Social Network Analysis Resources for R

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Social Network Analysis is an increasingly popular tool for modelling dependence structures between social actors. In my department researchers are developing new models for representing such dependence structures (MELNET). In 2007 I gave a talk on my consulting experience using social network analysis to provide insights on team dynamics. Since then I have switched to mainly using R for analysing social network datasets.

R has many advantages for running social network analyses:
  • R packages exist that are devoted to representing, modelling, and plotting networks
  • Network data tends to be less standardised than the typical social science dataset. Thus, R’s ability to manipulate and restructure datasets programmatically is particularly useful.
  • It’s relatively easy to implement customised functions in R, which are often required in social networks
Some social network resources for R include:
My own experience using R: I’ve recently conducted research looking at social networks in the class room. The data includes multiple networks (e.g., friendship, talking), longitudinal measurement, and many different class rooms. R makes it particularly easy to manipulate such data structures and present them graphically. It’s also encouraging that many of the modelling techniques including exponential random graph models and the longitudinal models in Siena have been, or are in the process of being, migrated to R.

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