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Improving community detection in networks by targeted node removal
How a network breaks up into subnetworks or communities is of wide interest. Here we show that vertices connected to many other vertices across a network can disturb the community structures of otherwise ordered networks, introducing noise. We investigate strategies to identify and remove noisy vert...
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| Published in: | Physical review. E, Statistical, nonlinear, and soft matter physics Statistical, nonlinear, and soft matter physics, 2011-01, Vol.83 (1 Pt 2), p.016114-016114, Article 016114 |
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| Main Authors: | , , |
| Format: | Article |
| Language: | English |
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| cited_by | cdi_FETCH-LOGICAL-c346t-8a3e01a60284df72187638ef5ad07e5e521bbdfa192eb26240b015f7641da5153 |
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| cites | cdi_FETCH-LOGICAL-c346t-8a3e01a60284df72187638ef5ad07e5e521bbdfa192eb26240b015f7641da5153 |
| container_end_page | 016114 |
| container_issue | 1 Pt 2 |
| container_start_page | 016114 |
| container_title | Physical review. E, Statistical, nonlinear, and soft matter physics |
| container_volume | 83 |
| creator | Wen, Haoran Leicht, E A D'Souza, Raissa M |
| description | How a network breaks up into subnetworks or communities is of wide interest. Here we show that vertices connected to many other vertices across a network can disturb the community structures of otherwise ordered networks, introducing noise. We investigate strategies to identify and remove noisy vertices ("violators") and develop a quantitative approach using statistical breakpoints to identify when the largest enhancement to a modularity measure is achieved. We show that removing nodes thus identified reduces noise in detected community structures for a range of different types of real networks in software systems and in biological systems. |
| doi_str_mv | 10.1103/PhysRevE.83.016114 |
| format | article |
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| source | American Physical Society:Jisc Collections:APS Read and Publish 2023-2025 (reading list) |
| title | Improving community detection in networks by targeted node removal |
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