  Social scientists have long appreciated that relationships between
individuals cannot be described from observing a single domain, and that the
structure across domains of interaction can have important effects on outcomes
of interest (e.g., cooperation).1 One debate explicitly about this surrounds
food sharing. Some argue that failing to find reciprocal food sharing means
that some process other than reciprocity must be occurring, whereas others
argue for models that allow reciprocity to span domains in the form of trade.2
Multilayer networks, high-dimensional networks that allow us to consider
multiple sets of relationships at the same time, are ubiquitous and have
consequences, so processes giving rise to them are important social phenomena.
The analysis of multi-dimensional social networks has recently garnered the
attention of the network science community.3 Recent models of these processes
show how ignoring layer interdependencies can lead one to miss why a layer
formed the way it did, and/or draw erroneous conclusions.6 Understanding the
structuring processes that underlie multiplex networks will help understand
increasingly rich datasets, giving more accurate and complete pictures of
social interactions.
