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Google Ngram Viewer

January 01, 1970

The Google Ngram Viewer or Google Books Ngram Viewer is an online search engine that charts the frequencies of any set of search strings using a yearly count of n-grams found in printed sources published between 1500 and 2019[1][2][3][4] in Google's text corpora in English, Chinese (simplified), French, German, Hebrew, Italian, Russian, or Spanish.[2][5] There are also some specialized English corpora, such as American English, British English, and English Fiction.[6]

Example of an Ngram query

The program can search for a word or a phrase, including misspellings or gibberish.[5] 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),[7] and, if found in 40 or more books, are then displayed as a graph.[8] The Google Ngram Viewer supports searches for parts of speech and wildcards.[6] It is routinely used in research.[9][10]

History edit

The program was developed by Jon Orwant and Will Brockman and released in mid-December 2010.[2][3] It was inspired by a prototype called Bookworm created by Jean-Baptiste Michel and Erez Aiden from Harvard's Cultural Observatory, Yuan Shen from MIT, and Steven Pinker.[11]

The Ngram Viewer was initially based on the 2009 edition of the Google Books Ngram Corpus. As of July 2020, the program supports 2009, 2012, and 2019 corpora.

Operation and restrictions edit

Commas delimit user-entered search terms, indicating each separate word or phrase to find.[8] The Ngram Viewer returns a plotted line chart.

As an adjustment for more books having been published during some years, the data are normalized, as a relative level, by the number of books published in each year.[8]

Due to limitations on the size of the Ngram database, only matches found in at least 40 books are indexed in the database.[8]

Limitations edit

The data set has been criticized for its reliance upon inaccurate OCR, an overabundance of scientific literature, and for including large numbers of incorrectly dated and categorized texts.[12][13] Because of these errors, and because it is uncontrolled for bias[14] (such as the increasing amount of scientific literature, which causes other terms to appear to decline in popularity), it is risky to use this corpus to study language or test theories.[15] Since the data set does not include metadata, it may not reflect general linguistic or cultural change[16] and can only hint at such an effect.

Guidelines for doing research with data from Google Ngram have been proposed that address many of the issues discussed above.[17]

OCR issues edit

Optical character recognition, or OCR, is not always reliable, and some characters may not be scanned correctly. In particular, systemic errors like the confusion of s and f in pre-19th century texts (due to the use of ſ, the long s, which was similar in appearance to f) can cause systemic bias. Although Google Ngram Viewer claims that the results are reliable from 1800 onwards, poor OCR and insufficient data mean that frequencies given for languages such as Chinese may only be accurate from 1970 onward, with earlier parts of the corpus showing no results at all for common terms, and data for some years containing more than 50% noise.[18][19]

See also edit

References edit

  1. ^ "Quantitative analysis of culture using millions of digitized books" JB Michel et al, Science 2011, DOI: 10.1126/science.1199644 [1]
  2. ^ a b c "Google Ngram Database Tracks Popularity Of 500 Billion Words" Huffington Post, 17 December 2010, webpage: HP8150.
  3. ^ a b "Google's Ngram Viewer: A time machine for wordplay", Cnet.com, 17 December 2010, webpage: CN93 2014-01-23 at the Wayback Machine.
  4. ^ @searchliaison (July 13, 2020). "The Google Books Ngram Viewer has now been updated with fresh data through 2019" (Tweet). Retrieved 2020-08-11 – via Twitter.
  5. ^ a b "Google Books Ngram Viewer - University at Buffalo Libraries", Lib.Buffalo.edu, 22 August 2011, webpage: Buf497 2013-07-02 at the Wayback Machine
  6. ^ a b "Google Books Ngram Viewer info page".
  7. ^ "Google Ngram Viewer - Google Books", Books.Google.com, May 2012, webpage: G-Ngrams.
  8. ^ a b c d "Google Ngram Viewer - Google Books" (Information), Books.Google.com, December 16, 2010, webpage: G-Ngrams-info: notes bigrams and use of quotes for words with apostrophes.
  9. ^ Greenfield, Patricia M. (September 2013). "The Changing Psychology of Culture From 1800 Through 2000". Psychological Science. 24 (9): 1722–1731. doi:10.1177/0956797613479387. ISSN 0956-7976. PMID 23925305. S2CID 6123553.
  10. ^ Younes, Nadja; Reips, Ulf-Dietrich (October 2018). "The changing psychology of culture in German-speaking countries: A Google Ngram study: THE CHANGING PSYCHOLOGY OF CULTURE". International Journal of Psychology. 53: 53–62. doi:10.1002/ijop.12428. PMID 28474338. S2CID 7440938.
  11. ^ The RSA (4 February 2010). "Steven Pinker – The Stuff of Thought: Language as a window into human nature" – via YouTube.
  12. ^ Google Ngrams: OCR and Metadata 2016-04-27 at the Wayback Machine. ResourceShelf, 19 December 2010
  13. ^ Nunberg, Geoff (16 December 2010). . Archived from the original on 10 March 2016.
  14. ^ Pechenick, Eitan Adam; Danforth, Christopher M.; Dodds, Peter Sheridan; Barrat, Alain (7 October 2015). "Characterizing the Google Books Corpus: Strong Limits to Inferences of Socio-Cultural and Linguistic Evolution". PLOS ONE. 10 (10): e0137041. arXiv:1501.00960. Bibcode:2015PLoSO..1037041P. doi:10.1371/journal.pone.0137041. PMC 4596490. PMID 26445406.
  15. ^ Zhang, Sarah. "The Pitfalls of Using Google Ngram to Study Language". WIRED. Retrieved 2017-05-24.
  16. ^ Koplenig, Alexander (2015-09-02). "The impact of lacking metadata for the measurement of cultural and linguistic change using the Google Ngram data sets—Reconstructing the composition of the German corpus in times of WWII". Digital Scholarship in the Humanities. 32 (1) (published 2017-04-01): 169–188. doi:10.1093/llc/fqv037. ISSN 2055-7671.
  17. ^ Younes, Nadja; Reips, Ulf-Dietrich (2019-03-22). "Guideline for improving the reliability of Google Ngram studies: Evidence from religious terms". PLOS ONE. 14 (3): e0213554. Bibcode:2019PLoSO..1413554Y. doi:10.1371/journal.pone.0213554. ISSN 1932-6203. PMC 6430395. PMID 30901329.
  18. ^ Google n-grams and pre-modern Chinese. digitalsinology.org.
  19. ^ When n-grams go bad. digitalsinology.org.

Bibliography edit

  • Lin, Yuri; et al. (July 2012). "Syntactic Annotations for the Google Books Ngram Corpus" (PDF). Proceedings of the 50th Annual Meeting. Demo Papers. 2. Jeju, Republic of Korea: Association for Computational Linguistics: 169–174. 2390499. Whitepaper presenting the 2012 edition of the Google Books Ngram Corpus

External links edit

  • Official website

January 01, 1970
google, ngram, viewer, google, books, ngram, viewer, online, search, engine, that, charts, frequencies, search, strings, using, yearly, count, grams, found, printed, sources, published, between, 1500, 2019, google, text, corpora, english, chinese, simplified, . The Google Ngram Viewer or Google Books Ngram Viewer is an online search engine that charts the frequencies of any set of search strings using a yearly count of n grams found in printed sources published between 1500 and 2019 1 2 3 4 in Google s text corpora in English Chinese simplified French German Hebrew Italian Russian or Spanish 2 5 There are also some specialized English corpora such as American English British English and English Fiction 6 Example of an Ngram query The program can search for a word or a phrase including misspellings or gibberish 5 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 7 and if found in 40 or more books are then displayed as a graph 8 The Google Ngram Viewer supports searches for parts of speech and wildcards 6 It is routinely used in research 9 10 Contents 1 History 2 Operation and restrictions 3 Limitations 3 1 OCR issues 4 See also 5 References 6 Bibliography 7 External linksHistory editThe program was developed by Jon Orwant and Will Brockman and released in mid December 2010 2 3 It was inspired by a prototype called Bookworm created by Jean Baptiste Michel and Erez Aiden from Harvard s Cultural Observatory Yuan Shen from MIT and Steven Pinker 11 The Ngram Viewer was initially based on the 2009 edition of the Google Books Ngram Corpus As of July 2020 update the program supports 2009 2012 and 2019 corpora Operation and restrictions editCommas delimit user entered search terms indicating each separate word or phrase to find 8 The Ngram Viewer returns a plotted line chart As an adjustment for more books having been published during some years the data are normalized as a relative level by the number of books published in each year 8 Due to limitations on the size of the Ngram database only matches found in at least 40 books are indexed in the database 8 Limitations editThe data set has been criticized for its reliance upon inaccurate OCR an overabundance of scientific literature and for including large numbers of incorrectly dated and categorized texts 12 13 Because of these errors and because it is uncontrolled for bias 14 such as the increasing amount of scientific literature which causes other terms to appear to decline in popularity it is risky to use this corpus to study language or test theories 15 Since the data set does not include metadata it may not reflect general linguistic or cultural change 16 and can only hint at such an effect Guidelines for doing research with data from Google Ngram have been proposed that address many of the issues discussed above 17 OCR issues edit Optical character recognition or OCR is not always reliable and some characters may not be scanned correctly In particular systemic errors like the confusion of s and f in pre 19th century texts due to the use of ſ the long s which was similar in appearance to f can cause systemic bias Although Google Ngram Viewer claims that the results are reliable from 1800 onwards poor OCR and insufficient data mean that frequencies given for languages such as Chinese may only be accurate from 1970 onward with earlier parts of the corpus showing no results at all for common terms and data for some years containing more than 50 noise 18 19 See also editCulturomics Google Trends Lexical analysisReferences edit Quantitative analysis of culture using millions of digitized books JB Michel et al Science 2011 DOI 10 1126 science 1199644 1 a b c Google Ngram Database Tracks Popularity Of 500 Billion Words Huffington Post 17 December 2010 webpage HP8150 a b Google s Ngram Viewer A time machine for wordplay Cnet com 17 December 2010 webpage CN93 Archived 2014 01 23 at the Wayback Machine searchliaison July 13 2020 The Google Books Ngram Viewer has now been updated with fresh data through 2019 Tweet Retrieved 2020 08 11 via Twitter a b Google Books Ngram Viewer University at Buffalo Libraries Lib Buffalo edu 22 August 2011 webpage Buf497 Archived 2013 07 02 at the Wayback Machine a b Google Books Ngram Viewer info page Google Ngram Viewer Google Books Books Google com May 2012 webpage G Ngrams a b c d Google Ngram Viewer Google Books Information Books Google com December 16 2010 webpage G Ngrams info notes bigrams and use of quotes for words with apostrophes Greenfield Patricia M September 2013 The Changing Psychology of Culture From 1800 Through 2000 Psychological Science 24 9 1722 1731 doi 10 1177 0956797613479387 ISSN 0956 7976 PMID 23925305 S2CID 6123553 Younes Nadja Reips Ulf Dietrich October 2018 The changing psychology of culture in German speaking countries A Google Ngram study THE CHANGING PSYCHOLOGY OF CULTURE International Journal of Psychology 53 53 62 doi 10 1002 ijop 12428 PMID 28474338 S2CID 7440938 The RSA 4 February 2010 Steven Pinker The Stuff of Thought Language as a window into human nature via YouTube Google Ngrams OCR and Metadata Archived 2016 04 27 at the Wayback Machine ResourceShelf 19 December 2010 Nunberg Geoff 16 December 2010 Humanities research with the Google Books corpus Archived from the original on 10 March 2016 Pechenick Eitan Adam Danforth Christopher M Dodds Peter Sheridan Barrat Alain 7 October 2015 Characterizing the Google Books Corpus Strong Limits to Inferences of Socio Cultural and Linguistic Evolution PLOS ONE 10 10 e0137041 arXiv 1501 00960 Bibcode 2015PLoSO 1037041P doi 10 1371 journal pone 0137041 PMC 4596490 PMID 26445406 Zhang Sarah The Pitfalls of Using Google Ngram to Study Language WIRED Retrieved 2017 05 24 Koplenig Alexander 2015 09 02 The impact of lacking metadata for the measurement of cultural and linguistic change using the Google Ngram data sets Reconstructing the composition of the German corpus in times of WWII Digital Scholarship in the Humanities 32 1 published 2017 04 01 169 188 doi 10 1093 llc fqv037 ISSN 2055 7671 Younes Nadja Reips Ulf Dietrich 2019 03 22 Guideline for improving the reliability of Google Ngram studies Evidence from religious terms PLOS ONE 14 3 e0213554 Bibcode 2019PLoSO 1413554Y doi 10 1371 journal pone 0213554 ISSN 1932 6203 PMC 6430395 PMID 30901329 Google n grams and pre modern Chinese digitalsinology org When n grams go bad digitalsinology org Bibliography editLin Yuri et al July 2012 Syntactic Annotations for the Google Books Ngram Corpus PDF Proceedings of the 50th Annual Meeting Demo Papers 2 Jeju Republic of Korea Association for Computational Linguistics 169 174 2390499 Whitepaper presenting the 2012 edition of the Google Books Ngram CorpusExternal links editOfficial website Retrieved from https en wikipedia org w index php title Google Ngram Viewer amp oldid 1208322096, wikipedia, wiki, book, books, library,

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