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dc.contributor.authorThedchanamoorthy, G-
dc.contributor.authorPiraveenan, M-
dc.contributor.authorKasthurirathna, D-
dc.date.accessioned2022-02-09T06:47:48Z-
dc.date.available2022-02-09T06:47:48Z-
dc.date.issued2013-08-25-
dc.identifier.citationG. Thedchanamoorthy, M. Piraveenan and D. Kasthurirathna, "Standard deviations of degree differences as indicators of mixing patterns in complex networks," 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013), 2013, pp. 1202-1208, doi: 10.1145/2492517.2500265.en_US
dc.identifier.isbn978-1-4503-2240-9-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1060-
dc.description.abstractMixing patterns in social networks can give us important clues about the structure and functionality of these networks. In the past, a number of measures including variants of assortativity have been used to quantify degree mixing patterns of networks. In this paper, we are interested in observing the heterogeneity of the neighbourhood of nodes in networks. For this purpose, we use the standard deviation of degree differences between a node and its neighbours. We call this measure the `versatility' of a node. We apply this measure on synthetic and real world networks. We find that among real world networks three classes emerge -(i) Networks where the versatility converges to non-zero values with node degree (ii) Networks where the versatility converges to zero with node degree (iii) Networks where versatility does not converge with node degree. We find that there may be some correlation between this and network density, and the geographical / anatomical nature of networks may also be a factor. We also note that versatility could be applicable to any quantifiable network property, and not just node degree.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013);Pages 1202-1208-
dc.subjectStandard deviationsen_US
dc.subjectdegree differencesen_US
dc.subjectindicatorsen_US
dc.subjectmixing patternsen_US
dc.subjectcomplex networksen_US
dc.titleStandard deviations of degree differences as indicators of mixing patterns in complex networksen_US
dc.typeArticleen_US
dc.identifier.doi10.1145/2492517.2500265en_US
Appears in Collections:Research Papers - Dept of Computer Science and Software Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

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