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Regarding written English that isn't proofread ...
_[it's](http://theoatmeal.com/comics/apostrophe) quality
[definately](http://theoatmeal.com/comics/misspelling) leaves
[alot](http://hyperboleandahalf.blogspot.com/2010/04/alot-is-better-than-you-
at-everything.html)_ to be desired. I would advise people against treating
written English that wasn't professionally written (for example, mailing lists
or Stack Overflow questions) as good English.

Am I likely to pick up bad spelling or grammar from Japanese that is written
by native speakers but isn't professionally written?

Assume that I'm reading somewhat serious material, such as the ruby-dev
mailing list, rather than [YouTube](http://en.wikipedia.org/wiki/YouTube)
comments.

I'm not really planning on learning spelling and grammar from them, just
practicing reading the kana within the emails, but I don't want to mis-train
myself (learn something that isn't correct) by accident.

I've also heard warnings not to learn from Japanese done by the opposite sex -
sadly, I don't think there'd be too large a risk of that with a programming
mailing list!
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learning orthography publishing
Is Japanese that lacks proofreading likely to contain bad spelling or grammar?
Even the quality of professional writings (probably without proofreading) such
as an article in an online newspaper is very bad these days. For example, on
articles on an online news site [www.livedoor.com](http://www.livedoor.com),
which I regularly read, I usually find several grammatical mistakes each day.
You can only trust professional writings that are printed on paper.

I don't think it is a good idea in general to learn a language from sources
such as programmers' questions, but there are some points that may help you.

  * If something is just a simple mistake, then that should happen randomly, so the more you read, the more likely that that mistake that you wrongly picked up will be corrected. If it happens repeatedly, then that might be slang, or at least you are making the same kind of mistake as natives.

  * One common mistake you encounter on the internet is _誤変換_ 'misconversion'. Nowadays, in most cases, the kanji (Chinese character) parts of Japanese are not directly typed on a computer, but are input indirectly: First they are input by their reading, most often by hiragana, and then the user looks through the possible combinations of kanji matching the reading that the computer provides, and picks one. Sloppy people or people with a low education level often pick up the wrong one. For example, I often see `確立` where `確率` is supposed to be used. If you think that a word does not make sense in the context, you can suspect that it is meant to be a different kanji word with the same reading.

  * Another common mistake is the wrong use of particles. But they are not that frequent, and you will likely notice it when it is wrong if you read enough.
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The spelling and grammar are two different things. You might easily pick up
bad grammar because people (especially on the internet) tend to write as they
would speak. So I'd use caution when trying to pick up grammar this way.

However, with Japanese, spelling is hardly an issue. Since kana correspond to
sounds, if you can pronounce a word, then there is almost no chance you can
misspell it. The only time I think there might be misspellings is if you don't
recognize a long sound or a small っ in a word and would then not put it into
the word. Also, as @sawa mentioned, homophonic kanji may produce spelling
errors as well.
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This is something I've been wondering myself and the answers here so far have
been wonderful. I'm gunna add something different. I'm guessing you're a
programmer, so I think you might like to think about it like a programmer and
consider this question a question of [corpus
linguistics](http://en.wikipedia.org/wiki/Corpus_linguistics). I dunno if Ruby
has an [NLP](http://en.wikipedia.org/wiki/Natural_language_processing) package
(like [Python's NLTK](http://nltk.org/)) for Japanese but if it does and you
know how to use it, then you pretty much have an answer to your question.
Answers here could only tell you which textual domains are trustworthy for low
error rates and will likely not lead to mistraining (newspaper articles,
google blogs, etc), which domains have notoriously high error rates which will
lead to mistraining (youtube comments, etc) or what the most common types of
errors actually are by listing them. But if your goal is to avoid mistraining
while you read text in your browser, then your only task is to not fail in
identifying errors. So really you should be thinking about how to identify
errors given that you can't do it yourself because you're not a native
speaker.

"Am I likely to pick up bad spelling or grammar from Japanese that is written
by native speakers but isn't professionally written" In short, no. For the
grammatical errors, they are just as abundant in English as in Japanese as in
French as in etc. Unless you can explain why a Japanese native is more or less
likely to make a grammatical error than an English native? So if you trust the
English ruby dev mailing list, then for all practical purposes there is no
reason not to trust the Japanese dev mailing list.

I'm guessing basically that your question is one of
[likelihood](http://en.wikipedia.org/wiki/Likelihood): "how common are
grammatical errors" and "how common are spelling errors" where spelling is
using the wrong kanji or mistyping. If avoiding mistraining is your goal, then
to achieve that you only need to correctly identify errors.

For the spelling, just copy a representative text sample and past it into a
word processor like Word with Japanese spell check on and see how many red
squigglies appear. Add or subtract from the dictionary on specific instances
to train the spell checker. You can literally get an approximate numerical
answer to "how likely" a spelling mistake is given the specific textual
domain, such as a mailing list or newspaper articles in like 20 minutes. If
there isn't a spell checker then use [Kuromoji](http://www.atilika.org/).

Spelling errors aren't as straightforward as grammatical errors. The ideal way
to test for grammaticality is get a census from natives not a yes/no boolean
value. There should be a census on what qualifies as a blatant grammatical
error, so for example using the wrong preposition "print down a paper" instead
of "print out a paper" should have near 100% agreement from native speakers.
But something like "me and Bill" instead of "Bill and I" no doubt receives a
more fragmented census. So just create an index, then you decide based off
scores on the index whether or not that's something you want to adopt and
internalize. For example things higher up on the index are more reliably safe
to learn yourself.

For starters, the most unacceptable grammatical errors would be easy to
candidatentially identify, because they are by definition rare and so you
don't expect them to occur systematically. So in English the phrase "The
children never have waited" would occur infrequently in a corpus relative to
the phrases "The children {will/must/couldn't/should} have waited" which tells
you it _could_ be an error. The larger the corpus the more evidence you will
have in favour or against that hypothesis.

Looking at frequencies to identify erroneous constructions would have to be
supplemented by parsing the text. With a [syntax
tree](http://en.wikipedia.org/wiki/Concrete_syntax_tree) you could compare it
to a [syntax model](http://kheafield.com/code/kenlm/) of Japanese to compute
whether or not it's derivable. Use a [string
metric](http://en.wikipedia.org/wiki/String_metric), such as the [Levenshtein
distance](http://en.wikipedia.org/wiki/Levenshtein_distance), to define the
distance from a 100% grammatically correct syntax to get an index of
"ungrammaticality". Depending on how many rules you have you can make very
minute definitions on what is acceptable grammar. You should be able to do all
this on an NLP package.

If your corpus is something like Youtube comments, there is still something
you can learn from them. It seems that most comments are in sentence fragments
and inconsistent with punctuation. So you can't learn anything above the
phrase level from Youtube. That still leaves things like
[collocations](http://en.wikipedia.org/wiki/Collocation) (frequent word
pairings) to learn. A lot of what natives think is grammatical is actually
just collocational. When you ask a native if something is grammatical and they
say yes but tell you not to say it because people just don't say it, then the
thing in question is in reality probably just a collocation, so if you want
good language habits, you need to learn collocations.

In terms of practical learning and not just theory, what I think you would
want to do is write a text filter, maybe in Javascript with
[TinySegmenter](http://chasen.org/~taku/software/TinySegmenter/) or something,
so that you could visit a website, run the Javascript, and use a color scheme
(that corresponds to the computed index) to highlight text that, according to
your script, deems bad grammar. Red for the blatant unquestionable errors,
orange for errors that are more tolerable, etc. The point is to identify
errors on the page as you read the text. If this is done, then there's no risk
of mistraining.
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