The Structure of Networks

Network topology summarizes connection patterns through measures such as degree, clustering, paths, and communities. Its implications depend on what links mean and how the relevant process uses them.

Network structure describes the pattern of defined connections. Degree counts local links, clustering describes connections among neighbors, and betweenness concerns shortest paths through a node under a chosen convention. These metrics answer different questions; none is a direct measurement of trust, influence, or actual information flow.

Function also depends on direction, capacity, timing, routing, and the process using the network. A short topological path may be slow in practice, while a high-degree node may have substitutes. Choose the outcome before choosing a metric, then test the dependency the diagram suggests rather than treating centrality as a universal importance score.

When to use it

When organizational or social network structure needs strategic analysis; when key person risk from hub dependency needs assessment; when information flow needs to be understood or improved; when network position determines strategic advantage.

How it can help

Define the network and desired outcome, select relevant metrics, and inspect routing, timing, capacity, and redundancy. Test the dependency suggested by the structure.