Departmental Papers (ASC)

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Journal Article

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Journal of Complex Networks



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Most human interactions today take place with the mediation of information and communications technology. This is extending the boundaries of interdependence: the group of reference, ideas and behaviour to which people are exposed is larger and less restricted to old geographical and cultural boundaries; but it is also providing more and better data with which to build more informative models on the effects of social interactions, amongst them, the way in which contagion and cascades diffuse in social networks. Online data are not only helping us gain deeper insights into the structural complexity of social systems, they are also illuminating the consequences of that complexity, especially around collective and temporal dynamics. This paper offers an overview of the models and applications that have been developed in what is still a nascent area of research, as well as an outline of immediate lines of work that promise to open new vistas in our understanding of cascading behaviour in social networks.

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© The Authors 2013. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact


Borge-Holthoefer, J., Baños, R., González-Bailón, S., and Moreno, Y. (2013). “Cascading Behaviour in Complex Socio-Technical Networks", Journal of Complex Networks, 1(1), 3-24. doi:0.1093/comnet/cnt006

At the time of publication, author Sandra González-Bailón was affiliated with the Oxford Internet Institute, University of Oxford. Currently (February 2016), she is a faculty member at the Annenberg School for Communication at the University of Pennsylvania.


contagion, diffusion, social influence, computational social science, big data

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Date Posted: 24 February 2017