Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic Space
Community detection and structural hole spanner (the node bridging different communities) identification, revealing the mesoscopic and microscopic structural properties of complex networks, have drawn much attention in recent years. As the determinant of mesoscopic structure, communities and structu...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/24/7/894 |
| _version_ | 1797439607142350848 |
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| author | Qi Nie Hao Jiang Si-Dong Zhong Qiang Wang Juan-Juan Wang Hao Wang Li-Hua Wu |
| author_facet | Qi Nie Hao Jiang Si-Dong Zhong Qiang Wang Juan-Juan Wang Hao Wang Li-Hua Wu |
| author_sort | Qi Nie |
| collection | DOAJ |
| description | Community detection and structural hole spanner (the node bridging different communities) identification, revealing the mesoscopic and microscopic structural properties of complex networks, have drawn much attention in recent years. As the determinant of mesoscopic structure, communities and structural hole spanners discover the clustering and hierarchy of networks, which has a key impact on transmission phenomena such as epidemic transmission, information diffusion, etc. However, most existing studies address the two tasks independently, which ignores the structural correlation between mesoscale and microscale and suffers from high computational costs. In this article, we propose an algorithm for simultaneously detecting communities and structural hole spanners via hyperbolic embedding (SDHE). Specifically, we first embed networks into a hyperbolic plane, in which, the angular distribution of the nodes reveals community structures of the embedded network. Then, we analyze the critical gap to detect communities and the angular region where structural hole spanners may exist. Finally, we identify structural hole spanners via two-step connectivity. Experimental results on synthetic networks and real networks demonstrate the effectiveness of our proposed algorithm compared with several state-of-the-art methods. |
| first_indexed | 2024-03-09T11:56:32Z |
| format | Article |
| id | doaj.art-5dafef582f20459080d237f919c86770 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T11:56:32Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-5dafef582f20459080d237f919c867702023-11-30T23:08:48ZengMDPI AGEntropy1099-43002022-06-0124789410.3390/e24070894Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic SpaceQi Nie0Hao Jiang1Si-Dong Zhong2Qiang Wang3Juan-Juan Wang4Hao Wang5Li-Hua Wu6Electronic Information School, Wuhan University, Wuhan 430072, ChinaElectronic Information School, Wuhan University, Wuhan 430072, ChinaElectronic Information School, Wuhan University, Wuhan 430072, ChinaElectronic Information School, Wuhan University, Wuhan 430072, ChinaSchool of Business Administration, Zhongnan University of Economics and Law, Wuhan 430073, ChinaWuhan Second Ship Design and Research Institute, Wuhan 430064, ChinaWuhan Second Ship Design and Research Institute, Wuhan 430064, ChinaCommunity detection and structural hole spanner (the node bridging different communities) identification, revealing the mesoscopic and microscopic structural properties of complex networks, have drawn much attention in recent years. As the determinant of mesoscopic structure, communities and structural hole spanners discover the clustering and hierarchy of networks, which has a key impact on transmission phenomena such as epidemic transmission, information diffusion, etc. However, most existing studies address the two tasks independently, which ignores the structural correlation between mesoscale and microscale and suffers from high computational costs. In this article, we propose an algorithm for simultaneously detecting communities and structural hole spanners via hyperbolic embedding (SDHE). Specifically, we first embed networks into a hyperbolic plane, in which, the angular distribution of the nodes reveals community structures of the embedded network. Then, we analyze the critical gap to detect communities and the angular region where structural hole spanners may exist. Finally, we identify structural hole spanners via two-step connectivity. Experimental results on synthetic networks and real networks demonstrate the effectiveness of our proposed algorithm compared with several state-of-the-art methods.https://www.mdpi.com/1099-4300/24/7/894complex networkshyperbolic embeddingcommunity detectionstructural hole spanner |
| spellingShingle | Qi Nie Hao Jiang Si-Dong Zhong Qiang Wang Juan-Juan Wang Hao Wang Li-Hua Wu Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic Space Entropy complex networks hyperbolic embedding community detection structural hole spanner |
| title | Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic Space |
| title_full | Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic Space |
| title_fullStr | Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic Space |
| title_full_unstemmed | Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic Space |
| title_short | Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic Space |
| title_sort | joint detection of community and structural hole spanner of networks in hyperbolic space |
| topic | complex networks hyperbolic embedding community detection structural hole spanner |
| url | https://www.mdpi.com/1099-4300/24/7/894 |
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