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

• Activity Number: 548
• Type: Contributed
• Date/Time: Wednesday, August 12, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistical Learning and Data Mining
• Author(s): Daniel Sewell* and Yuguo Chen
• Companies: University of Illinois at Urbana-Champaign and University of Illinois at Urbana-Champaign
• Keywords: Network structure ; Markov chain Monte Carlo ; Network dynamics ; Visualization ; Weighted networks ; Social networks

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.