Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
977454 | Physica A: Statistical Mechanics and its Applications | 2006 | 9 Pages |
Abstract
Based on a database of collaboration recording in econophysics scientists and other networks, hierarchical clustering method and the algorithm of Girvan and Newman are applied to detect their community structure. The interesting results for community structure of econophysicists collaboration network are shown. A dissimilarity function D is proposed to quantitatively measure the difference between community structures obtained by different methods. Using this measurement, the differences between the process and community results obtained by aforementioned algorithms are given. The effectiveness of hierarchical clustering method and GN algorithm for detecting community structure in various networks is discussed.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Peng Zhang, Menghui Li, Jinshan Wu, Zengru Di, Ying Fan,