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Table 1 Considered real-world networks

From: Node-weighted centrality: a new way of centrality hybridization

Instance name n m Avg. deg. Density \(\hat{C}\) Assortativity (D) Max clique Network type
Chicago Road [36] 1467 1298 1.7696 0.0012 0.0001 \(-\) 0.5049 2 Transport network
Chilean Power Grid [38] 347 444 2.5591 0.0074 0.0865 \(-\) 0.0773 4 Energy network
Euroroad [36] 1174 1417 2.414 0.0021 0.0167 0.1267 3 Transport network
London Metro [34] 266 308 2.3158 0.0087 0.0363 0.1531 3 Transport network
Madrid Metro [34] 209 240 2.2967 0.011 0.0056 0.1776 3 Transport network
Mexico Metro [34] 147 164 2.2313 0.0153 0.0034 \(-\) 0.1105 3 Transport network
Minnesota Road [31] 2642 3303 2.5004 0.0009 0.016 \(-\) 0.1848 3 Transport network
Moscow Metro [34] 134 156 2.3284 0.0175 0.0174 0.4492 3 Transport network
New York Metro [34] 433 475 2.194 0.0051 0.0173 \(-\) 0.0297 3 Transport network
Oldenburg Road [32] 6105 7029 2.3027 0.0004 0.0108 0.0554 3 Transport network
Openflights [34] 2939 15677 10.6683 0.0036 0.4526 0.0509 22 Transport network
Osaka Metro [34] 108 123 2.2778 0.0213 0.0001 0.1965 2 Transport network
p2p-Gnutella08 [37] 6301 20777 6.5948 0.001 0.0109 0.0356 5 Internet peer-to-peer network
Paris Metro [34] 299 356 2.3813 0.008 0.0204 \(-\) 0.0297 3 Transport network
as20000102 [37] 6474 13895 4.2926 0.0007 0.2522 \(-\) 0.1704 10 Autonomous systems graph
Seoul Metro [34] 392 437 2.2296 0.0057 0.006 0.0313 3 Transport network
Shanghai Metro [34] 148 158 2.1351 0.0145 0.0029 \(-\) 0.0318 3 Transport network
Tokyo Metro [34] 217 262 2.4147 0.0112 0.0237 0.1983 3 Transport network
US Air [35] 332 2126 12.8072 0.0387 0.6252 \(-\) 0.2079 22 Transport network
US Power Grid [39] 4941 6594 2.6691 0.0005 0.0801 0.0035 6 Energy network
NRPG data [33] 246 373 3.0325 0.0124 0.1071 \(-\) 0.0932 3 Energy network