Fine-grained sentiment analysis with 32 dimensions

Understanding human's complicated and capricious emotions remains a fundamental challenge. In this paper, we propose a fine-grained sentiment analysis system which classify emotions into 32 categories. For one direction, we cover more detailed emotions and for the other direction, we further measure each emotion with strength, such as describing angry by annoyance, anger and range. Taking Japanese as a test language, we describe our methods of building the training data, of constructing deep neural network classifiers, and of evaluating the models.