{"title":"通过节点中心性检测网络核心","authors":"Peijie Ma, Xuezao Ren, Jun-fang Zhu, Yanqun Jiang","doi":"10.1088/1674-1056/ad4cd4","DOIUrl":null,"url":null,"abstract":"\n Many networks exhibit the core/periphery structure. Core/periphery structure is a type of meso-scale structure that consists of densely connected core nodes and sparsely connected peripheral nodes. Core nodes tend to be well-connected both among themselves and to peripheral nodes which tend not to be well-connected to other nodes. In this brief report, we propose a new method to detect the core of a network by the centrality of each node. It is discovered that such nodes with the non-negative centrality often consist of the core of the networks. The simulation is carried out on the different real networks. And the results could be checked by the objective function. The checked results may show the effectiveness of the simulation results by the centralities of the nodes on the real networks. Furthermore, we discuss the characters of networks with the single core/periphery structure and point out the scope of the application of our method at the end of this report.","PeriodicalId":504421,"journal":{"name":"Chinese Physics B","volume":"2 9","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detecting the Core of a Network by the Centrality of the Nodes\",\"authors\":\"Peijie Ma, Xuezao Ren, Jun-fang Zhu, Yanqun Jiang\",\"doi\":\"10.1088/1674-1056/ad4cd4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Many networks exhibit the core/periphery structure. Core/periphery structure is a type of meso-scale structure that consists of densely connected core nodes and sparsely connected peripheral nodes. Core nodes tend to be well-connected both among themselves and to peripheral nodes which tend not to be well-connected to other nodes. In this brief report, we propose a new method to detect the core of a network by the centrality of each node. It is discovered that such nodes with the non-negative centrality often consist of the core of the networks. The simulation is carried out on the different real networks. And the results could be checked by the objective function. The checked results may show the effectiveness of the simulation results by the centralities of the nodes on the real networks. Furthermore, we discuss the characters of networks with the single core/periphery structure and point out the scope of the application of our method at the end of this report.\",\"PeriodicalId\":504421,\"journal\":{\"name\":\"Chinese Physics B\",\"volume\":\"2 9\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chinese Physics B\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1088/1674-1056/ad4cd4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chinese Physics B","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/1674-1056/ad4cd4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detecting the Core of a Network by the Centrality of the Nodes
Many networks exhibit the core/periphery structure. Core/periphery structure is a type of meso-scale structure that consists of densely connected core nodes and sparsely connected peripheral nodes. Core nodes tend to be well-connected both among themselves and to peripheral nodes which tend not to be well-connected to other nodes. In this brief report, we propose a new method to detect the core of a network by the centrality of each node. It is discovered that such nodes with the non-negative centrality often consist of the core of the networks. The simulation is carried out on the different real networks. And the results could be checked by the objective function. The checked results may show the effectiveness of the simulation results by the centralities of the nodes on the real networks. Furthermore, we discuss the characters of networks with the single core/periphery structure and point out the scope of the application of our method at the end of this report.