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Table 18 Summary of network characteristics

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

Networks NetDep Weak-Prominents (%) Co-liaisonship Avg Embed. CC Modular. Non-zero TwDep neighbors Overlap size Good match
Collaboration astro-ph cond-mat cond-2005 High High High High High High High Middle \(\underset {\text {Louvain}}{\text {Low}}\)
Social artist facebook new sites Low Low* Low* Low Low* Middle* Low Low \(\underset {\text {Louvain}}{\text {Middle}}\)
Communication Brightkite Email-Enron Low Low Low Low Unclear Middle Middle Middle \(\underset {\text {Louvain}}{\text {High}}\)
Technological as-22july06 power Highest Low Low Unclear Low Unclear Middle Unclear \(\underset {\text {Louvain}}{\text {Unclear}}\)
Biological ChCh-Miner PP-Decagon PP-Pathways Yeast Low Low Unclear Low Low Low Lowest High** \(\underset {\text {Louvain}}{\text {Middle}}\)
Ground-truth com-amazon com-dblp High High Middle High Unclear High High Middle \(\underset {\text {ground-truth}}{\text {Highest}}\)
LFR benchmark LFR 20 500 2000 LFR 7 60 4000 Low Low Low High Middle Middle Low Unclear \(\underset {\text {ground-truth}}{\text {High}}\)
  1. * except facebook, ** except Yeast
  2. In the individual columns in the table, there are values of selected parameters of networks that we analyzed. Each value of individual parameters comes from the experiments performed; if ‘unclear’ is listed, the networks are different in this parameter; the value of ‘Non-zero TwIndep neighbors’ represents the proportion of nodes that have at least one neighbor with which they are mutually dependent; ‘Overlap size ’ is estimated based on both maximum and average values.
  3. There is a similarity between collaboration and ground-truth networks; however, this is expected because the com-dblp network is also one of the collaboration networks. Social, communication, and biological networks show further similarity; communication networks are distinguished by a high match of zones with non-overlapping communities, and, on the other hand, large overlaps exist in biological networks. Technological networks and LFR benchmark networks differ from these three network groups; technological networks have a high value of NetDep, the total network dependency; the LFR benchmark networks differ in having high embeddedness value. Anobii and com-youtube networks are not listed because they were not the subject of all experiments