Contents - Index


PURPOSE Produces a hierarchically nested set of vertices based on betweenness.

DESCRIPTION The betweenness of each vertex is calculated and those with a score of zero are deleted, the procedure is then repeated on the reduced graph until all vertices have been deleted. Initially all vertices are placed in the hierarchy and then at each level the deleted vertices are removed. 

Input dataset:
Name of file containing network to be analyzed. Data type: Digraph.
(Output)  (Default = 'hierbet').
Name of file which will contain the partition vector. The vector consists of a single row with each column corresponding to a vertex. A value k in column i means that actor i was deleted after k iterations.

(Output) Partition (Default =hierbetpart)
Name of dataset to contain the partition-by-item incidence matrix. Each column of this matrix corresponds to a cluster  labeled by the level of the cluster.  A value of 1 in a column labeled x and row j means that actor j was in the cluster at level x. 

LOG FILE The partition vector described above. A cluster diagram in which the columns have been re-arranged so that actors in the same cluster at each level are consecutive. A value of 1 in a row labeled x and column labeled j means that actor j was in the cluster at level x. 


REFERENCES Freeman L C (1979).  'Centrality in Social Networks: Conceptual Clarification'.  Social Networks 1, 215-239.