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. Common measures include degree centrality (how many direct connections a node has), betweenness centrality (how often a node sits on the shortest path between other nodes, making it a broker or bottleneck), and closeness centrality (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
- Define the network: who or what are the nodes, and what counts as a connection
- Choose the centrality measure that fits the question (degree for popularity, betweenness for brokerage, closeness for reach)
- Compute or estimate centrality and compare nodes relative to each other
- 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
Sources
Centrality measures (degree, betweenness, closeness) originate in social network analysis, with foundational work by Linton Freeman on centrality in social networks (1970s).