A Multilingual Polarity Classification Method using Multi-label Classification Technique Based on Corpus Analysis
نویسنده
چکیده
In NTCIR-7 MOAT, we participated in four sub-tasks (opinion & holder detection, relevance judg-ment, and polarity classification) at two languagesides: Japanese and English. In this paper, we fo-cused on the feature selection and polarity classifi-cation methodology in both languages. To detectopinion and classify the polarity, the features wereselected based on a statistical χ-square tests overNTCIR-6 and MPQA corpora. We also comparedseveral multi-label classification methods to clas-sify positive, negative, and neutral polarity. Theevaluation results suggested that the coverage ofthe features in Japanese was acceptable for theopinion analysis in newspaper articles, but therewas still a room for improvement in the coverageof the features in English. We also found the resultof SVM voting approach was slightly better thanthe results of Multi-label classification approach.
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