Name
Abstract | ||
|---|---|---|
Community detection has been one of the major topics in complex network research. Recently, several greedy algorithms for networks of millions of nodes have been proposed, but one of their limitations is inconsistency of outcomes [1]. Kwak et al. propose an iterative reinforcing approach to eliminate inconsistency in detected communities. In this paper we delve into structural characteristics of communities identified by Kwak's method with 12 real networks. We find that about 40%of nodes are grouped into communities in an inconsistent way in Orkut and Cyworld. Interestingly, they are only two out of 12 networks whose community size distribution follow power-law. As a first step towards interpretation of communities, we use Guimera and Amaral's method [2]to classify nodes into seven classes based on the z-score and the participation coefficient. Using the z-P analysis, we identify the roles of nodes in Karate and Autonomous System (AS) networks and match them against known roles for evaluation. We apply topological mesoscale information to compare two AS produced by Oliveira et al. [3], and Dhamdhere and Dovrolis [4] We report that even though their AS graphs differ in size, their topological characteristics are very similar. |
Year | Venue | Keywords |
|---|---|---|
2010 | COMSNETS | complex network research,community mining,known role,autonomous system,topological mesoscale information,greedy algorithm,topological mesoscale feature,participation coefficient,community detection,topological characteristic,community size distribution,major topic,greedy algorithms,electronic publishing,encyclopedias,complex network,computer networks,internet,data mining,power law |
Field | DocType | Citations |
Data mining,Graph,Topology,Community mining,Computer science,Computer network,Mesoscale meteorology,Greedy algorithm,Complex network,Encyclopedia,Autonomous system (mathematics),The Internet | Conference | 4 |
PageRank | References | Authors |
0.42 | 15 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sue Moony | 1 | 4 | 0.42 |
| Jinyoung You | 2 | 4 | 0.42 |
| Haewoon Kwak | 3 | 4487 | 267.95 |
| Daniel Kim | 4 | 4 | 0.42 |
| Hawoong Jeong | 5 | 988 | 190.47 |