The data we use in our research is often relational in nature, from legislative bill co-sponsorship to the grooming behaviors in animals; unfortunately, though, we tend to boil these relations down and use them merely as covariates in our research. However, preserving the inherent relational aspect and modeling it as a whole can often lead to novel understandings; for instance, who would have thought that in comparing behavioral networks across species, Senate bill co-sponsorship networks would most resemble the networks of social licking among cows! 

In this workshop, we hope to expand your methodological toolkit by providing an overview of the nuts and bolts of social network analysis through the following topics: importing and cleaning data, exploratory analyses, basic statistical tests, an overview of various advanced statistical procedures, and visualizing your results. 

Code snippets will be provided so that folks from any background can take something away from this workshop; the only requirement will be bringing a laptop and having RStudio and R installed beforehand.

This workshop was developed by Scott Renshaw, a computational sociologist specializing in social network analysis. He is a current Post-Doctoral Research Associate at the Center for Informed Democracy & Social-Cybersecurity (IDeaS), CMU's center for the study of disinformation, hate speech, and extremism online. Scott hopes that this workshop will inspire participants to view their data in a more relational light. Please email Scott Renshaw, srenshaw@andrew.cmu.edu, to schedule a one-on-one consultation for those who would like additional support in network analytic approaches. 

Please note: programming or statistical experience in R, SPSS, Stata, Python, etc. is highly recommended.