Here, for example, we can see that all occupants of the social role "male" choose each other as friends no females choose each other as friends, and that males are more likely to choose females (3 out of 4 possibilities are selected) than females are to choose males (only 2 out of 4 possible choices). This kind of grouping of cells is often done in network analysis to understand how some sets of actors are "embedded" in social roles or in larger entities. Partitioning is also sometimes called "blocking the matrix," because partitioning produces blocks. Here we have partitioned by the actor by their sex. Passing these dividing lines through the matrix is called partitioning the matrix. Blocks are formed by passing dividing lines through the matrix (e.g. Each colored section is referred to as a block. We've also highlighted some sections of the matrix. None of the elements have had their values changed by this operation or rearranging the rows and columns, we have just shifted things around. Since the matrix is symmetric, if I change the position of a row, I must also change the position of the corresponding column. Matrix permutation ( Data>Permute) simply means to change the order of the rows and columns. Let's rearrange (permute) this so that the two males and the two females are adjacent in the matrix. Shifting rows and columns (if you want to rearrange the rows, you must rearrange the columns in the same way, or the matrix won't make sense for most operations) is called "permutation" of the matrix. It is also helpful, sometimes, to rearrange the rows and columns of a matrix so that we can see patterns more clearly.
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