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WS-M12: Tidy Networks: the tidyverse and tidygraph for social network analysis in R
Time:
Monday, 23/June/2025:
1:30pm - 4:30pm
Session Chair: Matthew Smith Session Chair: Yasaman Sarabi
Session Abstract
This 3-hour workshop provides an introduction to the R programming language for those without any previous or limited experience. It will introduce the tidyverse – a set of functions and packages for data processing, cleaning, and visualisation in R. In particular, we will focus on dplyr for data processing, ggplot2 for visualisation, and Rmarkdown for creating reports. We will go on to demonstrate how the tidyverse can be applied to social network analysis - more specifically through the use of the tidygraph package. The tidygraph permits you to utilise the underlying grammar structure of the tidyverse when dealing with graph objects in R. By using the tidygraph package you can manage edgelists and network attributes in a single object, along with implementing analysis on these objects. The tidyverse allows you to create tidy data frames, whilst the tidygraph allows you to create tidy graph objects – or tidy networks!
Learning Outcomes:
By the end of the session participants should be able to:
• Use R and RStudio.
• Make use of the tidyverse for data processing – more specifically preparing datasets for SNA.
• Visualising networks in R using ggplot2 (part of the tidyverse) and tidygraph.
• Create tidygraph objects and undertake some initial network analysis using the tidygraph package.
These users will benefit from gaining an insight into how to use R for data processing and social network analysis following the tidy philosophy.
Presentations
Tidy Networks: the tidyverse and tidygraph for social network analysis in R
Matthew Smith, Yasaman Sarabi
This 3-hour workshop provides an introduction to the R programming language for those without any previous or limited experience. It will introduce the tidyverse – a set of functions and packages for data processing, cleaning, and visualisation in R. In particular, we will focus on dplyr for data processing, ggplot2 for visualisation, and Rmarkdown for creating reports. We will go on to demonstrate how the tidyverse can be applied to social network analysis - more specifically through the use of the tidygraph package. The tidygraph permits you to utilise the underlying grammar structure of the tidyverse when dealing with graph objects in R. By using the tidygraph package you can manage edgelists and network attributes in a single object, along with implementing analysis on these objects. The tidyverse allows you to create tidy data frames, whilst the tidygraph allows you to create tidy graph objects – or tidy networks!
Learning Outcomes:
By the end of the session participants should be able to:
• Use R and RStudio.
• Make use of the tidyverse for data processing – more specifically preparing datasets for SNA.
• Visualising networks in R using ggplot2 (part of the tidyverse) and tidygraph.
• Create tidygraph objects and undertake some initial network analysis using the tidygraph package.
These users will benefit from gaining an insight into how to use R for data processing and social network analysis following the tidy philosophy.
