Centrality

Centrality measures how important or influential a node is within a network, based on its position and connections relative to others.

The idea

In network analysis, centrality captures a node’s structural importance. Degree centrality counts how many direct connections a node has. Betweenness centrality counts how often a node sits on the shortest path between other nodes, which makes it a broker or bottleneck. Closeness centrality measures how quickly a node can reach every other node in the network. A person, product, or idea with high centrality often has outsized influence or information flow compared to peripheral nodes, even without formal authority.

When to use it

• Mapping who actually holds influence in an organization, beyond the org chart
• Identifying key connectors or bottlenecks in a supply chain or communication network
• Prioritizing which nodes to strengthen, protect, or target in a network (viral marketing, epidemiology, fraud detection)

How to apply it

1. Define the network. Who or what are the nodes, and what counts as a connection?
2. Choose the centrality measure that fits the question (degree for popularity, betweenness for brokerage, closeness for reach)
3. Compute or estimate centrality and compare nodes relative to each other
4. Use the ranking to guide decisions about where to invest attention or resources

Watch out for

• Different centrality measures can rank the same node very differently. Pick the one that matches the actual question
• High centrality is not the same as high quality or trustworthiness; it only measures structural position
• Networks change over time, so centrality snapshots can go stale

Related models

• Brokerage and Closure. Brokerage is a specific way central nodes create value by bridging gaps
• Small-world phenomenon. Related network property describing short path lengths between nodes
• Network building. A practical approach to increasing one’s own centrality
• Bottleneck. High betweenness centrality makes a node a broker or bottleneck.

Sources

Centrality measures (degree, betweenness, closeness) originate in social network analysis, with foundational work by Linton Freeman on centrality in social networks (1970s).