The larger an encoding dimension in NLP the better?
No, it isn't that way. From my personal experience, I have built custom word2vec's to some datasets and observed that at times, shorter vectors did better than longer ones. I think you can try shorters length vectors for smaller datasets. I cannot tell any metric in specific for comparison of dataset size and word2vec length though.