Yes, it is strange. The analysis takes words into account – here is the underlying wordlist. The words were created by Google and the process is described on page 12 of the revised online supplement of this paper as follows: > The tokenization process for Chinese was different. For Chinese, an internal CJK (Chinese/Japanese/Korean) segmenter was used to break characters into word units. The CJK segmenter inserts spaces along common semantic boundaries. Hence, 1-grams that appear in the Chinese simplified corpora will sometimes contain strings with 1 or more Chinese characters.

I think the problem is that the Chinese corpus is much smaller than the other corpora. A better way to create this graph might have been to only include words that occur at least once every say one million words, but this would have needed quite some code changes and I'm not sure it is better. Right now the count of the total number of words per language, the denominator in the y-axis, includes all "words".

Moreover, the Chinese corpus might be based on a more narrow selection of books than the other corpora, as a look at the list of most common 5-grams (sequences of 5 "words") reveals.