Tracking the evolution of communities in dynamic social networks

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Show simple item record Greene, Derek Doyle, Dónal Cunningham, Pádraig 2010-06-01T16:11:11Z 2010-06-01T16:11:11Z 2010 IEEE en 2010 by The Institute of Electrical and Electronics Engineers, Inc. 2010-08-11
dc.identifier.isbn 978-1-4244-7787-6
dc.description 2010 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2010), 9-11 August 2010, Odense, Denmark en
dc.description.abstract Real-world social networks from a variety of domains can naturally be modelled as dynamic graphs. However, approaches to detecting communities have largely focused on identifying communities in static graphs. Recently, researchers have begun to consider the problem of tracking the evolution of groups of users in dynamic scenarios. Here we describe a model for tracking the progress of communities over time in a dynamic network, where each community is characterised by a series of significant evolutionary events. This model is used to motivate a community-matching strategy for efficiently identifying and tracking dynamic communities. Evaluations on synthetic graphs containing embedded events demonstrate that this strategy can successfully track communities over time in volatile networks. In addition, we describe experiments exploring the dynamic communities detected in a real mobile operator network containing millions of users. en
dc.description.sponsorship Science Foundation Ireland en
dc.description.uri Conference details en
dc.description.uri en
dc.format.extent 1016274 bytes
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher IEEE en
dc.relation.ispartof N. Memon and R. Alhajj (ed.s). 2010 2010 International Conference on Advances in Social Network Analysis and Mining : ASONAM 2010 : proceedings
dc.subject Social network analysis en
dc.subject Machine learning en
dc.subject Community finding en
dc.subject.lcsh Online social networks--Computer simulation en
dc.subject.lcsh Social groups--Computer simulation en
dc.subject.lcsh Machine learning en
dc.title Tracking the evolution of communities in dynamic social networks en
dc.type Conference Publication en
dc.internal.availability Full text available en
dc.status Peer reviewed en
dc.identifier.doi 10.1109/ASONAM.2010.17
dc.neeo.contributor Greene|Derek|aut| en
dc.neeo.contributor Doyle|Dónal|aut| en
dc.neeo.contributor Cunningham|Pádraig|aut| en
dc.description.admin ti ke SB. 010610 On publication need to replace pdf with published version - AV 19/5/2010 en

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