Kezia Manlove

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  Can a tripartite model help us understand temporal variation in social contact networks?
  Kezia Manlove

  Understanding dynamics of social contact is a key precursor for modeling propagation of pathogens, genes, and information through societies. However, there is little consistency within the ecological community about what form of social contact network to use, when. In this talk, I'll propose a tripartite network model borrowing from Lagrangian descriptions of animal movement, that relates disparate ecological networks under a single unifying structure using nodes of type Individual, Location, and Time. I'll show how this tripartite network can be reduced to a variety of different commonly used ecological networks, including individual association networks, home-range overlap networks, and transportation-like networks; and then I'll argue that particular social structures generate consistent redundancies in information between these node types. I'll then demonstrate how information derived from alternative ecological metrics like group size or home range size distributions can be used to constrain the tripartite network's topology. Lastly, I'll outline two potential pathways for using the tripartite network to formally quantify information lost through network projection, one reliant on graph theory, and the other reliant on Shannon's information.