Context-aware Natural Language Generation with Recurrent Neural Networks
Table 7: Binary sentiment classification. Results on the true and fake reviews are very close.
['Domain', 'Data', 'Precision', 'Recall', 'F1']
To conduct the classification, we randomly sample one 100,000 real reviews from the training data for training the sentiment classifier. As for the evaluation data, a fake review is generated for each test data according to its contexts. We can see that the results on the real and fake reviews are very close to each other. On some domains (e.g., Book and Movie), the results on the fake reviews are even better than the real reviews, showing that the reviews generated by the gC2S model accurately reflect the sentiment polarity.