This workflow addresses the problem of extracting and modeling topics from reviews. Block 1 performs the data preparation on review texts. Block 2 optimizes the parameters for the LDA algorithm. Block 3 applies the LDA algorithm with optimized parameters and displays the LDA topic probabilities along with the average number of stars by topic. Block 4 estimates the importance of topics via linear regression (KNIME) and polynomial regression (R). If you use this workflow, please cite:
Used extensions & nodes
Created with KNIME Analytics Platform version 4.5.0
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