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Table 13 Realism results for the Krackhardt Office CSS 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 21.00 21.00 0.00 0.00 0.00 21.00 0.00 0.00 0.00 21.00 0.00 0.00 0.00
Links 14.00 12.50 1.50 45.00 9.75 14.00 0.00 0.00 0.00 14.00 0.00 0.00 0.00
Components 9.00 9.43 0.43 17.00 4.58 9.13 0.13 4.00 2.00 9.17 0.17 5.00 2.24
Network density 0.07 0.06 0.01 0.21 0.05 0.07 0.00 0.00 0.00 0.07 0.00 0.00 0.00
Average degree 1.33 1.19 0.14 4.29 0.93 1.33 0.00 0.00 0.00 1.33 0.00 0.00 0.00
Standard deviation degree 1.39 1.18 0.21 6.23 1.38 2.08 0.69 20.55 3.93 2.11 0.72 21.70 4.06
Global cluster coefficient 0.13 0.08 0.05 2.91 0.60 0.14 0.01 0.69 0.14 0.13 0.01 0.59 0.13
Average cluster coefficient 0.16 0.11 0.05 3.80 0.76 0.68 0.53 15.78 2.90 0.70 0.55 16.38 3.01
Mean path length 15.84 16.45 0.61 41.12 8.83 14.37 1.48 44.27 8.77 14.53 1.31 41.18 8.38
Communities 10.00 11.33 1.33 40.00 8.72 10.47 0.47 14.00 3.74 10.50 0.50 17.00 4.36
Gini coefficient 0.40 0.33 0.07 2.04 0.43 0.42 0.02 0.77 0.17 0.42 0.02 0.80 0.18
Average betweenness 3.67 3.86 0.20 53.33 12.11 3.90 0.23 27.43 5.73 3.51 0.16 22.48 5.23
Maximum betweenness 22.50 25.14 2.64 315.33 71.60 55.97 33.47 1004.0 186.61 54.70 32.20 966.0 182.25
Average closeness 0.04 0.06 0.01 0.66 0.24 0.04 0.00 0.17 0.04 0.05 0.00 0.17 0.05
Minimum closeness 0.03 0.04 0.01 0.52 0.19 0.04 0.00 0.18 0.05 0.04 0.01 0.21 0.06
Average eigencentrality 0.47 0.52 0.05 2.33 0.56 0.39 0.08 2.36 0.45 0.39 0.09 2.54 0.48
Minimum eigencentrality 0.11 0.17 0.07 2.62 0.64 0.25 0.14 4.30 0.82 0.25 0.14 4.19 0.81
Network radius 3.00 2.87 0.13 14.00 4.00 1.83 1.17 35.00 6.71 1.83 1.17 35.00 6.71
Average eccentricity 2.33 2.41 0.08 13.00 3.07 1.77 0.57 17.05 3.68 1.66 0.67 20.10 3.99
Network diameter 5.00 5.20 0.20 26.00 6.16 3.20 1.80 54.00 10.58 3.00 2.00 60.00 11.40
  1. Boldfaced numbers indicate which algorithm performed better for a particular metric