Welcome!

In this workshop, we will explore social network analysis (SNA), a set of methods and theories used in the analysis of social structure. We will work with a variety of state-of-the-art tools available in the free statistical language, R, emphasizing in particular the use of statistical models for networks (e.g., exponential random graph models) and network visualization. We focus on data as they would be collected in face-to-face, anthropological fieldwork (i.e., either through direct observation or through ethnographic interviews or surveys), which makes this workshop different from most SNA short courses. This means generally concentrating on egocentric network, two-mode network, and sampled network data.

In order to build our way up to discussion of statistical models for networks, we will cover some classic approaches to structural analysis, including: social relationships in humans and other animals, introduction to graphs and the basics of graph theory, network visualization, structural measures (e.g., density, centrality and centralization, clustering and community detection, embeddedness). In addition, we will cover topics in research design, including: network sampling, data representation, data quality, and missing data. We will use R-based tools from both the igraph package and the statnet family of packages. Some familiarity with R is advisable.

This page has all the materials you will need for the workshop. We will update the webpage as the workshop date approaches.

Pre-workshop materials

These materials will guide you through installing the software needed for the workshop and help familiarize new users with the basics of R. Please complete these before the workshop. We also recommend starting to work through the Introduction to igraph tutorial ahead of time.

• Installing R
• Introduction to R

Workshop materials

These are the topics we will cover in the workshop:

• Introduction to networks and network data collection
• Data formatting and import
• Introduction to igraph
• Introduction to ERGMs

Additional resources

• Graph concepts and measures
• ERGM predictions and GWESP
• Plotting Embedded Subgraphs
• Epidemics and Sampling Graph Vertices
• Syllabus for SNA course at Stanford, with extensive list of readings
• Links to various SNA resources

About us

James Holland Jones, Associate Professor, Stanford University

Elspeth Ready, Senior Researcher, Department of Human Behavior, Ecology and Culture Max Planck Institute for Evolutionary Anthropology

Ashley Hazel, Research Scientist, Stanford University