On neighbourhood degree sequences of complex networks
Smith, Keith M. (2019) On neighbourhood degree sequences of complex networks. Scientific Reports, 9 (1). pp. 1-11. 8340. ISSN 2045-2322 (https://doi.org/10.1038/s41598-019-44907-8)
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Abstract
Network topology is a fundamental aspect of network science that allows us to gather insights into the complicated relational architectures of the world we inhabit. We provide a first specific study of neighbourhood degree sequences in complex networks. We consider how to explicitly characterise important physical concepts such as similarity, heterogeneity and organization in these sequences, as well as updating the notion of hierarchical complexity to reflect previously unnoticed organizational principles. We also point out that neighbourhood degree sequences are related to a powerful subtree kernel for unlabeled graph classification. We study these newly defined sequence properties in a comprehensive array of graph models and over 200 real-world networks. We find that these indices are neither highly correlated with each other nor with classical network indices. Importantly, the sequences of a wide variety of real world networks are found to have greater similarity and organisation than is expected for networks of their given degree distributions. Notably, while biological, social and technological networks all showed consistently large neighbourhood similarity and organisation, hierarchical complexity was not a consistent feature of real world networks. Neighbourhood degree sequences are an interesting tool for describing unique and important characteristics of complex networks.
ORCID iDs
Smith, Keith M. ORCID: https://orcid.org/0000-0002-4615-9020;-
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Item type: Article ID code: 87347 Dates: DateEvent1 December 2019Published6 June 2019Published Online28 May 2019Accepted25 February 2019SubmittedNotes: Funding Information: We would like to thank Aaron Clauset for helpful discussions and provision of the data from the Colorado Index of Complex Networks. This work was supported by Health Data Research UK (MRC ref Mr/S004122/1), which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, National Institute for Health Research (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome. A version of this article has been made available on an online preprint server at https://arxiv.org/abs/1901.02353. Publisher Copyright: © 2019, The Author(s). Smith, K.M. On neighbourhood degree sequences of complex networks. Sci Rep 9, 8340 (2019). https://doi.org/10.1038/s41598-019-44907-8 Subjects: Science > Mathematics > Electronic computers. Computer science Department: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 16 Nov 2023 11:33 Last modified: 11 Nov 2024 14:08 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/87347