Join Curt Frye for an in-depth discussion in this video What you should know before watching this course, part of Social Network Analysis Using R.
- [Narrator] Thank you again for your interest in social network analysis using R. Before I get started with the main part of the course, I'd like to review a few things that will be helpful for you to know before you get started. The first is that you should know how to install and use R. There is an Up and Running with R course available on the Lynda.com site. So if you need to review anything, then that would be a great place to go. And second, you should be familiar with some network analysis terminology which I'll review now, but again, I'll cover during the course.
First, I should note that a network is represented as a graph which shows links, if any, between each vertex, also called a node, and its neighbors. A line indicating a link between vertices is called an edge, also called a link. A group of vertices that are mutually reachable by following edges on the graph are called a component. And finally, the edges followed from one node to another are called a path. So let's take a quick look at a graph and see these elements in action.
The first thing to note is that I have called out an edge and a vertex. At the top left, you'll see an orange arrow pointing to a link between node number 11 and node number 24. That line is called an edge. The vertex arrow on the right side of the diagram is pointing to node number 20, so you can see that that is a vertex. This graph has two components. The first is in the top right. That is node or vertex number six.
It's by itself. And all of the other vertices or nodes can reached by following paths along the links between them. So for example, if I wanted to go at the bottom right of the graph from vertex number 19 to vertex number one, I could start on 19, go to five, 15, and then one. That would be the shortest path between those two nodes. And with that introduction, I think you're ready to take on social network analysis using R.
- Formatting data
- Creating network graphs
- Measuring connectedness and betweenness of points
- Calculating networking density
- Describing network components
- Visualizing a network
- Writing a network description to a text file