Abstract: In sentiment analysis, sentiment dictionary is important because it affects the results of sentiment analysis. To build a sentiment dictionary, it is needed to classify the sentiment category of a word and to quantify its sentiment polarity strength. In English-based studies, it is easy to build an English sentiment dictionary to quantify the sentiment polarity strength of a word. However, such English sentiment dictionary is unsuitable for sentiment analysis of Korean documents. In Korean based studies, it is difficult to perform sentiment analysis for Korean documents precisely because most of Korean sentiment dictionaries with the sentiment polarity strength are built by surveys and the number of words is limited. In this study, we propose a method to automatically estimate the polarity index of a word using the synonyms and definitions information of words in a Korean dictionary. The experimental results show that the proposed method outperforms methods of using only one of the synonyms or definitions information.