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Table 6 Realism results for the Bernard & Killwork Technical 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 34.00 34.00 0.00 0.00 0.00 34.00 0.00 0.00 0.00 34.00 0.00 0.00 0.00
Links 175.00 143.63 31.37 941.00 173.03 175.00 0.00 0.00 0.00 175.00 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 0.26 0.06 1.68 0.31 0.31 0.00 0.00 0.00 0.31 0.00 0.00 0.00
Average degree 10.29 8.45 1.85 55.35 10.18 10.29 0.00 0.00 0.00 10.29 0.00 0.00 0.00
Standard deviation degree 4.63 3.55 1.08 32.41 5.97 5.03 0.40 12.12 2.45 5.00 0.37 11.02 2.31
Global cluster coefficient 0.48 0.30 0.17 5.17 0.95 0.44 0.03 0.98 0.20 0.45 0.03 0.77 0.16
Average cluster coefficient 0.47 0.32 0.16 4.76 0.88 0.53 0.05 1.61 0.32 0.53 0.06 1.69 0.33
Mean path length 1.81 1.90 0.09 2.70 0.52 1.77 0.04 1.08 0.21 1.78 0.03 0.95 0.19
Communities 4.00 6.37 2.37 75.00 16.82 7.37 3.37 103.00 21.10 6.50 2.50 77.00 16.70
Gini coefficient 0.49 0.49 0.01 1.42 0.31 0.50 0.02 1.18 0.27 0.51 0.02 1.49 0.32
Average betweenness 13.32 14.81 1.48 44.53 8.51 12.75 0.58 17.74 3.49 12.81 0.52 15.74 3.17
Maximum betweenness 63.29 53.03 10.26 368.03 75.25 104.94 41.65 1249.56 238.61 102.52 39.23 1176.86 229.79
Average closeness 0.02 0.02 0.00 0.03 0.01 0.02 0.00 0.01 0.00 0.02 0.00 0.01 0.00
Minimum closeness 0.01 0.01 0.00 0.03 0.01 0.01 0.00 0.02 0.00 0.01 0.00 0.02 0.00
Average eigencentrality 0.53 0.59 0.06 1.82 0.38 0.50 0.03 1.32 0.27 0.49 0.04 1.38 0.30
Minimum eigencentrality 0.06 0.06 0.00 0.44 0.10 0.07 0.01 0.46 0.10 0.07 0.01 0.45 0.10
Network radius 2.00 2.13 0.13 4.00 2.00 2.00 0.00 0.00 0.00 2.00 0.00 0.00 0.00
Average eccentricity 2.88 3.08 0.19 5.79 1.33 2.79 0.09 3.74 0.85 2.80 0.08 3.68 0.80
Network diameter 4.00 3.97 0.03 3.00 1.73 3.47 0.53 16.00 4.00 3.47 0.53 16.00 4.00
  1. Boldfaced numbers indicate which algorithm performed better for a particular metric