Anthropologists have long appreciated that single-layer networks are insufficient descriptions of human interactions---individuals are embedded in complex networks with dependencies. 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 . The analysis of multi-dimensional social networks has recently garnered the attention of the mathematics and physics communities. Multilayer networks are ubiquitous and have consequences, so processes giving rise to them are important social phenomena.  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 . Understanding the structuring processes that underlie multiplex networks will help understand increasingly rich datasets, which give better, richer, and more accurate pictures of social interactions.
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.
R
Anthropologists
Social scientists
R
single-layer networks are insufficient descriptions of human interactions---individuals are embedded in complex networks with dependencies.
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
R
. The analysis of multi-dimensional social networks has recently garnered the attention of the mathematics and physics communities. Multilayer networks
in the form of trade.2 Multilayer networks, high-dimensional networks that allow us to consider multiple sets of relationships at the same time,
A
The analysis of multi-dimensional social networks has recently garnered the attention of the network science community.3
R
.
.6
R
which give better, richer, and more accurate
giving more accurate and complete