An evolving network model with community structure
Many social and biological networks consist of communities—groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this...
| Main Authors: | , |
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| Format: | Journal article |
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2005
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| _version_ | 1797095144699199488 |
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| author | Li, C Maini, P |
| author_facet | Li, C Maini, P |
| author_sort | Li, C |
| collection | OXFORD |
| description | Many social and biological networks consist of communities—groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties. |
| first_indexed | 2024-03-07T04:23:43Z |
| format | Journal article |
| id | oxford-uuid:cbe8ac77-8703-484e-8cad-70ef48a2c5d0 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T04:23:43Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | oxford-uuid:cbe8ac77-8703-484e-8cad-70ef48a2c5d02022-03-27T07:18:06ZAn evolving network model with community structureJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:cbe8ac77-8703-484e-8cad-70ef48a2c5d0Mathematical Institute - ePrints2005Li, CMaini, PMany social and biological networks consist of communities—groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties. |
| spellingShingle | Li, C Maini, P An evolving network model with community structure |
| title | An evolving network model with community structure |
| title_full | An evolving network model with community structure |
| title_fullStr | An evolving network model with community structure |
| title_full_unstemmed | An evolving network model with community structure |
| title_short | An evolving network model with community structure |
| title_sort | evolving network model with community structure |
| work_keys_str_mv | AT lic anevolvingnetworkmodelwithcommunitystructure AT mainip anevolvingnetworkmodelwithcommunitystructure AT lic evolvingnetworkmodelwithcommunitystructure AT mainip evolvingnetworkmodelwithcommunitystructure |