This summer the Essex Summer School (University of Essex, UK) will again offer an introductory and an advanced course on Social Network Analysis.
1) Introduction to Social Network Analysis (2 weeks, 8-19 July 2019)
Content. The course focuses on the description and visualization of social network data using UCINET. We will concentrate on uncovering structural properties of the network (e.g. density, homophily, and clustering), as well as on how to identify important persons in a network (e.g. degree centrality, structural holes, …). We will also pay attention to the detection of subgroups and deal with basic hypothesis testing for social network analysis. Throughout the course some classic theories that focus on network processes (e.g. related to homophily, centrality measures, structural holes, Granovetter’s strength of weak ties and small worlds) will be discussed.
2) Advanced Social Network Analysis: Cross-sectional and longitudinal SNA (1 week, 22-26 July 2019)
Content. This module covers advanced statistical methods for analyzing social network data, focusing on testing hypotheses about network structure (e.g. reciprocity, transitivity, and closure), and the formation of ties based on attributes (e.g. homophily). The first three days provide an in depth discussion of exponential random graph models (also known as ERGM or p* models). We then introduce longitudinal models such as RSiena models (SAOMs) and relational event models.
Please feel free to forward to anyone that you think might be interested.
- Senior Lecturer in Organisational Behaviour/Programme Director of the 4-year PhD in Management, Surrey Business School, University of Surrey
- Associate Member, Department of Sociology/Nuffield College, University of Oxford
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