Tail-scope : using friends to estimate heavy tails of degree distributions in large-scale complex networks
Eom, Young-Ho and Jo, Hang-Hyun (2015) Tail-scope : using friends to estimate heavy tails of degree distributions in large-scale complex networks. Scientific Reports, 5. pp. 1-9. 09752. ISSN 2045-2322 (https://doi.org/10.1038/srep09752)
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Abstract
Many complex networks in natural and social phenomena have often been characterized by heavy-tailed degree distributions. However, due to rapidly growing size of network data and concerns on privacy issues about using these data, it becomes more difficult to analyze complete data sets. Thus, it is crucial to devise effective and efficient estimation methods for heavy tails of degree distributions in large-scale networks only using local information of a small fraction of sampled nodes. Here we propose a tail-scope method based on local observational bias of the friendship paradox. We show that the tail-scope method outperforms the uniform node sampling for estimating heavy tails of degree distributions, while the opposite tendency is observed in the range of small degrees. In order to take advantages of both sampling methods, we devise the hybrid method that successfully recovers the whole range of degree distributions. Our tail-scope method shows how structural heterogeneities of large-scale complex networks can be used to effectively reveal the network structure only with limited local information.
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Item type: Article ID code: 60279 Dates: DateEvent11 May 2015Published13 March 2015AcceptedSubjects: Science > Mathematics Department: Faculty of Science > Mathematics and Statistics Depositing user: Pure Administrator Date deposited: 24 Mar 2017 12:00 Last modified: 30 Sep 2024 15:07 URI: https://strathprints.strath.ac.uk/id/eprint/60279