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Table 11 Properties of real-world networks

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

Network n m Degree CC Strong-prominents Weak-prominents Modularity
    Max Avg   Total Percent Total Percent  
artist 50515 819090 1469 32.438 0.137 8755 17.3 325 0.6 0.604
as-22july06 22963 48436 2390 4.218 0.230 2416 10.5 363 1.5 0.663
astro-ph 14845 119652 360 16.120 0.669 3291 22.1 3473 23.3 0.755
Brightkite 56739 212945 1134 15.012 0.173 14297 25.1 1961 3.4 0.660
com-amazon 334863 925872 549 5.529 0.396 75603 22.5 43161 12.8 0.926
com-dblp 317080 1049866 343 6.622 0.632 65090 20.5 29139 9.1 0.810
cond-mat 13861 44619 107 6.438 0.651 2241 16.1 3315 23.9 0.862
cond-2005 36458 171735 278 9.420 0.656 6372 17.4 8904 24.4 0.786
email-Enron 33696 180811 1383 21.463 0.509 5180 15.3 2591 7.6 0.584
facebook 4039 88234 1045 43.691 0.605 61 1.5 1242 30.7 0.835
ChCh-Miner 1510 48512 443 64.254 0.304 197 13.0 48 3.1 0.392
new_sites 27917 205964 678 14.776 0.294 7276 26.0 1588 5.6 0.611
power 4941 6594 19 2.669 0.080 1494 30.2 144 2.9 0.935
PP-Decagon 19065 715602 251 75.069 0.233 3500 18.3 147 0.7 0.445
PP-Pathways 21521 338625 213 31.812 0.124 3492 16.2 46 0.2 0.386
Yeast 2224 6609 64 6.339 0.125 563 25.3 38 1.7 0.587
LFR 20 500 2000 10000 102054 200 20.411 0.399 1499 15.0 225 2.3 0.659
LFR 7 60 4000 10000 32262 99 6.452 0.349 2280 22.8 472 4.7 0.578
  1. The collaboration networks and networks with ground-truth communities differ from others (except facebook) in weakly-prominent nodes. For networks of these two types, there is a higher percentage of weakly-prominent nodes than for other networks. Biological networks, social networks (except facebook), and communication networks have a lower clustering coefficient