Syrupy Mouthfeel and Hints of Chocolate -- Predicting Coffee Review Scores using Text Based Sentiment
This paper uses textual data contained in certified (q-graded) coffee reviews to predict corresponding scores on a scale from 0-100. By transforming this highly specialized and standardized textual data in a predictor space, we construct regression models which accurately capture the patterns in corresponding coffee bean scores.
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