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Table 12 Node dependencies and network dependency in real-world networks

From: Ego-zones: non-symmetric dependencies reveal network groups with large and dense overlaps

Network OwDep OwIndep TwDep TwIndep NetDep
  Max Avg Max Avg Max Avg Max Avg  
artist 16 0.308 41 0.308 8 0.019 1463 31.795 0.020
as-22july06 12 1.399 2024 1.399 3 0.038 503 1.383 0.672
astro-ph 55 3.256 136 3.256 30 1.414 239 8.193 0.492
Brightkite 31 0.857 245 0.857 7 0.130 1027 5.661 0.246
com-amazon 6 1.221 348 1.221 6 0.281 201 2.806 0.493
com-dblp 75 1.602 112 1.602 39 0.882 237 2.536 0.617
cond-mat 15 1.648 53 1.648 9 0.686 79 2.456 0.619
cond-2005 24 2.024 83 2.024 15 0.595 228 4.777 0.493
email-Enron 10 1.575 1319 1.575 7 0.426 870 7.155 0.333
facebook 26 1.959 1001 1.959 12 0.236 290 39.536 0.095
ChCh-Miner 16 1.053 62 1.053 3 0.021 432 62.127 0.033
new_sites 27 0.793 107 0.793 13 0.128 672 13.042 0.116
power 4 0.711 12 0.711 3 0.340 10 0.906 0.661
PP-Decagon 180 0.572 267 0.572 16 0.040 2426 73.886 0.016
PP-Pathways 80 0.485 584 0.485 7 0.007 1950 30.493 0.031
Yeast 6 0.819 24 0.819 2 0.040 56 4.265 0.282
LFR 20 500 2000 16 1.215 63 1.215 6 0.054 194 17.927 0.122
LFR 7 60 4000 10 1.207 42 1.207 3 0.111 74 3.927 0.391
  1. Biological networks, social networks, and communication networks have a low NetDep value. The technological networks have a low average TwIndep compared to the other networks; in both of technological networks, there is the highest NetDep value. Thus, the highest dependencies were found in the technological networks