Analysis of the formation of the structure of social networks by using latent space models for ranked dynamic networks

Daniel K. Sewell, Yuguo Chen

Research output: Contribution to journalArticlepeer-review

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 frame and answer these questions intuitively. The well-known data collected by Newcomb in the 1950s are very well suited to analyse the formation of a social network. We applied our model to these data to investigate the network stability, what groupings emerge and when they emerge, and how individual popularity is associated with individual stability.

Original languageEnglish (US)
Pages (from-to)611-633
Number of pages23
JournalJournal of the Royal Statistical Society. Series C: Applied Statistics
Volume64
Issue number4
DOIs
StatePublished - Aug 1 2015

Keywords

  • Embedding
  • Markov chain Monte Carlo sampling
  • Network dynamics
  • Network structure
  • Social networks
  • Visualization
  • Weighted networks

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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