Editing Communication and Social Networks (Spring 2024)/Visualization challenge (section)

== Dutch School Data ==

In 2003 and 2004, researchers repeatedly surveyed a number of Dutch school students about their friendships and their behavior. They were particularly interested in the relationship between friendships and drinking behavior. They recorded information about alcohol use, gender, age, ethnicity (whether Dutch or not), and religion.

You may want to ask questions like:
* Are people who drink more more popular?
* Are males or females more likely to have the same drinking behavior as their friends?
* Are people of the dominant religion more likely to be popular? More likely to be friends with each other?


=== Resources ===

The [https://jeremydfoote.com/Communication-and-Social-Networks/week_6/ggraph_walkthrough.html Introduction to ggraph and tidygraph reading] actually uses this dataset. You can look to that for examples to build on (Here is the [https://jeremydfoote.com/Communication-and-Social-Networks/week_6/ggraph_walkthrough.Rmd R Markdown file] that I used to create the web page).

Data:
* [https://raw.githubusercontent.com/jdfoote/Communication-and-Social-Networks/fall-2022/resources/school_graph_nodes.csv Node data]
* [https://raw.githubusercontent.com/jdfoote/Communication-and-Social-Networks/fall-2022/resources/school_graph_edges.csv Edge data]

Descriptions of what each measure means are at [http://www.stats.ox.ac.uk/~snijders/siena/tutorial2010_data.htm this site], maintained by the people who collected the data.

To import the data you can right-click on and save the edge and node data files above to your computer and then import them into R.

Alternatively, the following code will download the files and create a graph object. You are welcome to reuse it.
<syntaxhighlight lang="R">
library(tidyverse)
library(igraph)
library(tidygraph)
library(ggraph)

nodes = read_csv('https://raw.githubusercontent.com/jdfoote/Communication-and-Social-Networks/fall-2022/resources/school_graph_nodes.csv')
edges = read_csv('https://raw.githubusercontent.com/jdfoote/Communication-and-Social-Networks/fall-2022/resources/school_graph_edges.csv')

G = graph_from_data_frame(d=edges, v=nodes) %>% as_tbl_graph()
</syntaxhighlight>