The link to http://emojitracker.com/ in the near-duplicate question I personally think is the most promising resource for this. I have not examined the sources (I don't speak Ruby) but from a real-time Twitter feed of character frequencies, I would expect quite a different result than from static web pages, and probably a radically different language distribution (I see lots more Arabic and Turkish on Twitter than in my otherwise ordinary life). It's probably not exactly what you are looking for, but if we just look at the title of your question (which probably most visitors will have followed to get here) then that is what I would suggest as the answer.
Of course, this begs the question what kind of usage you attempt to model. For static XML, which you seem to be after, maybe the Common Crawl set is a better starting point after all. Text coming out of an editorial process (however informal) looks quite different from spontaneous text.
Out of the suggested options so far, Wikipedia (and/or Wiktionary) is probably the easiest, since it's small enough for local download, far better standardized than a random web dump (all UTF-8, all properly tagged, most of it properly tagged by language and proofread for markup errors, orthography, and occasionally facts), and yet large enough (and probably already overkill by an order of magnitude or more) to give you credible statistics. But again, if the domain is different than the domain you actually want to model, they will probably be wrong nevertheless.
