Name of output file which contains a cluster indicator vector for the row partition. This vector has the form (k1,k2,...ki...) where ki assigns vertex i to cluster ki and ki is either 1 or 2 where 1 is the core and 2 is the periphery, so that (1 1 2 1 2) assigns vertices 1, 2 and 4 to the core, and 3 and 5 to the periphery. This vector is not displayed at output.

Name of output file which contains a cluster indicator vector for the column partition. This vector has the form (k1,k2,...ki...) where ki assigns vertex i to cluster ki and ki is either 1 or 2 where 1 is the core and 2 is the periphery, so that (1 1 2 1 2) assigns vertices 1, 2 and 4 to the core, and 3 and 5 to the periphery. This vector is not displayed at output.

The algorithm seeks to find the maxima of the cost function. Even if successful this result may still be a low value in which case the partition may not represent a core/periphery model.

In addition there may be a number of alternative partitions which also produce the maximum value; the algorithm does not search for additional solutions. Finally it is possible that the routine terminates at a local maxima and does not locate the desired global maxima.

To test the robustness of the solution the algorithm should be run a number of times from different starting configurations. If there is good agreement between these results then this is a sign that there is a clear split of the data into a core/periphery structure.

Borgatti SP and Everett M G (1997) Network analysis of 2-mode data. Social Networks 19 243-269