Abstract
In this paper, we present a method for estimating the sentiment polarity of Japanese sentences including onomatopoeic words. Onomatopoeic words imitate the sounds they represent and can help us understand the sentiment of the sentence. Although there are many onomatopoeic words in Japanese, conventional sentiment classification methods have not taken them into consideration. The sentiment polarity of onomatopoeic words can be estimated using the sound symbolism derived from their vocal sounds. Our experimental results show that the proposed method with sound symbolism can significantly outperform the baseline method that is not with sound symbolism.
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Igarashi, T., Sasano, R., Takamura, H., Okumura, M. (2012). The Use of Sound Symbolism in Sentiment Classification. In: Anthony, P., Ishizuka, M., Lukose, D. (eds) PRICAI 2012: Trends in Artificial Intelligence. PRICAI 2012. Lecture Notes in Computer Science(), vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_67
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DOI: https://doi.org/10.1007/978-3-642-32695-0_67
Publisher Name: Springer, Berlin, Heidelberg
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