Closeness centrality mutatealgorithm

The closeness centrality mutate algorithm computes a Closeness Centrality (CC) metric for specified nodes in a graph. The CC metric of a node can be used as a positive measure of how close it is to all other nodes or how central it is in the graph.

The CC metric can be interpreted to show how quickly all other nodes in a network can be reached from a given node, and how important it is as a central hub for rapid information flow. It can be used in transportation networks to identify key hub locations, and in disease-spread modeling to pinpoint central points for targeted intervention efforts.

The closeness centrality (CC) score of a node is calculated based on the sum of its distances to all other vertices. The CC score itself is the inverse of that number; in other words, one divided by that sum. In practice, the calculation is commonly normalized to use the average length of the shortest paths rather than the actual sum of their lengths.

.closenessCentrality.mutate  syntax

CALL neptune.algo.closenessCentrality.mutate(
  [node list (required)],
  {
    numSources: the number of BFS sources to use for computing the CC (required)
    writeProperty: name of the node property to write the CC score to (required)
    edgeLabels: [a list of edge labels for filtering (optional)],
    vertexLabel: "a node label for filtering (optional)",
    traversalDirection: traversal direction (optional),
    normalize: Boolean, set to false to prevent normalization (optional)
    concurrency: number of threads to use (optional)
  }
)
YIELD success
RETURN success

.closenessCentrality.mutate  inputs

.closenessCentrality.mutate  outputs

The closeness centrality score of each source node in the input list is written as a new node property using the property name specified in writeProperty.

If the algorithm is invoked as a standalone query, there is no other output.

If the algorithm is invoked following a MATCH clause that provides its source node list (query integration), the algorithm outputs a key column of the source vertices from the MATCH clause and a value column of Booleans (true or false) that indicate whether the CC value was successfully written to the node in question.

Query examples for  .closenessCentrality.mutate

This example computes closeness centrality scores and writes them as a new node property called ccScore:

CALL neptune.algo.closenessCentrality.mutate(
  {
    numSources: 10,
    writeProperty: "ccScore",
    edgeLabels: ["route"],
    vertexLabel: "airport",
    traversalDirection: "outbound",
    normalize: true,
    concurrency: 1
  }
)

Then you can query the ccScore property in a subsequent query:

MATCH (n) RETURN id(n), n.ccScore limit 5

Sample   .closenessCentrality.mutate   output

Here is an example of the output returned by .closenessCentrality.mutate when run against the sample air-routes dataset [nodes], and sample air-routes dataset [edges], when using the following query:

aws neptune-graph execute-query \
  --graph-identifier ${graphIdentifier} \
  --query-string "CALL neptune.algo.closenessCentrality.mutate(
       {
         writeProperty: 'ccscore',
         numSources: 10
       }
     )
     YIELD success
     RETURN success"
  --language open_cypher \
  /tmp/out.txt
  
cat /tmp/out.txt  
{
  "results": [
    {
      "success": true
    }
  ]
}