 188.93 42.15 124.58 78.46 2353.65 456.14 118.82 72.69 2183.96 439.83
Average closeness 0.02 0.01 0.00 0.02 0.00 0.02 0.00 0.01 0.00 0.02 0.00 0.01 0.00
Minimum closeness 0.01 0.01 0.00 0.02 0.00 0.01 0.00 0.04 0.01 0.01 0.00 0.04 0.01
Average eigencentrality 0.58 0.60 0.02 0.87 0.20 0.45 0.13 3.97 0.76 0.45 0.13 3.93 0.76
Minimum eigencentrality 0.12 0.15 0.03 1.17 0.24 0.11 0.01 0.56 0.13 0.10 0.02 0.81 0.19
Network radius 2.00 2.00 0.00 0.00 0.00 2.00 0.00 0.00 0.00 2.00 0.00 0.00 0.00
Average eccentricity 2.83 2.84 0.02 1.50 0.39 2.53 0.29 8.88 1.76 2.59 0.24 7.10 1.48
Network diameter 4.00 3.07 0.93 28.00 5.29 3.03 0.97 29.00 5.39 3.00 1.00 30.00 5.48
  1. Boldfaced numbers indicate which algorithm performed better for a particular metric