Tail-scope

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Eom, Young Ho
dc.contributor.author Jo, Hang Hyun
dc.date.accessioned 2017-03-23T12:49:41Z
dc.date.available 2017-03-23T12:49:41Z
dc.date.issued 2015-05-11
dc.identifier.citation Eom , Y H & Jo , H H 2015 , ' Tail-scope : Using friends to estimate heavy tails of degree distributions in large-scale complex networks ' Scientific Reports , vol 5 , 09752 . DOI: 10.1038/srep09752 en
dc.identifier.issn 2045-2322
dc.identifier.other PURE UUID: e3da3577-8ce2-469a-b2d8-b45a1156a4d9
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/tailscope(e3da3577-8ce2-469a-b2d8-b45a1156a4d9).html
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=84929152983&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/12913009/srep09752.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/24955
dc.description.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 networkscan be used to effectively reveal the network structure only with limited local information. en
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries Scientific Reports en
dc.relation.ispartofseries Volume 5 en
dc.rights openAccess en
dc.subject.other General en
dc.subject.other 113 Computer and information sciences en
dc.title Tail-scope en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Universite de Toulouse
dc.contributor.department Department of Neuroscience and Biomedical Engineering
dc.subject.keyword General
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201703233198
dc.identifier.doi 10.1038/srep09752


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