A network epidemic model for online community commissioning data |
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Authors: | Clement Lee Andrew Garbett Darren J Wilkinson |
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Institution: | 1.School of Mathematics and Statistics,Newcastle University,Newcastle upon Tyne,UK;2.Open Lab,Newcastle University,Newcastle upon Tyne,UK |
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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. |
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