  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.
