Abstract
The exploding Web opinion data has the essential need for automatic tools to analyze people’s sentiments in many fields. Predicting the polarity of a product review is an important work in applications such as market investigation and trend analysis. In this paper, we focus on analyzing the Chinese sentiment word strengths and the sentiment drop point. We propose a novel algorithm based on the sentiment drop point algorithm to conduct sentiment polarity assignment. It predicts the sentiment polarity by a determinative policy which involves two classifiers simultaneously. The experiments show that our approach is efficient and suited for reviews analysis in different domains.
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Hao, Z., Cheng, J., Cai, R., Wen, W., Wang, L. (2013). Chinese Sentiment Classification Based on the Sentiment Drop Point. In: Huang, DS., Gupta, P., Wang, L., Gromiha, M. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2013. Communications in Computer and Information Science, vol 375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39678-6_10
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DOI: https://doi.org/10.1007/978-3-642-39678-6_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39677-9
Online ISBN: 978-3-642-39678-6
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