Principal Component Analysis (PCA) was a favorite technique of ours for a long time, because it addressed the dimensionality of a problem, So important for problems that had many socially influenced dimensions. These problems also typically had relatively sparse data, because it could be expensive to obtain. Here a good example of PCA in R, and motivation for its use. Worth knowing.
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