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Calculates the betweenness centrality for each node in the network. Betweenness centrality is a measure of the number of times a node acts as a bridge along the shortest path between two other nodes.

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Usage

The following example shows how the step can be used in a recipe.

Examples

extract_node_betweenness(ds.targets, ds.weights) -> (ds.betweenness)

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Inputs & Outputs

The following are the inputs expected by the step and the outputs it produces. These are generally columns (ds.first_name), datasets (ds or ds[["first_name", "last_name"]]) or models (referenced by name e.g. "churn-clf").
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targets
column[list[number]]
required
A column containing link targets. Source is implied in the index.
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*weights
column[list[number]]
An optional column containing link weights.
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betweenness
column[number]
required
A column containing the betweenness metric for each node/row.

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Configuration

The following parameters can be used to configure the behaviour of the step by including them in a json object as the last “input” to the step, i.e. step(..., {"param": "value", ...}) -> (output).

Parameters

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directed
boolean
default:"false"
Whether the links are directed or not.
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cutoff
[number, null]
The maximum path length to consider when calculating the betweenness. If cutoff is zero or negative then there is no such limit.