Sentiment Analysis for Multilingual Corpora

The paper presents a generic approach to the supervised sentiment analysis of social media content in foreign languages. The method proposes translating documents from the original language to English with Google's Neural Translation Model. The resulted texts are then converted to vectors by averaging the vectorial representation of words derived from a pretrained Word2Vec English model. Testing the approach with several machine learning methods on Polish, Slovenian and Croatian Twitter corpora returns up to 86 % of classification accuracy on the out-of-sample data.