Analysis of the Formation of the Structure of Social Networks using Latent Space Models for Ranked Dynamic Networks

TL;DR

This paper introduces a latent space model for ranked dynamic social networks to analyze their formation, stability, group emergence, and popularity effects, providing insights into social structure evolution.

Contribution

The paper presents a novel latent space modeling approach specifically designed for ranked dynamic networks, enabling intuitive analysis of social network formation and evolution.

Findings

Network stability over time was characterized.

Emergence of social groups was identified.

Popularity correlates with individual stability.

Abstract

The formation of social networks and the evolution of their structures have been of interest to researchers for many decades. We wish to answer questions about network stability, group formation and popularity effects. We propose a latent space model for ranked dynamic networks that can be used to intuitively frame and answer these questions. The well known data collected by Newcomb in the 1950's is very well suited to analyze the formation of a social network. We applied our model to this data in order to investigate the network stability, what groupings emerge and when they emerge, and how individual popularity is associated with individual stability.