Syrupy Mouthfeel and Hints of Chocolate -- Predicting Coffee Review Scores using Text Based Sentiment
Computation and Language
2023-01-31 v1
Abstract
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.
Cite
@article{arxiv.2301.12417,
title = {Syrupy Mouthfeel and Hints of Chocolate -- Predicting Coffee Review Scores using Text Based Sentiment},
author = {Christopher Lohse and Jeroen Lemsom and Athanasios Kalogiratos},
journal= {arXiv preprint arXiv:2301.12417},
year = {2023}
}