University of Cambridge > Talks.cam > Making connections- brains and other complex systems > Discovering and quantifying patterns in networks with coloured nodes

Discovering and quantifying patterns in networks with coloured nodes

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  • UserDr Vincenzo Nicosia
  • ClockThursday 16 June 2022, 15:00-16:00
  • HouseOnline.

If you have a question about this talk, please contact Sarah Morgan.

Graphs with coloured nodes provide an informative model for complex systems whose units are associated to a discrete number of classes. Some relevant examples include social systems, geographic networks, and cell adjacency networks. Quite often, as in the case of geographical networks, the arrangement of those classes is an important aspect of the global organisation of the system. Hence, quantifying the existence of heterogeneity and correlations in the assignment of the nodes of a graph to classes is paramount to characterise the behaviour of a system. In this talk we will cover the basics of networks with coloured nodes, and we will show how a simple set of measures, based on random walks on the graph, can be effectively used to measure the existence of correlations and heterogeneity among classes. Interesting applications include the quantification of spatial segregations in cities, the identification of polarisation in social systems, the emergence of robust spatial organisation in plant tissues, and the incorporation of metadata in community detection tasks.

This talk is part of the Making connections- brains and other complex systems series.

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