Our workshops provide hands-on training in social network analysis with R and
statnet. We teach the main workshops at least once each year at one of the INSNA related conferences – Sunbelt, North American Social Networks, and European Union Social Networks meetings. All of our workshop materials are posted online and the links can be found on this page.
These are the materials you need if you are participating in one of our formal workshops.
But this site is also designed to be used for self-guided learning: detailed instructions for getting started, tutorials with lots of examples, and downloadable scripts for reproducing these examples on your own computer.
The links are organized by workshop category. If you know the workshop you want, you can navigate to it using the links on the left sidebar. Otherwise, scroll down and you will find a bit more information about each.
Please check this site periodically for updates and announcements.
You’ll need to install R and one or more of the
statnet packages. Which of the packages you install depends on what type of network analysis you have planned. Some basic information on the package functionality and purpose can be found on the “About” page.
We recommend also installing and using the
Rstudio application/environment, but all of the tutorial examples and scripts can also be run from the standard R console.
For basic instructions on getting started, see:
If you have additional questions, please see the Help page for the best way to reach us.
Introduction to SNA tools in R A comparative survey workshop of the main R packages used for network data management, analysis, and visualization.
Cross-sectional (static) network modeling
Exponential Random Graph Models (ERGMs) using
statnet Introduction to Exponential-family Random Graph Models (ERGMs) for statistical analysis and simulation of social networks.
Advanced ERGMs using
statnet Model specification with advanced ergm features and extension packages, including multi-level network analysis with the
ERGMs for egocentrically sampled network data using
statnet Analyzing egocentrically sampled data with Exponential-family Random Graph Models.
Modeling Valued Networks with
statnet Introduction to modeling social networks with ties that have weights (e.g., counts of interactions) or are ranks (i.e., each actor ranks the others according to some criterion).
Temporal network modeling
Temporal network exploratory tools in
tsna Introduction to exploratory analysis and visualization of temporal network data.
Temporal Exponential Random Graph Models (TERGMs) for dynamic network modeling in
statnet Introduction to the estimation and simulation of dynamic networks with Temporal Exponential-family Random Graph Models (TERGMs).