Aspect-Based Relational Sentiment Analysis Using a Stacked Neural Network Architecture
Table 2: Performances for aspect and opinion phrase extraction on the USAGE dataset for joint and separate models. Joint small and Joint large are the joint models with hidden layer size 100-50-50-50-100 and 100-100-100-100-200, respectively.
['Model', 'Aspects  [ITALIC] P', 'Aspects  [ITALIC] R', 'Aspects  [ITALIC] F1', 'Opinions  [ITALIC] P', 'Opinions  [ITALIC] R', 'Opinions  [ITALIC] F1']
This section investigates the benefits of predicting aspect and opinion phrases of the USAGE corpus jointly in one model, in contrast to two separate models. For this, we consider two joint models with different hidden layer sizes, namely with 100-50-50-50-100 (dubbed Joint small) and 100-100-100-100-200 (dubbed Joint large). This should account for differences in performance that solely result from different network capacities.