Bipartite Graphs for Modelling and Monitoring Heterogeneous Data

In this Master Thesis, the student explored network modelling and monitoring on the example of bipartite graphs. In graph theory, k-partite graphs define graphs whose vertices can be partitioned into k different independent sets. The work introduces a joint application of the latent trait analysis model to represent graphs and the exponentially weighted moving average chart for monitoring real-life data. Using the Norwegian company and director dataset to perform modelling and monitoring, it could be displayed how the interlocking directorate (the same person is a director board member of two or more companies) changed overtime at an alarming rate during the global financial crisis.

The picture shows a bipartite graph representation of the Norwegian public limited companies (blue nodes) and their directors (orange nodes).