The Centrality algorithm places data based on networks of connected objects. This placement determines the root object of each network based on connection counts and lets you choose how the algorithm weights
the connections. Centrality facilitates Social Network Analysis quickly exposing the objects with the most
influence over other objects within the network. Centrality can be displaying using any several measures
to identify the root of each network:
- Degree – Determines the root by identifying the object with the most direct connections to other objects within the network. This finds the object with the most influence over the network.
- Closeness – Determines the root as the object with the lowest number of links to all other objects within the network. This finds the object with the quickest access to the highest number of other objects within the network.
- Betweenness – Determines the root as the object between the most other linked objects. This measure finds objects that control the information flow of the network, sometimes referred to as “gatekeepers.”
This example shows a centric, or circular, layout of the Centrality Placement. The objects at the center of each network represent the root objects – those directly connected with the highest number of other objects within the network.
This example shows a hierarchical layout of the Centrality Placement. The objects to the left of each network represent the root – or most connected – objects within the network.
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