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This paper uses textual data contained in certified (q-graded) coffee reviewsto predict corresponding scores on a scale from 0-100. By transforming thishighly specialized and standardized textual data in a predictor space, weconstruct regression models which accurately capture the patterns incorresponding coffee bean scores.

Syrupy Mouthfeel and Hints of Chocolate -- Predicting Coffee Review Scores using Text Based Sentiment