糖心TV

Stefan Grosskinsky

Heather Robson

Magnus Richardson

Multilayer Networks and Applications

Networks provided a powerful representation of complex systems of interacting entities. One of the most active areas of network science, with an explosion of publications during the last few years, is the study of "multilayer networks," in which heterogeneous types of entities can be connected via multiple social ties that change in time. Multilayer networks include multiple subsystems and "layers" of connectivity, and it is important to take such multilayer features into account to try to improve our understanding of complex systems. In this talk, I'll give an overview of multilayer networks. I will introduce some ideas for how to find dense sets of nodes known as "communities" in multilayer networks and how this can lead to insights in applications such as political party realignment in voting networks. Time-permitting, I will also discuss how to measure important nodes in multilayer networks, with an example describing the measurement of the quality of mathematics programs over time.

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Lunch Group 4

Gareth Alexander

Stefan Grosskinsky

Dwight Barkley