Comparative Experiments for Multilingual Sentiment Analysis using Machine Translation

Sentiment analysis is the Natural Language Processing task dealing with sentiment detection and classification. In the past few years, there has been a steady increase in the interest towards this task, for which different methods and resources have been proposed. Sentiment analysis has been studied in the context of traditional media, but also the new social media. Nevertheless, the research community has concentrated less on developing methods for languages other than English.Motivated by this fact, the present article deals with the problem of sentiment detection in three different languages - French, German and Spanish - using three distinct Machine Translation (MT) systems - Bing, Google and Moses, using supervised methods with different combinations of features. Our extensive evaluation scenarios show that SMT systems are approaching a good level of maturity and can start to be employed to obtain training data for languages other than English and that sentiment analysis systems can obtain comparable performances to the one obtained for English.

BALAHUR DOBRESCU Alexandra;  TURCHI Marco; 

2013-01-10

CEUR Workshop Proceedings

JRC73295

1613-0073,   

http://ceur-ws.org/Vol-917/,    https://publications.jrc.ec.europa.eu/repository/handle/JRC73295,