The analysis and dissimilarity comparison of community structure
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.
| Year of publication: |
2006
|
|---|---|
| Authors: | Zhang, Peng ; Li, Menghui ; Wu, Jinshan ; Di, Zengru ; Fan, Ying |
| Published in: |
Physica A: Statistical Mechanics and its Applications. - Elsevier, ISSN 0378-4371. - Vol. 367.2006, C, p. 577-585
|
| Publisher: |
Elsevier |
| Subject: | Complex networks | Community structure | Dissimilarity | Weight |
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