Back in March I introduced the basic concept of what a social network was and how and why we use them, so I'll use this post to introduce some more "in depth" social network ideas and some more complicated network pictures - hopefully meaning when the full social networks are posted from Dublin or Alftanes they won't take too much explaining....
The social network in that March post is about as simple as could be. It contains relatively few individuals (nodes on the graph) and edges (the lines connecting them) are present if two individuals have associated and not present if they're weren't seen together. Clearly a social network could include a lot more information than this. For example, it is useful to have the edges weighted by how strong the association/interaction between two individuals is - whilst weak associations between individuals can be important, it is generally much more interesting to know that two individuals interact frequently, especially for our research which is focussed on investigating "friendships" or patterns of social interactions. Below I've reproduced the same network as in that first post on the subject, but this time with edges weighted by how often individuals are seen together. Clearly networks that contain information on the strength as well as the presence of associations contain lots more useful information.
Part of a brent goose social network. Lines join individuals that have been seen together three or more times. The thickness denotes how strong the connections are
As more individuals are included, networks begin to get more complicated - much more complicated! Larger social networks often contain distinct clusters of individuals (known as communities in social network speak) that are normally connected by links between only one or two individuals. Often the associations of individuals themselves become difficult to ascertain just by looking at the network, as patterns of interactions become very complex, particularly within social clusters. Here is a larger section of a social network from Iceland this year:
A brent goose social network from the Alftanes peninsula this spring. Edges are weighted by the strength of the association between two individuals. The colour of each node represents which social community an individual belongs to
Clearly this sort of situation is where we need to start using the properties of each node (called metrics) to fully understand an individual's position in a social network, and I'll introduce the more important of these in the next post from me.
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