install.packages("igraph")
install.packages("statnet") #installs ergm, network, and sna
install.packages("snahelper")
install.packages("netUtils")
install.packages("ggraph")
install.packages("backbone")
install.packages("netrankr")
install.packages("signnet")
install.packages("intergraph")
install.packages("graphlayouts")
install.packages("visNetwork")
install.packages("patchwork")
install.packages("edgebundle")
install.packages("ggplot2")
install.packages("gganimate")
install.packages("ggforce")
install.packages("rsiena")
install.packages("remotes")
remotes::install_github("schochastics/networkdata")Social Network Analysis
MSc course
This course is an introduction to the statistical analysis and modeling of social networks. The course aims to give a basic understanding of and a working handle on drawing inference for network structure and actor level attributes for both cross-sectional and longitudinal network data. A fundamental notion of the course will be on how the structure of observed graphs relate to various forms of random graphs. This will be developed in the context of non-parametric approaches, and elaborated to the analysis of networks using models such as Exponential Random Graph Models (ERGMs) and Stochastic Actor Oriented Models (SAOMs). The students will be provided several hands-on exercises and will apply the covered approaches to a suite of real world data sets.
The course text book can be found here: R4SNA (work in progress)
Schedule
| slides | practical | data | worksheet | |
|---|---|---|---|---|
| 1: Introduction | .qmd | |||
| 2: The Language of Networks | .qmd |
R Packages
Throughout the course we will use a variety of different packages of doing network analysis, modeling and visualization. Make sure to install them all and have them ready to load when needed: