hub algorithm influence

Runs the influence algorithm on a model and saves the results for each entity to a model property. The influence algorithm reflects the importance of an entity, based on its connections to high-scoring entities.

Centrality algorithms measure the importance and significance of individual entities and relationships. When you run centrality algorithms, the value returned by an algorithm indicates the importance of an element. The influence algorithm implements Eigenvector Centrality to measure the transitive influence or connectivity of entities. Relationships to high-scoring entities contribute more to the score of an entity than connections to low-scoring nodes. A high score means that an entity is connected to other entities that have high scores.

Usage

hub algorithm influence --m model --d direction --p precision --wp weightProperty --lvsignificantLowValues --op outputProperty --w waitForComplete

Required	Argument	Description
Yes	--m `model`	Specifies the model.
No	--d `direction`	Specifies the direction to apply to the algorithm where `direction` is one of the following: in The results will be based on incoming relationships on the entity. out The results will be based on outgoing relationships on the entity. both The results will be based on both incoming and outgoing relationships on the entity. This is the default value.
No	--p `precision`	Specifies how precise the results should be. A lower precision will return more accurate results, but the algorithm will run more slowly. This argument may be set between 0.00001 and 0.1. The default is 0.01.
No	--wp `weightProperty`	Specifies a relationship property to use to measure how unfavorable a relationship is. By default, a higher value indicates a negative association. The default setting is null.
No	--lv `significantLowValues`	If a relationship property is used as weight, this specifies whether a lower value is considered better than a higher value. true Specifies that a lower value is considered better than a higher value for a relationship property used as weight. For example, if the property is some sort of ranking system, 1 or 1st would be considered the best value. If the property is distance, and you are trying to determine the shortest route, 5 miles would be considered better than 10 miles. false Specifies that a higher value is considered better than a lower value for a relationship property used as weight. This is the default value.
No	--op `outputProperty`	Specifies the output property name to be something other than the algorithm name. The default is Influence.
No	--w `waitForComplete`	Specifies whether to wait for jobs to complete in a synchronous mode. true Specifies to wait for jobs to complete in a synchronous mode. false Specifies to not wait for jobs to complete in a synchronous mode. This is the default value.

Example

The following command line runs the algorithm on the 911 model.

hub algorithm influence --m 911