Language-Specific Sentiment Analysis in Morphologically Rich Languages
نویسندگان
چکیده
In this paper, we propose languagespecific methods of sentiment analysis in morphologically rich languages. In contrast of previous works confined to statistical methods, we make use of various linguistic features effectively. In particular, we make chunk structures by using the dependence relations of morpheme sequences to restrain semantic scope of influence of opinionated terms. In conclusion, our linguistic structural methods using chunking improve the results of sentiment analysis in Korean news corpus. This approach will aid sentiment analysis of other morphologically rich languages like Japanese and Turkish.
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