Google N-grams
The Google Ngram Viewer or Google Books Ngram Viewer is an online search engine that charts frequencies of any set of comma-delimited search strings using a yearly count of n-grams found in sources printed between 1500 and 2008 in Google's text corpora in English, Chinese (simplified), French, German, Hebrew, Italian, Russian, or Spanish; there are also some specialized English corpora, such as American English, British English, English Fiction, and English One Million; the 2009 version of most corpora is also available.
The program can search for a single word or a phrase, including misspellings or gibberish. The n-grams are matched with the text within the selected corpus, optionally using case-sensitive spelling (which compares the exact use of uppercase letters), and, if found in 40 or more books, are then plotted on a graph.
The Ngram Viewer as of January 2016 supports searches for parts of speech and wildcards.
The program was developed by Jon Orwant and Will Brockman and released in mid-December 2010. It was inspired by a prototype (called "Bookworm") created by Jean-Baptiste Michel and Erez Aiden from Harvard's Cultural Observatory and Yuan Shen from MIT and Steven Pinker.
The Ngram Viewer was initially based on the 2009 edition of the Google Books Ngram Corpus. As of January 2016[update], the program can search an individual language's corpus within the 2009 or the 2012 edition.
Commas delimit user-entered search-terms, indicating each separate word or phrase to find. The Ngram Viewer returns a plotted line chart within seconds of the user pressing the Enter key or the "Search" button on the screen.
As an adjustment for more books having been published during some years, the data is normalized, as a relative level, by the number of books published in each year.
Google populated the database from over 5 million books published up to 2008. Accordingly, as of January 2016[update], no data will match beyond the year 2008, no matter if the corpora was generated in 2009 or 2012. Due to limitations on the size of the Ngram database, only matches found in at least 40 books are indexed in the database; otherwise the database could not have stored all possible combinations.
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