Towards Controllable and Personalized Review Generation
Table 3: Confusion Matrix of Empirical Test
['Empirical Test', 'Actual Value Human-Written', 'Actual Value RevGAN']
Besides the statistical and semantical metrics, we also design an empirical study to test the personalized performance of our generated reviews. We randomly select 15 reviews to include in each questionnaire, 5 from the original dataset, 5 from RevGAN generated results with personalization and 5 from RevGAN generated results without personalization, and ask participants to analyze which ones are generated by the machine and which ones are really created by humans. Besides, they are also asked to assess the helpfulness of each review by choosing the helpfulness score scale 1-5 for each review. To test that whether the RevGAN generated reviews are indeed statistically indistinguishable from original ones, we run chi-test for significance testing: χ2=0.012