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Illustration: Ludwig Pettersson Loading… Share A linear model⁠ using this representation achieves state-of-the-art sentiment analysis accuracy on a small but extensively-studied dataset, the Stanford Sentiment Treebank (we get 91.8% accuracy versus the previous best of 90.2%), and can match the performance of previous supervised systems using 30-100x fewer labeled examples. Our representation also contains a distinct “ sentiment neuron⁠” which contains almost all of the sentiment signal. Our system beats other approaches on Stanford Sentiment Treebank while using dramatically less data. The number of labeled examples it takes two variants of our model (the green and blue lines) to match fully supervised approaches, each trained with 6,920 examples (the dashed gray lines). 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