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.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).
- Author:
- Scott White
- See Also:
- "Ulrik Brandes: A Faster Algorithm for Betweenness Centrality. Journal of Mathematical Sociology 25(2):163-177, 2001."
Methods inherited from class edu.uci.ics.jung.algorithms.importance.AbstractRanker |
assignDefaultEdgeTransitionWeights, finalizeIterations, getEdgeWeight, getEdgeWeightKeyName, getGraph, getRankings, getRankScore, getRankScores, getVertices, initialize, isRankingEdges, isRankingNodes, normalizeEdgeTransitionWeights, normalizeRankings, onFinalize, printRankings, reinitialize, setEdgeWeight, setNormalizeRankings, setRankScore, setRemoveRankScoresOnFinalize, setUserDefinedEdgeWeightKey |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
CENTRALITY
public static final 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)
BetweennessCentrality
public BetweennessCentrality(Graph g,
boolean rankNodes,
boolean rankEdges)
computeBetweenness
protected void computeBetweenness(Graph graph)
getRankScoreKey
public String getRankScoreKey()
- the user datum key used to store the rank scores
- Specified by:
getRankScoreKey
in class AbstractRanker
- Returns:
- the key
evaluateIteration
protected double evaluateIteration()
- Description copied from class:
IterativeProcess
- Evaluate the result of the current interation.
- Specified by:
evaluateIteration
in class IterativeProcess
- Returns:
- the estimated precision of the result.