Estimating the Number of Communities in Weighted Networks
Community detection in weighted networks has been a popular topic in recent years. However, while there exist several flexible methods for estimating communities in weighted networks, these methods usually assume that the number of communities is known. It is usually unclear how to determine the exa...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
|
| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/25/4/551 |
| _version_ | 1827745142147121152 |
|---|---|
| author | Huan Qing |
| author_facet | Huan Qing |
| author_sort | Huan Qing |
| collection | DOAJ |
| description | Community detection in weighted networks has been a popular topic in recent years. However, while there exist several flexible methods for estimating communities in weighted networks, these methods usually assume that the number of communities is known. It is usually unclear how to determine the exact number of communities one should use. Here, to estimate the number of communities for weighted networks generated from arbitrary distribution under the degree-corrected distribution-free model, we propose one approach that combines weighted modularity with spectral clustering. This approach allows a weighted network to have negative edge weights and it also works for signed networks. We compare the proposed method to several existing methods and show that our method is more accurate for estimating the number of communities both numerically and empirically. |
| first_indexed | 2024-03-11T05:02:57Z |
| format | Article |
| id | doaj.art-464171b95b20425fb4a6c1140b0482c5 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-11T05:02:57Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-464171b95b20425fb4a6c1140b0482c52023-11-17T19:07:41ZengMDPI AGEntropy1099-43002023-03-0125455110.3390/e25040551Estimating the Number of Communities in Weighted NetworksHuan Qing0School of Mathematics, China University of Mining and Technology, Xuzhou 221116, ChinaCommunity detection in weighted networks has been a popular topic in recent years. However, while there exist several flexible methods for estimating communities in weighted networks, these methods usually assume that the number of communities is known. It is usually unclear how to determine the exact number of communities one should use. Here, to estimate the number of communities for weighted networks generated from arbitrary distribution under the degree-corrected distribution-free model, we propose one approach that combines weighted modularity with spectral clustering. This approach allows a weighted network to have negative edge weights and it also works for signed networks. We compare the proposed method to several existing methods and show that our method is more accurate for estimating the number of communities both numerically and empirically.https://www.mdpi.com/1099-4300/25/4/551community detectiondegree-corrected distribution-free modelweighted modularitynetwork analysis |
| spellingShingle | Huan Qing Estimating the Number of Communities in Weighted Networks Entropy community detection degree-corrected distribution-free model weighted modularity network analysis |
| title | Estimating the Number of Communities in Weighted Networks |
| title_full | Estimating the Number of Communities in Weighted Networks |
| title_fullStr | Estimating the Number of Communities in Weighted Networks |
| title_full_unstemmed | Estimating the Number of Communities in Weighted Networks |
| title_short | Estimating the Number of Communities in Weighted Networks |
| title_sort | estimating the number of communities in weighted networks |
| topic | community detection degree-corrected distribution-free model weighted modularity network analysis |
| url | https://www.mdpi.com/1099-4300/25/4/551 |
| work_keys_str_mv | AT huanqing estimatingthenumberofcommunitiesinweightednetworks |