Sentiment analysis of non-English texts

Question

I want to analyze sentiment of texts that are written in German. I found a lot of tutorials on how to do this with English, but I found none on how to apply it to different languages.

I have an idea to use the TextBlob Python library to first translate the sentences into English and then to do sentiment analysis, but I am not sure whether or not it is the best way to solve this task.

Or are there any other possible ways to solve this task?

Answer 1

Now there is a pre-trained sentiment classifier for German text. Hugging Face has released two open-source APIs as follows.

1. oliverguhr/german-sentiment-bert
2. bert-base-german-cased-sentiment-Germeval17

Answer 2

As Andy has pointed about above, the best approach would be to train your own classifier. Another, more quick and dirty approach would be to use a German sentiment lexicon such as the SentiWS, and compute the polarity of a sentence simply on the basis of the polarity values of its individual words (for example by summing them). This method isn't foolproof (it doesn't take negation into account, for example), but it would give reasonable results relatively quickly.