Clustering | Network Encyclopedia
What is Clustering?
Clustering in network science refers to the tendency of nodes to form tightly connected groups or triangles. A cluster occurs when a node’s neighbors are also connected to one another, creating a denser local network. The concept is often quantified using the Clustering Coefficient, which measures the proportion of a node's neighbors that are also connected to each other.
At the network level, the Average Clustering Coefficient provides insight into how interconnected the network is overall. High clustering indicates a tightly-knit network with strong local connections, while low clustering suggests a more dispersed structure.
An Example of Clustering
In a workplace network, clustering occurs when employees who work closely with a manager are also collaborating with one another. For example, in a project team, high clustering would mean that most team members regularly interact with one another, creating a strong group dynamic.
Interpreting the Clustering Coefficient
- High Clustering: Networks with high clustering often indicate close-knit communities or subgroups. This is common in social networks or collaborative teams where trust and frequent interaction foster dense local connections.
- Low Clustering: Networks with low clustering suggest fewer interconnections among neighbors. This could indicate a more hierarchical structure or a network with weaker local cohesion.
Why Study Clustering?
Clustering provides insights into the social structure and collaboration patterns within a network. High clustering can signify resilience and trust within subgroups, while low clustering might highlight opportunities to strengthen connections. Organizations can use clustering analysis to identify strong local groups, encourage cross-group interaction, or address silos by connecting isolated clusters.