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dc.contributor.authorBelák, Václav
dc.contributor.authorMashhadi, Afra
dc.contributor.authorSala, Alessandra
dc.contributor.authorMorrison, Donn
dc.date.accessioned2015-07-29T11:47:46Z
dc.date.accessioned2015-09-03T08:52:40Z
dc.date.available2015-07-29T11:47:46Z
dc.date.available2015-09-03T08:52:40Z
dc.date.issued2015
dc.identifier.citationComputer Communications 2015nb_NO
dc.identifier.issn0140-3664
dc.identifier.urihttp://hdl.handle.net/11250/298549
dc.description.abstractResearch on information di usion generally assumes complete knowledge of the underlying network. However, in the presence of factors such as increasing pri- vacy awareness, restrictions on application programming interfaces (APIs) and sampling strategies, this assumption rarely holds in the real world which in turn leads to an underestimation of the size of information cascades. In this work we study the e ect of hidden network structure on information di usion processes. We characterise information cascades through activation paths traversing vis- ible and hidden parts of the network. We quantify di usion estimation error while varying the amount of hidden structure in ve empirical and synthetic network datasets and demonstrate the e ect of topological properties on this error. Finally, we suggest practical recommendations for practitioners and pro- pose a model to predict the cascade size with minimal information regarding the underlying network.nb_NO
dc.language.isoengnb_NO
dc.publisherElseviernb_NO
dc.titlePhantom cascades: The effect of hidden nodes on information diffusionnb_NO
dc.typeJournal articlenb_NO
dc.typePeer revieweden_GB
dc.date.updated2015-07-29T11:47:46Z
dc.source.journalComputer Communicationsnb_NO
dc.identifier.doi10.1016/j.comcom.2015.07.012
dc.identifier.cristin1255504
dc.description.localcode© 2015 Elsevier B.V. All rights reserved. This is the authors' accepted and refereed manuscript to the article. Locked until 2017-07-17 due to copyright restricrions.nb_NO


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