I want to compare two corpora. One with 15000 tokens and the other with 5000 tokens. Can I normalise the word frequencies per 100000 words? Or I have to normalise based on words per million?
Whether you normalise by 100,000 or 1,000,000 words is essentially a question of style and/or common practice in the journal or sub-field you're in. Mathematically, it makes not difference at all whether you say feature x occurs with a frequency of 10 per 100,000 words or 100 per 1,000,000 words. But you should be consistent, so if you provide other normalised frequencies or compare your results with previous findings, use the same normalisation index. In my experience, most corpus linguists give relative frequencies per million words, this is usually abbreviated as pmw. Some authors prefer normalisation per 100,000 words and call this the Mossé index, but this is in my experience relatively rare.
The only reason you might want to normalise by a smaller figure (e.g. per 1,000 words) is that some readers might interpret a frequency pmw as suggesting that you actually had a corpus of 1 M. words, not a (relatively small) 5,000 word corpus. So if you give no other normalised figures (from your own or other people's studies), it might be preferable to normalise by 1,000 words - especially if your audience is not very well acquainted with corpus linguistic methods.