KOSAC: A Full-Fledged Korean Sentiment Analysis Corpus
نویسندگان
چکیده
This paper aims to introduce the Korean Sentiment Analysis Corpus named KOSAC. KOSAC is a corpus consisting of 332 news articles taken from the Sejong Syntactic Parsed Corpus. These sentences have been manually-tagged for sentimental features. The corpus includes 7,713 sentence subjectivity tags and 17,615 opinionated expression tags based on the annotation scheme called KSML which reflects the characteristics of the Korean language. The results of sentence subjectivity and polarity classification experiements using the corpus show the wide possibilities of application the KSML scheme and the tagged information of the KOSAC comprehensively to other corpus. What is innovative about our work is that it pulls together both the concept of private states and nested-sources into one linguistic annotation scheme. We believe that this corpus could be used by researchers as a gold standard for various NLP tasks related to sentiment analysis.
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