How to setup text analytics when having multiple languages?

There are two things you can think of. I always recommend supervised text analytic systems and there are two ways to train them.

One way is that you auto translate everything into a main language. For instance, English, then have an English coder, teaching the AI. That’s one way.

The other way is to have another native coder and teacher. Everyone teaches the AI in native language.

Both approaches has pros and cons. There is no way which is just better. The con of the translation is obviously you loose some information, while translating it , but the disadvantage of having native teachers is that you cannot make sure that they really understand every category in every topics, the same way. You cannot make sure that they really code the same way. If you end up at least with more than three languages, we recommend to auto translate into one language.

That’s typically what we do and actually what’s not so well known so far is that there is an even much better translation machine than Google translate in the market it’s called Deepl.com.

It has been proven to be much more precise than google translate and for all systems, we use that machine to auto translate every single one language.