Animal social networks as intersections graphs of random walks

TL;DR

This paper analyzes animal social networks modeled as intersection graphs of random walks, revealing their structure as hypergraphs and providing analytical probability distributions, which improve understanding of animal association patterns.

Contribution

It characterizes the mathematical structure of animal social networks as hypergraphs derived from random walks, offering analytical probability distributions and insights into their true complexity.

Findings

Networks are better described by hypergraphs than simple graphs.

Analytical probability distributions for the associated bipartite graphs and hypergraphs are derived.

Hypergraph models capture more accurate associations among agents.

Abstract

We study here the social network generated by the asynchronous visits, to a fixed set of sites, of mobile agents modelled as independent random walks on the plane lattice. The social network is constructed by assuming that a group of agents are associated if they have visited the same set of sites within a finite time interval. This construction is an instance of a random intersection graph, and has been used in the literature to study association networks in a number of animal species. We characterize the mathematical structure of these networks, which we view as one-mode projections of suitable bipartite graphs or, equivalently, as 2-sections of the corresponding hypergraphs. We determine analytically the probability distribution of the random bipartite graphs and hypergraphs associated to this construction, and suggest that association networks generated by the use of common resources are better described by hypergraphs rather than simple projected graphs, that miss important information regarding the actual associations among the agents.