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Cross-Lingual Mixture Model for Sentiment Classification
2012
Annual Meeting of the Association for Computational Linguistics
The amount of labeled sentiment data in English is much larger than that in other languages. Such a disproportion arouse interest in cross-lingual sentiment classification, which aims to conduct sentiment classification in the target language (e.g. Chinese) using labeled data in the source language (e.g. English). Most existing work relies on machine translation engines to directly adapt labeled data from the source language to the target language. This approach suffers from the limited
dblp:conf/acl/MengWLZXW12
fatcat:pdb3natzfvhv5mcgnpfy5m5734