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Google Ngram viewer allows one to compare the frequencies of a set of phrases over time. It even allows you to restrict that comparison to an American corpus, or separately to an English one.

What I am wondering if there is any way to compare the frequency of one word/phrase over time between American and English? Either through Google Ngram or something else. I couldn't really find anything on google (itself or by using it).

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There's a scale. You can do two Ngrams and look at the numbers on the left. I don't know whether there's any software clever enough to combine them. –  Peter Shor Jun 20 '11 at 23:25
    
@PeterShor NGrams added a while ago specifying the corpus in a single query so you can compare side by side (see my new answer) –  Mitch Jun 8 at 19:49

2 Answers 2

up vote 6 down vote accepted

On Google's Ngram viewer you can set the corpus to be American English or British English, and get a graph for each. You can then compare the y-axis values, being careful to note that Google autoscales it.

For example: American English and British English.

You can also download the datasets of each corpus if you'd like to do your own data processing.

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But we mustn't forget that nGrams is a record drawn only from printed books. No newspapers, no magazines and, most importantly of all, no speech. –  Barrie England Jan 8 '12 at 10:21
    
@Barrie: Well, some newspapers and magazines have been re-published in books, and some are included, but you make a good point. –  Hugo Jan 8 '12 at 10:32
  • one solution is to compare frequencies in COCA (AmE) to those in BNC (British). You'll have to account for the size of the corpus as the 'denominator' though.

  • Google NGrams allows specifying as tags the corpus American or British. For example

    appropriation:eng_us_2012, appropriation:eng_gb_2012

will graph 'appropriation' over time for their American corpus against their British corpus. This isn't terribly recent (there's lots more new functionality there too) but it is slightly more recent than the time of the original question. All the usual caveats about using NGrams still apply (OCR, punctuation, grammar, polysemy, limited text, only written, etc)

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As usual, my condolences to ScE, IrE, AusE, NZE, SAfrE, and doubly so to those I leave out here. –  Mitch Jun 8 at 19:53

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