Network analysis glossary
Degree centrality
Degree centrality is the number of ties a person has. It is the simplest measure of centrality: in a network of who talks to whom, the person with the highest degree talks to the most people. Divided by the number of other people in the network, it becomes a share between 0 and 1.
Updated · Netgraf
| Person | Ties |
|---|---|
| Diane | 6 |
| Fernando | 5 |
| Garth | 5 |
| Andre | 4 |
| Beverly | 4 |
Average 3.6 ties each across 10 people. Computed live from the example map with the same code the Netgraf insights panel runs.
How it's calculated
degree(v) = number of ties touching v normalised degree(v) = degree(v) / (n - 1)
When ties have a direction, degree splits in two. In-degree counts ties pointing at a person (how often they are chosen, cited or asked for help). Out-degree counts ties pointing away (how often they choose, cite or ask). In a classroom sociogram, in-degree is popularity.
What it tells you, and what it misses
Degree is a good first measure of activity, visibility and popularity, and it is the only centrality measure that needs nothing beyond each person's own ties. It says nothing about where those ties lead. In Krackhardt's kite, Diane has the most ties of anyone, but every one of them runs into the same busy cluster; she is not the person holding the network together. That is betweenness.
In Netgraf
Degree is the default size of each dot in the Graph view, and the Insights panel lists the most connected people first, under Most connected. The distribution chart in the panel shows how many people have each number of ties, which is where a hub-and-spoke network gives itself away.