Paper: Joint Bilingual Sentiment Classification with Unlabeled Parallel Corpora

ACL ID P11-1033
Title Joint Bilingual Sentiment Classification with Unlabeled Parallel Corpora
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

Most previous work on multilingual sentiment analysis has focused on methods to adapt sentiment resources from resource-rich languages to resource-poor languages. We present a novel approach for joint bilingual sentiment classification at the sentence level that augments available labeled data in each language with unlabeled parallel data. We rely on the intuition that the sentiment labels for parallel sentences should be similar and present a model that jointly learns improved mono- lingual sentiment classifiers for each language. Experiments on multiple data sets show that the proposed approach (1) outperforms the mono- lingual baselines, significantly improving the accuracy for both languages by 3.44%-8.12%; (2) outperforms two standard approaches for leveraging unlabele...