Finding community structure in directed networks
We consider the problem of finding communities or modules in directed networks. In the past, the most common approach to this problem has been to ignore edge direction and apply methods developed for community discovery in undirected networks, but this approach discards potentially useful informatio...
| Główni autorzy: | , |
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| Format: | Journal article |
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2008
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| _version_ | 1826276516231643136 |
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| author | Leicht, E Newman, M |
| author_facet | Leicht, E Newman, M |
| author_sort | Leicht, E |
| collection | OXFORD |
| description | We consider the problem of finding communities or modules in directed networks. In the past, the most common approach to this problem has been to ignore edge direction and apply methods developed for community discovery in undirected networks, but this approach discards potentially useful information contained in the edge directions. Here we show how the widely used community finding technique of modularity maximization can be generalized in a principled fashion to incorporate information contained in edge directions. We describe an explicit algorithm based on spectral optimization of the modularity and show that it gives demonstrably better results than previous methods on a variety of test networks, both real and computer generated. |
| first_indexed | 2024-03-06T23:15:08Z |
| format | Journal article |
| id | oxford-uuid:66df40c3-1c85-445e-aefe-56e55cac1623 |
| institution | University of Oxford |
| last_indexed | 2024-03-06T23:15:08Z |
| publishDate | 2008 |
| record_format | dspace |
| spelling | oxford-uuid:66df40c3-1c85-445e-aefe-56e55cac16232022-03-26T18:34:35ZFinding community structure in directed networksJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:66df40c3-1c85-445e-aefe-56e55cac1623Saïd Business School - Eureka2008Leicht, ENewman, MWe consider the problem of finding communities or modules in directed networks. In the past, the most common approach to this problem has been to ignore edge direction and apply methods developed for community discovery in undirected networks, but this approach discards potentially useful information contained in the edge directions. Here we show how the widely used community finding technique of modularity maximization can be generalized in a principled fashion to incorporate information contained in edge directions. We describe an explicit algorithm based on spectral optimization of the modularity and show that it gives demonstrably better results than previous methods on a variety of test networks, both real and computer generated. |
| spellingShingle | Leicht, E Newman, M Finding community structure in directed networks |
| title | Finding community structure in directed networks |
| title_full | Finding community structure in directed networks |
| title_fullStr | Finding community structure in directed networks |
| title_full_unstemmed | Finding community structure in directed networks |
| title_short | Finding community structure in directed networks |
| title_sort | finding community structure in directed networks |
| work_keys_str_mv | AT leichte findingcommunitystructureindirectednetworks AT newmanm findingcommunitystructureindirectednetworks |