Statistical computing and social network analysis with R: a modeling approach
This workshop introduces participants to the R statistical programming environment with a modeling approach that serves as a foundation for more advanced Polnet workshops.
Specifically, participants will learn in six self-contained 30-minute modules:
- How to use R to model social systems: students will learn how to use R to model social systems (e.g., how model and measure individual attributes with sets, lists, and vectors; and how to model collections of individuals or societies with matrices and data frames).
- How to use R to manage and describe data. This component covers the basics of importing and exporting data, as well as an overview of descriptive statistics and statistical model formulae for regression analysis.
- Overview of R packages for data analysis. The workshop itself will use the sna and network modules and also provide a high-level overview of statnet and igraph package capabilities.
- How to import and export relational data. This component reviews the major formats of relational data and how these can be used within and outside R.
- How to describe SNA data. This component shows the basics of descriptive social network analysis (e.g., centrality scores, network-level statistics like density, etc.).
- How to visualize and describe SNA data.
What you will need
- A computer with Internet access
- An installation of R and RStudio
- No previous background with R or social network analysis is required
Statistical software information, installation, and use
- "What is R?"
- A more extensive introduction is available at "An Introduction to R"
- "How to install R""
- GUI to facilitate analysis with R: RStudio Integrated Development Environment
- An interactive "Using R" tutorial to see how R works
How to model and analyze networks (conceptual readings)
- “Social Network Analysis: A Brief Introduction”
- Jackson, Matthew (2008), "Representing and Measuring Networks" in Social and Economic Networks. Princeton University Press.
- Hanneman, Robert A. and Mark Riddle. 2005. Introduction to social network methods. Riverside, CA: University of California, Riverside
- R Packages for network analysis
About the instructor
Armando Razo is Associate Professor of Political Science and a faculty affiliate at the Indiana University Network Institute. His teaching and research interests include comparative analysis of networks and institutions, game-theoretic and computational models of networks and collective action, and political economy of development.