Betweenness centrality measures a node's influence on the flow of information or resources through the entire network. It is defined by counting the number of shortest paths that pass through a specific node, rather than just counting direct connections.
Conditions: Requires the concept of shortest paths.; Applies to networks where flow or routing is relevant.
Betweenness centrality measures a node's influence on the flow of information or resources through the entire network. It is defined by counting the number of shortest paths that pass through a specific node, rather than just counting direct connections.
Conditions: Requires the concept of shortest paths.; Applies to networks where flow or routing is relevant.
In directed networks, degree centrality is split into two distinct metrics based on edge direction. In-degree counts the number of edges flowing into a node, while out-degree counts the number of edges flowing out of the node.
Conditions: Applies to directed networks where edges have a specific direction.
In directed networks, degree centrality is split into two distinct metrics based on edge direction. In-degree counts the number of edges flowing into a node, while out-degree counts the number of edges flowing out of the node.
Conditions: Applies to directed networks where edges have a specific direction.