Foundations of Data Science II - December 8th 2021

Day 3 - Foundations of Data Science II (Wednesday 8th December)

9.30-12.00am: Dr Riccardo Rastelli, UCD. Topic: An introduction to statistical network analysis

Brief synopsis : Nowadays, large amounts of stored data describe how entities interact with each other. For example, these data may represent friendship relations between scholars, coauthorship relations between researchers, mutual claims between financial institutions, or functional connectivity between different areas of the brain. Random graphs are the mathematical tools that are used to represent these interaction datasets.

Researchers and practitioners are often interested in modelling the random graphs, and in understanding their structures and capturing some of their features of interest. For these purposes, a number of statistical models have been introduced in recent times. One family of these statistical models relies on a "latent variable" structure, whereby one assumes that the nodes are characterised by some latent information that determines their connectivity behaviour.

In this session, I will focus on two latent variable models for random graphs: the stochastic block model and the latent position model. I will introduce the theory behind these models, and give an overview of their mathematical properties. Then, I will focus on the R packages that can be used to fit them, and I will coordinate an interactive session where the models will be used to analyse real datasets.

Software required: laptop with R installed https://www.r-project.org/ with additional R packages that will be used: igraph, statnet, latentnet, blockmodels, dynsbm

Speaker biography: Dr. Riccardo Rastelli is Lecturer at the School of Mathematics and Statistics, University College Dublin. His research focuses on statistical methodologies for the analysis of complex networks