This course offers an in-depth overview of statistical models for social network analysis. The course is run by network experts at the Mitchell Centre for Social Network Analysis – a leading cross-disciplinary research group in the development and application of social network analysis techniques, located in the School of Social Sciences at the University of Manchester.

The course covers some of the core statistical methods, including Exponential Random Graph Models (ERGMs), Stochastic Actor-Oriented Models (SAOMs/SIENA) and Relational Event Models (REMs). In addition, we will cover tERGMs, autoregressive models (ALAAMs) and ERGMs/SAOMs for two/mode and multi groups (multilevel). The last day participants will be able to choose between advanced longitudinal network models, or semantic and socio-semantic network modelling with automap and mpnet.

For most of the analysis, we will be using R (aswell as MPNet). No prior knowledge of R is required, but basic knowledge of social network analysis and quantitative methods is recommended (see also the course in the first week of the Summer School).

Course Description

£100 discount off the total if booking on to two Mitchell Centre Summer School courses.