On about 700 Starbucks reviews, SVM (91 percent) and BiLSTM (92 percent) outperformed eight other standard classifiers, in a routine benchmark with weak external validation.
Optimizing Sentiment Analysis on Imbalanced Hotel Review Data Using SMOTE and Ensemble Machine Learning Techniques,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches
On about 700 Starbucks reviews, SVM (91 percent) and BiLSTM (92 percent) outperformed eight other standard classifiers, in a routine benchmark with weak external validation.