How to assess customer opinions beyond language barriers?

Abstract

The main focus of this paper is to introduce an approach to sentiment classification for documents in different languages. The method is based on language-specific resources available for English. First, documents are translated to English using standard translation software. For polarity detection, sentiment-bearing terms are identified by means of SentiWordNet. Polarity scores calculated for words of three word classes are exploited by a machine learning classifier for determining the document polarity. The introduced method is tested and evaluated on movie reviews in six different languages. The results show that polarity can be correctly determined even if language specific resources are unavailable.