Minimum spanning trees for community detection |
| |
Authors: | Jianshe Wu Xiaoxiao Li Licheng Jiao Xiaohua Wang Bo Sun |
| |
Affiliation: | 1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi’an 710071, PR China;2. Aeronautical Computing Technique Research Institute, Xi’an 710068, PR China;3. ZTE corporation, PR China |
| |
Abstract: | A simple deterministic algorithm for community detection is provided by using two rounds of minimum spanning trees. By comparing the first round minimum spanning tree (1st-MST) with the second round spanning tree (2nd-MST) of the network, communities are detected and their overlapping nodes are also identified. To generate the two MSTs, a distance matrix is defined and computed from the adjacent matrix of the network. Compared with the resistance matrix or the communicability matrix used in community detection in the literature, the proposed distance matrix is very simple in computation. The proposed algorithm is tested on real world social networks, graphs which are failed by the modularity maximization, and the LFR benchmark graphs for community detection. |
| |
Keywords: | Community structure Minimum spanning tree Distance matrix Complex network |
本文献已被 ScienceDirect 等数据库收录! |
|