Documentation of 'edu.uci.ics.jung.algorithms.importance.BetweennessCentrality' Java class
BetweennessCentrality
edu.uci.ics.jung.algorithms.importance

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."
    • Constructor Detail

      • 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)

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