Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification
Table 4: Translation experiment. We translated each source language to each target language and used the model trained on the target language to predict tweets polarity.
['[BOLD] Source', '[BOLD] Target English', '[BOLD] Target Italian', '[BOLD] Target German', '[BOLD] Target French']
Translation Approach. The F1-score is higher when not translating tweets to another language for English, Italian and German. As an exception, we obtained better results when translating French to English and using the English model to predict sentiments.