The use of matrices to describe social relations is as follows:
Transform a block operation allows us to select a matrix to be blocked, a row and/or column partition and a method for calculating the entries in a resulting block. We first split the row and column partition. These are just data sets which we then group to form partitioned data sets.  This operation requires a method for summarizing the information within each block. The operation outputs two new matrices. The PreImage data set contains the original scores, but permuted. The reduced image data set contains a new block matrix containing the block densities.
The Transform collapse method allows us to combine rows and/or columns by specifying which elements are to be combined and how. Combinations can be maximum, minimum and sum. The result of the combinations is a new matrix with specified operation performed.
The Data -> Permute allows us to re-arrange the rows and/or columns and/or matrices.  This operation requires us to list the new orders method needed.
The Data->Sort re-arranges the  rows, columns or both of the matrix according to a criterion we select.
The Data-> Transpose re-arranges the data in a way that is very commonly used in matrix algebra and switches the columns with the rows.