A social network's adjacency matrix represents connections between users. Which effect results when Principal Component Analysis (PCA) is performed on this matrix?

💡 Explanation

PCA identifies the principal components that capture the most variance in the data; therefore, applying PCA to the adjacency matrix reveals community structures with high interconnectivity, because it is a dimensionality reduction technique, rather than affecting communication or randomization.

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