What can we find out from the denseness of social networks?
Individual Versus Network Characteristics
Researchers often study questions focused upon the individual. For example, we might want to know if a consumer has been influenced by an advertisement. Alternatively, we might assess what sort of skills are useful for a salesperson to possess? There are good reasons for this. Often we are seeking to give advice to individuals on how they should behave. Other times we are seeking to understand the decision-making of individuals. Individuals matter.
Clearly however this isn’t the full story of how the world works. The relationships between people and the nature of groups also matter. We are not just ‘egos’ on our own. At least, mostly not. Social Network Analysis attempts to do this. Such work considers networks, social groups. Each group comprises nodes and edges. In a typical analysis, the nodes will be people. Meanwhile, the edges will be the connections between people. The connections being friendships, working relationships, and family ties.
Comparing Social Networks
After mapping networks you may want to compare them. There are great visual ways of representing networks. I’ll discuss this in future posts, but visual networks are hard to compare. Ideally, we want measures of the network that are comparable across different networks. One such measure is the density of the complete network. Density is how highly the network members “are connected among themselves” (Knoke and Yang 2008, page 53).
The Denseness of Social Networks
Density represents the percentage of all the connections that could exist that actually do exist. So if everyone was connected to everyone else density would be one. If no one was connected to anyone else density would be zero.
Let us assume that we are examining an undirected network. This means all connections are mutual, if you know me I must also know you. To calculate density first count all the connections that exist in the network. Then find the number of connections that could exist. You can manually assess this for small networks. With larger networks, the number gets very large, very quickly. A helpful formula exists. N is the number of people. And so the formula shows the number of connections possible when N people are linked.
! is factorial. Use the command FACT() in Excel.
What To Expect?
The level of density that you might expect depends upon the relationships that you are coding. If you count having met someone as a connection you will have a denser network. At least compared to if you count only, relatively rare, academic co-authorships. Density represents an interesting way to start measuring the properties of social groups.
For more on social network analysis see here, here, and here.
Read: David Knoke and Song Yang, (2008), Social Network Analysis, 2nd Edition, Sage Publications.