Specifications and Analysis of the Korean Sentiment Analysis Corpus

Abstract

This paper describes the two year endeavor of constructing the Korean Sentiment Analysis Corpus (KOSAC), focusing on the theoretical background and the analysis of the corpus itself. Our aim is to provide a solid theoretical background for the corpus which reflects the characteristics of the Korean language and includes approximately 7,744 sentences taken from news articles. The corpus annotation scheme, based on the MPQA, is described along with the statistics of features specified in the corpus. The analysis of the corpus can be a starting point for how to utilize the corpus not only for sentiment analysis but also for semantic or pragmatic work in terms of speakers attitude and emotional expressions.