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Research Highlight

Posted on 17 July 2014

Prof. James Gleeson, co-director of the Mathematics Applications Consortium for Science and Industry (MACSI) at the University of Limerick, has just published an article in the Proceedings of the National Academy of Sciences USA describing a model of collective online behaviour of millions of Facebook users in adopting apps. Prof. Gleeson used ICHEC's supercomputing resources via a Class B project to carry out some of the computations that enabled the study.

Reference:

Gleeson J.P., Cellai D., Onnela J.-P., Porter M.A. and Reed-Tsochas F. (2014) A simple generative model of collective online behavior. Proc. Natl. Acad. USA Published online 7 July 2014.

Abstract: One of the most common strategies in studying complex systems is to investigate and interpret whether any "hidden order" is present by fitting observed statistical regularities via data analysis and then reproducing such regularities with long-time or equilibrium dynamics from some generative model. Unfortunately, many different models can possess indistinguishable long-time dynamics, so the above recipe is often insufficient to discern the relative quality of competing models. In this paper, we use the example of collective online behavior to illustrate that, by contrast, time-dependent modeling can be very effective at disentangling competing generative models of a complex system

[ link to article ]

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