Template:R:GNV

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{{{1}}} at the Google Books Ngram Viewer.


Use this template to link to the Google Books Ngram Viewer, showing time-dependent graph of word form or spelling frequencies.

Parameters

The following parameters are used by this template:

|1=
The term or terms (comma-separated) to be graphed.
|2=
A display override for the term or terms.
|corpus=
The index of the corpus to be shown, see available corpora. Defaults to 26 i.e. English.
|startyear=, |start=
The year to begin the graph at. Defaults to 1800.
|endyear=, |end=
The year to end the graph at. Defaults to the newest available (see available corpora).
|caseinsensitive=
Whether to search with case insensitivity on or not. Any value taken to mean yes. Defaults to no.
|nodot=
By default, the template adds a full stop (period) at the end of the citation. To suppress this punctuation, use |nodot=1 or |nodot=yes.

Examples

Here are some:

* {{R:GNV|indecipherable, undecipherable}}

* {{R:GNV|ad lib, extemporal, extemporary, extemporaneous, extempore, extemporized, impromptu, improvised, improviso, off-the-cuff, offhand|some of the synonyms}}

* {{R:GNV|телепрогра́мма, телепереда́ча, телешо́у|corpus=36}}

* {{R:GNV|malen, streichen|corpus=31}}

* {{R:GNV|colour:eng_gb_2019,colour:eng_us_2019}}

* {{R:GNV|croissanterie|corpus=30|start=1900}}

* {{R:GNV|color/colour}}

* {{R:GNV|states of *}}

* {{R:GNV|states of *_NOUN}}

* {{R:GNV|*_ADJ argument}}

* {{R:GNV|cook_NOUN,cook_VERB}}

* {{R:GNV|cook_INF a meal}}

* {{R:GNV|cook_INF *_NOUN}} -- does not work

Available corpora

A list (with descriptions) is also available at https://books.google.com/ngrams/info.

Corpus 2019 index 2012 index 2009 index Shorthand (followed by _ and year)
American English 28 17 5 eng_us
British English 29 18 6 eng_gb
Chinese (simplified) 34 23 11 chi_sim
English 26 15 0 eng
English Fiction 27 16 4 eng_fiction
English One Million N/A N/A 1 eng_1m
French 30 19 7 fre
German 31 20 8 ger
Hebrew 35 24 9 heb
Italian 33 22 N/A ita
Russian 36 25 12 rus
Spanish 32 21 10 spa

Limitations

Google Ngram Viewer suffers from some limitations: (1) scanning errors (scannos); (2) the corpus increasingly becoming biased toward academic publications with the passage of time; (3) each book has the same weight regardless of popularity; and (4) wrong assignment of the year of publication. Some of the problems are covered below. The scanno problem does not seem to completely invalidate the results, especially for English and longer words. The severity of the problems depends on what we want to measure, whether cultural change over time or relative frequencies of word forms.

Bias toward academic publication

The search figure, Figure at the Google Books Ngram Viewer. reveals the problem: capitalized Figure rises to the top during 20th century, suggestive of use in captions of academic literature. When we restrict the corpus to English Fiction, the problem disappears: figure, Figure at the Google Books Ngram Viewer.

Long s vs. f

The search fuck at the Google Books Ngram Viewer. shows the problem: there is no way there were so many instances of fuck before 1800; rather, these are likely scannos of suck caused by the use of the long s (ſ). On the other hand, this problem does not occur after 1820.

Dropping hyphens

The searches anti-American, (antiAmerican*10) at the Google Books Ngram Viewer. and google books:"antiAmerican" show the problem: scanning sometimes drops the hyphen. There is no way there are so many occurrences of antiAmerican and the Google Books search confirms that. Other examples: (exteacher*10),ex-teacher at the Google Books Ngram Viewer, (nonEnglish*10),non-English at the Google Books Ngram Viewer.

Some hyphens are dropped when used within an unbroken line, other are dropped at a line break, which is ambiguous as for the presence of hyphen.

Dropping spaces

The searches thebook, nonchocolate at the Google Books Ngram Viewer and google books:"thebook" show the problem: the space was dropped and the result is as common as the legitimate nonchocolate. On the other hand, the book,(thebook*5000) at the Google Books Ngram Viewer shows this happens relatively rarely.

Joining different columns

The search google books:"misargument" shows the scanning problem: there are very few occurrences of misargument and some of the found items result from joining parts from different columns in multi-column publications.[1] This one example does not make it into GNV statistics, though. It is unclear this could significantly impact frequencies of common words.

Changes in capitalization

There is no reason to think there are spurious changes in capitalization. anti-American,(antiamerican*1000) at the Google Books Ngram Viewer looks plausible, unlike anti-American, antiAmerican at the Google Books Ngram Viewer.

Hyphens

As of Oct 2022:

Further reading