# Why understanding multiplex social network structuring processes will   help us better understand the evolution of human behavior

**Authors:** Curtis Atkisson, Piotr J. G\'orski, Matthew O. Jackson, Janusz A., Ho{\l}yst, Raissa M. D'Souza

arXiv: 1903.11183 · 2020-05-28

## TL;DR

Understanding the processes behind multiplex social networks enhances our comprehension of human behavior evolution by revealing complex interdependencies across different social domains.

## Contribution

This paper emphasizes the importance of analyzing multilayer networks to better understand social structuring processes and their impact on human behavior evolution.

## Key findings

- Multilayer networks are widespread and influential.
- Ignoring layer interdependencies can lead to incorrect conclusions.
- Understanding these processes improves analysis of complex social data.

## Abstract

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.

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Source: https://tomesphere.com/paper/1903.11183