Understanding an SNA chart – updated 28/11/2012
– The basic elements of an SNA chart are the node and the edge. Here’s how they are presented in their most basic form.
A node represents something (e.g. a person in your facebook network) whereas an edge indicates a connection to another node. Typically a node will only have one connection to eac other node.
The direction of the connection between two objects is often important as is the number of connections to an object. An easy to understand example is the links in a webpage. You click the link to take you to another page. Links that take you to another node are said to have outdegree and are shown like this:
The opposite situation is when a node is linked from another node and this node is said to have indegree:
When several nodes are linked together they may look like this:
The overall number of connections to a node is referred to as it’s degree. If you don’t care about the direction of the links, such as in a simple facebook map then you simply count the edges that arrive at a node to get it’s undirected degree.
Counting the number of arrows pointing to a node gives you it’s indegree.
Counting the number of arrows pointing away from a node gives you it’s outdegree.
Size & Colour
Nodes can usefully show other information by changing their size and colour. Typically color will be used to show different types of node (e.g. male and female or leisure v.s. work) whereas size will show something measurable such as degree or one of the other useful network metrics.
Sometimes instead of showing individual nodes we show a node that represents a bunch of other nodes to provide a clear overview. These nodes are termed Metanodes and are very useful in giving an overall picture.
Other Useful metrics
If a node is on the path to many other nodes following the path of connected edges in a diagram then it is said to exhibit high betweenness. There are calculations that can establish the betweenness of all the nodes in a network. This can be useful in many ways.
A node doesn’t have to be between many other nodes to be able to reach them in a short distance. Such a node is said to have high closeness.
In a network map we will often speak of the Giant Component. This is simply where a large portion of the map is interconnected. it’s possible for a network to have multiple giant components.
Example Map – My LinkedIn Network
Example Map 2 – My facebook Giant Component
The above is a selection from my Facebook Map.
Exactly how this was achieved will form the subject of another page at a later date.
The Nodes have been sized by Degree and colored by closeness with those having the lowest betweeness being mauve, medium green and highest blue. The labels have been anonymized to protect my friends.
From the map you can clearly see that nodes a28 and a36 have the highest degree and are thus the best connected in my network from my perspective i.e. amongst those people that I know.