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Relationship weight property

As explained in Graph Algorithms for Data Science

A relationship weight property is a configuration setting that identifies the relationship attribute whose numeric values supply edge weights to a graph algorithm.

A relationship weight property identifies the relationship attribute whose numeric values provide edge weights for a graph algorithm. Weighted algorithm variants read this property through the relationshipWeightProperty configuration parameter. section 6.2.1 section 6.5

Weighted out-degree in a retweet network

Evaluate the weighted out-degree distribution of the inferred retweet amplification network by passing the relationship property name: CALL gds.degree.stats('amplify', {relationshipWeightProperty:'weight'}) YIELD centralityDistribution. The resulting distribution has a mean weighted out-degree of 4.715 and a maximum of 2,006.0078. section 6.2.1

Listing 6.5 Evaluating the weighted out-degree distribution of the inferred retweet amplification network
CALL gds.degree.stats('amplify', {relationshipWeightProperty:'weight'})
YIELD centralityDistribution

Inspect the executable GDS query that supplies weight as the relationship attribute. section 6.2.1

How Graph Algorithms for Data Science covers it

How deep it goes
Defines the parameter and demonstrates its use in a GDS distribution query, without detailing algorithm internals.
Examples
Uses a retweet amplification network whose weight property records repeated retweet activity.
What it assumes
Assumes a projected graph with relationships carrying a numeric property selected as the algorithm’s weight.
What you can do after
Apply it via GDS configuration to evaluate weighted out-degree distributions and identify high-weighted-degree nodes.
How it connects
Connects weighted degree centrality and PageRank with graph projections and relationship properties.
Cover of Graph Algorithms for Data Science
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