A mixture model approach for clustering bipartite networks

This chapter investigates the latent structure of bipartite networks via a model-based clustering approach which is able to capture both latent groups of sending nodes and latent variability of the propensity of sending nodes to create links with receiving nodes within each group. This modelling app...

Full description

Saved in:
Bibliographic Details
Main Author Gollini, Isabella
Format Journal Article
LanguageEnglish
Published 07.05.2019
Subjects
Statistics - Applications
Statistics - Methodology
Online AccessGet full text

Cover

More Information
Summary:This chapter investigates the latent structure of bipartite networks via a model-based clustering approach which is able to capture both latent groups of sending nodes and latent variability of the propensity of sending nodes to create links with receiving nodes within each group. This modelling approach is very flexible and can be estimated by using fast inferential approaches such as variational inference. We apply this model to the analysis of a terrorist network in order to identify the main latent groups of terrorists and their latent trait scores based on their attendance to some events.
DOI:10.48550/arxiv.1905.02659