Network Visualization

Description: Network science approaches are being increasingly used to explore complex interactions and the general connectivity among entities, from friends in a social network to the spread of a disease in a population. Due to its complexity, network data is often explored and communicated using data visualizations. In this intermediate R workshop, we will cover how to tell useful stories with network data primarily using the 'network' package's network objects and the 'ggraph' plotting package that is compatible with much of the ggplot2 framework. In this interactive and hands-on workshop, we'll practice using these packages in R to plot one-mode and two-mode networks. As we introduce functions unique to these packages, we will discuss what visualization features best suit different types of network data and research communication goals. Along the way we will cover basic data preparation steps and how to calculate (or assign) key network descriptives including centrality measures, edge attributes, and community clusters for your plots.  

The target audience for this workshop is intermediate to advanced R users. This workshop will provide only a cursory introduction to network data and therefore is best suited for learners who have some familiarity working with networks. While workshop examples will be demonstrated using social scientific data (e.g., social connections and co-occurrence networks), network visualizations can be applied to a wide variety of research questions and learners from all domains are welcome. 

Learning Objectives

After completing this workshop, learners should be able to:

• Prepare network data of various formats and use them to generate both 'igraph' and 'network' objects
• Identify the necessary components for visualizing network objects in ggraph
• Calculate network and node-level descriptives in both one-mode and two-mode networks
• Select among various visualization strategies for communication goals
• Create well-designed network figures
• Identify where to go to learn more!

Prerequisites: Participants must have taken DataLab’s “R Basics” workshop series and/or have prior experience using R, be comfortable with basic R syntax, and have it pre-installed and running on their laptops. We also strongly encourage to have either taken DataLab's Intermediate R Data Visualization workshop, or have general familiarity with how to make plots in R using the ggplot2 package.

Software: Latest version of R and RStudio installed with these packages:

• igraph
• network (part of statnet)
• sna (part of statnet)
• ggraph
• tidyverse

Instructor: Liza Wood

Instructor Bio: Liza Wood is an environmental social scientist and a PhD candidate in Ecology/DE Computational Social Science. She has worked with the DataLab since 2022 teaching and supporting programs for programming education in R.