A network epidemic model for online community commissioning data

Lee, Clement and Garbett, Andrew and Wilkinson, Darren J. (2018) A network epidemic model for online community commissioning data. Statistics and Computing, 28 (4). pp. 891-904. ISSN 0960-3174

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Abstract

A statistical model assuming a preferential attachment network, which is generated by adding nodes sequentially according to a few simple rules, usually describes real-life networks better than a model assuming, for example, a Bernoulli random graph, in which any two nodes have the same probability of being connected, does. Therefore, to study the propagation of “infection” across a social network, we propose a network epidemic model by combining a stochastic epidemic model and a preferential attachment model. A simulation study based on the subsequent Markov Chain Monte Carlo algorithm reveals an identifiability issue with the model parameters. Finally, the network epidemic model is applied to a set of online commissioning data.

Item Type:
Journal Article
Journal or Publication Title:
Statistics and Computing
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1703
Subjects:
?? stochastic epidemic modelsmcmcrandom graphspreferential attachmentcommunity commissioningcomputational theory and mathematicstheoretical computer sciencestatistics and probabilitystatistics, probability and uncertainty ??
ID Code:
133320
Deposited By:
Deposited On:
01 May 2019 15:45
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 19:22