Triadic closure dynamics drives scaling-laws in social multiplex networks

TL;DR

This paper demonstrates that triadic closure is a fundamental dynamical principle explaining the scaling-laws observed in social multiplex networks, validated through a simple model and real-world data from an online game.

Contribution

The paper introduces a simple model showing that triadic closure explains key scaling-laws in social multiplex networks, supported by empirical data analysis.

Findings

Scaling-laws are interconnected through triadic closure.

The model accurately reproduces observed exponents in real data.

Triadic closure may be a fundamental principle in social network formation.

Abstract

Social networks exhibit scaling-laws for several structural characteristics, such as the degree distribution, the scaling of the attachment kernel, and the clustering coefficients as a function of node degree. A detailed understanding if and how these scaling laws are inter-related is missing so far, let alone whether they can be understood through a common, dynamical principle. We propose a simple model for stationary network formation and show that the three mentioned scaling relations follow as natural consequences of triadic closure. The validity of the model is tested on multiplex data from a well studied massive multiplayer online game. We find that the three scaling exponents observed in the multiplex data for the friendship, communication and trading networks can simultaneously be explained by the model. These results suggest that triadic closure could be identified as one of the fundamental dynamical principles in social multiplex network formation.