Using bilingual knowledge and ensemble techniques for unsupervised Chinese sentiment analysis
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Predicting the semantic orientation of terms in E-HowNet
ROCLING '11 Proceedings of the 23rd Conference on Computational Linguistics and Speech Processing
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Computer Speech and Language
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It is a challenging task to identify sentiments (the affective parts of options) of reviews. One of the most important problems is to predict the sentiment orientation of the words. This paper proposes a new method for determining the sentiment orientation of the Chinese words by using bilingual lexicons. Given a Chinese word, we observe the occurrences of English sentiment words in its interpretations, to predict the sentiment orientation of the Chinese word. The whole process can be illustrated logically as follows: (1) translate a Chinese word into Chinese-English interpretation; (2) generate an English word sequence by parsing the interpretation; (3) calculate the sentiment vector from the English word sequence; (4) use a classifier to predict the sentiment orientation for the Chinese word. The performance of two kinds of classifiers (SVM and C4.5) is studied. The experiments show that the proposed method performed well and achieved high accuracy.