Employing Questionnaire Knowledge to Japanese WordNet for Domain-Specific Sentiment Analysis

Abstract

Compared with computational language resources in English, word knowledge in Japanese for sentiment analysis is relatively under-developed. Sentiment axes have been used in Japanese psychological questionnaires for many years, and in this paper, we employ these axes for specific antonym relations in a word-relation network. The initial network is trained using target documents for sentiment analysis. We evaluate this trained word-relation network in several ways. First, we compare our results with a major sentiment-polarity dictionary. Then, we analyze the ex-tracted sentiment axes in each domain subjectively, along with the network's performance in predicting the grading of the reviews.