Should I seperate the data for a k-means model? I would like to cluster some user reviews and I'm doing this with k-means. In my dataset I have English and German reviews. Is this manipulating the cluster result if I don't seperate them? Or should I do a k-means prediction on each language?
Yes you should definitely split these two up. When calculating the TF-TDF matix, it will give different terms to objects of the same entity, because of the difference in language. This will affect your clustering results.