edu.uci.ics.jung.algorithms.importance
Class BetweennessCentrality
java.lang.Object
edu.uci.ics.jung.algorithms.IterativeProcess
edu.uci.ics.jung.algorithms.importance.AbstractRanker
edu.uci.ics.jung.algorithms.importance.BetweennessCentrality
- public class BetweennessCentrality
- extends AbstractRanker
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.RelativeBetweennessCentrality'
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:
RelativeBetweennessCentrality ranker = new RelativeBetweennessCentrality(someGraph);
ranker.evaluate();
ranker.printRankings();
Running time is: O(n^2 + nm).
- Author:
- Scott White
- See Also:
- "Ulrik Brandes: A Faster Algorithm for Betweenness Centrality. Journal of Mathematical Sociology 25(2):163-177, 2001."
Method Summary |
java.lang.String |
getRankScoreKey()
the user datum key used to store the rank scores |
Methods inherited from class java.lang.Object |
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
CENTRALITY
public static final java.lang.String CENTRALITY
- See Also:
- Constant Field Values
BetweennessCentrality
public BetweennessCentrality(Graph g)
- Constructor which initializes the algorithm
- Parameters:
g
- the graph whose nodes are to be analyzed
BetweennessCentrality
public BetweennessCentrality(Graph g,
boolean rankNodes)
getRankScoreKey
public java.lang.String getRankScoreKey()
- the user datum key used to store the rank scores
- Specified by:
getRankScoreKey
in class AbstractRanker
- Returns:
- the key