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You are analyzing a dataset of customer reviews for a Generative A1-powered product. You want to identify the key themes and topics that customers are discussing. Which technique would be MOST appropriate for this task?
Correct Answer: B
Topic modeling is specifically designed to discover the underlying themes and topics within a collection of documents (in this case, customer reviews). LDA (Latent Dirichlet Allocation) and NMF (Non-negative Matrix Factorization) are common topic modeling techniques. Sentiment analysis provides an overall sentiment score but doesn't identify specific themes. Regression analysis is for prediction, not theme discovery. Clustering groups customers, not review topics. Time series analysis tracks changes over time, not themes.