to the best of my knowledge:
1. SVD
2. therefore either rotated or unrotated eigenvectors, depending on 'allow correlated topics' node property setting
3. no, the topics are somewhat correlated whilst within-vector variance is minimised, which in turn increases the likelihood of a human interpreting the topic theme with a more relevant, grammatical phrase, based on the most influential topic terms.
If I'm wrong, I'd appreciate a correction.
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