The invention provides a bilingual sentiment classification method and device. The method comprises the steps of translating original language documents to be classified and the original language documents of a training sample set to obtain the translated documents to be classified and the translated documents of the training sample set; combining the original language documents to be classified and the translated documents to be classified to obtain a bilingual documents to be classified, and combining the original language documents of the training sample set and the translated documents of the training sample set to obtain bilingual documents of the training sample set; establishing a bilingual feature vector space to be classified and a bilingual feature vector space of the training sample set; training classifiers on the bilingual feature vector space of the training sample set by using a maximum entropy model; carrying out sentiment polarity classification on the bilingual feature vector space to be classified through the trained classifiers. The bilingual sentiment classification method and device combine the characteristics of two languages, provide extra classification information for the sentiment classification, improve classification accuracy, extract important characteristic items from the bilingual feature vector spaces, and improve classification efficiency.