Class BetweennessCentrality<V,E>

All Implemented Interfaces:
IterativeContext

public class BetweennessCentrality<V,E> extends AbstractRanker<V,E>
Computes betweenness centrality for each vertex and edge in the graph. The result is that each vertex and edge has a UserData element of type MutableDouble whose key is 'centrality.BetweennessCentrality'. Note: Many social network researchers like to normalize the betweenness values by dividing the values by (n-1)(n-2)/2. The values given here are unnormalized.

A simple example of usage is:

 BetweennessCentrality ranker = new BetweennessCentrality(someGraph);
 ranker.evaluate();
 ranker.printRankings();
 
Running time is: O(n^2 + nm).
See Also:
  • "Ulrik Brandes: A Faster Algorithm for Betweenness Centrality. Journal of Mathematical Sociology 25(2):163-177, 2001."
  • Field Details

  • Constructor Details

    • BetweennessCentrality

      public BetweennessCentrality(Graph<V,E> g)
      Constructor which initializes the algorithm
      Parameters:
      g - the graph whose nodes are to be analyzed
    • BetweennessCentrality

      public BetweennessCentrality(Graph<V,E> g, boolean rankNodes)
    • BetweennessCentrality

      public BetweennessCentrality(Graph<V,E> g, boolean rankNodes, boolean rankEdges)
  • Method Details