Social Network Analysis using R

Day/time: Wednesday, April 11,  1:00 PM – 5:00PM. Room: Big Bend B/C. Organizers: James Holland Jones (Stanford U), Ashley Hazel (Stanford U), and Elspeth Ready (U of Nebraska). Maximum attendance: 20

Registration for this workshop is now closed. We have serious space limitations at the Austin meetings, but are in the process of exploring ways to make the workshop available to more people.

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. Participants are limited to a maximum of 20.

The workshop is designed for students, post-docs, and faculty interested in using social network analysis in R. It will be of particular interest to primatologists and human behavioral ecologists.