Relevant bibliographies by topics / Ngram Viewer

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Academic literature on the topic 'Ngram Viewer'

Author: Grafiati
Published: 4 June 2021
Last updated: 28 January 2023

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Journal articles on the topic "Ngram Viewer"

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Shparberg, Anna L. "Google Books Ngram Viewer." Charleston Advisor 23, no. 1 (July 1, 2021): 16–19. http://dx.doi.org/10.5260/chara.23.1.16.

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The Google Books Ngram Viewer is a data mining tool that searches datasets derived from Google Books to generate frequency charts of language usage from the dawn of print until the present time. The available languages are English, French, German, Hebrew, Italian, Spanish, Chinese, and Russian. With a database in excess of two trillion words, it is the largest corpus of linguistics information in existence. In spite of concerns about the reliability of metadata used in Ngram Viewer, it is still viewed as a valuable resource for research into long-term cultural trends.
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McFadden, Robert H., William H. Zywiak, Ronald P. Bobroff, and Gao Niu. "War and Money in Ngram Viewer." Advances in Historical Studies 11, no. 04 (2022): 188–95. http://dx.doi.org/10.4236/ahs.2022.114016.

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Zięba, Anna. "Google Books Ngram Viewer in Socio-Cultural Research." Research in Language 16, no. 3 (September 30, 2018): 357–75. http://dx.doi.org/10.2478/rela-2018-0015.

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The objective of this paper is to verify if Google Books Ngram Viewer, a new tool working on a database of 361 billion words in English, and enabling quick recovery of data on word frequency in a diachronic perspective, is indeed valuable to socio-cultural research as suggested by its creators (Michel et al. 2010), i.e. the Cultural Observatory, Harvard University, Encyclopaedia Britannica, the American Heritage Dictionary, and Google. In the paper we introduce a study performed by Greenfield (2013), who applies the program to her Ecological Analysis, and contrast the findings with a study based on similar premises, in which we follow the trends in changes in word frequency throughout the 19th and 20th centuries to observe if these changes correspond to one of the major socio-cultural transformations that took place in the studied period, i.e. mediatization. The results of this study open a discussion on the usefulness of the program in socio-cultural research.
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Moon, Sang-Ho. "Case Study of Big Data in Humanities using Ngram Viewer." Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology 5, no. 6 (December 31, 2015): 57–65. http://dx.doi.org/10.14257/ajmahs.2015.12.10.

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O’Sullivan, O. P., R. M. Duffy, and B. D. Kelly. "Culturomics and the history of psychiatry: testing the Google Ngram method." Irish Journal of Psychological Medicine 36, no. 1 (August 17, 2017): 23–27. http://dx.doi.org/10.1017/ipm.2017.37.

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ObjectivesCulturomics is the study of behaviour and culture through quantitative analysis of digitised text. We aimed to apply a modern technique in this field to examine trends related to the history of psychiatry. In doing so, we aimed to explore the nature of the Google Ngram methodology.MethodsUsing Google Ngram Viewer, we studied Google’s corpus of over 4% of all published books and explored relevant trends in word usage.ResultsAn exponential growth in the use of ‘psychiatry’ between 1890 and 1984 was identified. ‘Sigmund Freud’ was mentioned more frequently than all other prominent figures in the history of psychiatry combined. Mentions of ‘suicide’ increased since 1820. The impact of several DSM editions is discussed.ConclusionThis study demonstrated the potential application of the Ngram methodology to the study of the history of psychiatry. The role of textual analysis in this field merits careful, constructive consideration and is likely to expand with technological advances.
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Oleinik, Anton. "Comparative Conceptology of Power and Resistance Using Google Ngram Books." Политическая концептология: журнал метадисциплинарных исследований, no. 01 (April 10, 2022): 26–40. http://dx.doi.org/10.18522/2218-5518.2022.1.2640.

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The article discusses the evolution of key concepts referring to governmentality in comparative perspective. The Russian discourse on government and power is compared with the Western discourse. The Google Books Ngram Viewer databank covering the period from 1800 to 2019 is used as a source of information. This databank contains more than 5 % of all published books. The proposed discourse analysis suggests that the Russian and Western discourses have some elective affinity: in both cases there is little room for truth telling and whistle-blowers face significant risk.
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Roth, Steffen. "Fashionable Functions." International Journal of Technology and Human Interaction 10, no. 2 (April 2014): 35–58. http://dx.doi.org/10.4018/ijthi.2014040103.

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Computer communication is revolutionizing modern society to the same extend as the invention of writing or the printing press have unsettled the archaic or the ancient society, respectively. In the present article, this idea will be exemplified by a demonstration of how the Google Ngram viewer – an online graphing tool which charts annual counts of words or sentences as found in the largest available corpus of digitalized books – allows for checks and challenges of familiar self-definitions of modern society. As functional differentiation is considered the central unique feature of modern societies, the hypotheses focus on the testing of prominent modern trend statements and predictions, such as the secularization, politicization, economization, and mediatization of society. All hypotheses are tested through a comparative analysis of word frequency time-series plots produced by means of the Google Ngram Viewer. The results show that the importance of individual function systems to society features significant change in time and considerable regional differences. Furthermore, the findings suggest adopting a skeptical position on some of the most frequent common senses of trends in functional differentiation and corresponding self-definitions of society.
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Zakharov, V. P., and A. Ts Masevich. "The experience of corpus-subjected historical-cultural studies of historical and political vocabulary." Bibliosphere, no. 2 (June 30, 2016): 47–55. http://dx.doi.org/10.20913/1815-3186-2016-2-47-55.

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The article represents results of diachronic studying the historical and political vocabulary with Google System Books Ngram Viewer. The authors investigate changes in use frequency of political figures names during 1920-2000. The study results demonstrate the relationship between changes in the frequency use of names in printed documents texts with historical events and political traditions of different countries. Some limitations of the system were also considered.
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Son, Seung Nam. "Case Study of Big Data in Liberal vs. General Education using Ngram Viewer." Korean Association of General Education 14, no. 2 (April 15, 2020): 23–34. http://dx.doi.org/10.46392/kjks.2020.14.2.23.

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Oleinik, Anton. "COMPARATIVE CONCEPTOLOGY OF POWER AND RESISTANCE USING GOOGLE NGRAM BOOKS." Respublica literaria, RL. 2021. Vol. 2. No. 4 (November 29, 2021): 124–43. http://dx.doi.org/10.47850/rl.2021.2.4.124-143.

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The article discusses the evolution of key concepts referring to governmentality in comparative perspective. The Russian discourse on government and power is compared with the Western discourse. The Google Books Ngram Viewer databank covering the period from 1800 to 2019 is used as a source of information. This databank contains more than 5% of all published books. The proposed discourse analysis suggests that the Russian and Western discourses have some elective affinity: in both cases there is little room for truth telling and whistle-blowers face significant risk.
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Dissertations / Theses on the topic "Ngram Viewer"

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Bryngelson, Andreas. "Google Books Ngram Viewer – nya möjligheter för den ryska korpusforskningen eller bara "More of the Same"?" Thesis, Uppsala universitet, Slaviska språk, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-298747.

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I detta arbete undersöks sökverktyget Ngram Viewer och dess ryska delkorpus, innehållande totalt drygt 67 miljarder ord från närmre 600 000 böcker, utgivna mellan 1607 och 2009. Arbetet består av tre huvudsakliga delar; en översiktligt jämförande undersökning av andra ryskspråkiga korpusar, därefter en mindre litteraturstudie av tidigare forskning genomförd med hjälp av den ryska delkorpusen i Ngram Viewer och slutligen egna tester och pilotundersökningar av densamma. Syftet med uppsatsen är framförallt att undersöka Ngram Viewers möjligheter och begränsningar i en större kontext av korpusforskning. Pilotstudierna i Ngram Viewer fokuserar framförallt på relationen mellan begreppen русский och российский (och därmed indirekt förhållandet mellan Русь och Россия‏), bland annat genom jämförelse med tidigare studier (Griščenko, 2013, 2014a). En av de viktigaste insikterna från arbetets första två delar är korpusens bristande funktioner vad gäller hantering av skrivtecken som avskaffades vid den ryska stavningsreformen 1917. Pilotundersökningarna i arbetets tredje del avgränsas därför främst till material från åren 1900–2008. Att de lingvistiska annotationerna i korpusen uteslutande är automatiskt genererade samt att man inte har direkt tillgång till korpusens källmaterial utgör också viktiga faktorer som begränsar Ngram Viewers användningsområde.
В этой работе изучается корпус и инструмент Google Books Ngram Viewer и как можно использовать корпус для исследования исторических изменений русского языка. Русский подкорпус Ngram Viewer содержит около 67 миллионов слов из почти 600 000 книг, изданных 1607–2009 гг.   Исследование состоит из трех частей. В первой части сравнивается Ngram Viewer с другими корпусами русского языка. Во второй части предлагается обзор научной литературы относительно Ngram Viewer, и его русского подкорпуса. В третьей части приводятся собственные пилотажные исследования с помощью Ngram Viewer. Прежде всего, рассматривается использование слов русский и российский, в частности, по сравнению с исследованиями Грищенко 2013 и 2014а.   Мы пришли к выводу, что Ngram Viewer в первую очередь может быть использован как инструмент количественного анализа русского языка 20-ого и 21-ого веков. По техническим причинам корпус оказался менее полезным для изучения более древних текстов (до орфографической реформы 1917 г.).
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Younes, Nadja [Verfasser]. "State-of-the-art research using the Google Books Ngram Viewer : Improving the method and investigating cultural change / Nadja Younes." Konstanz : KOPS Universität Konstanz, 2019. http://d-nb.info/1199266531/34.

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Books on the topic "Ngram Viewer"

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Michel, Jean-Baptiste. UNCHARTED: Big data as a lens on human culture. New York, USA: Riverhead Books, 2013.

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Jockers, Matthew L. Theme. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252037528.003.0008.

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This chapter demonstrates how big data and computation can be used to identify and track recurrent themes as the products of external influence. It first considers the limitations of the Google Ngram Viewer as a tool for tracing thematic trends over time before turning to Douglas Biber's Corpus Linguistics: Investigating Language Structure and Use, a primer on various factors complicating word-focused text analysis and the subsequent conclusions one might draw regarding word meanings. It then discusses the results of the author's application of latent Dirichlet allocation (LDA) to a corpus of 3,346 nineteenth-century novels using the open-source MALLET (MAchine Learning for LanguagE Toolkit), a software package for topic modeling. It also explains the different types of analyses performed by the author, including text segmentation, word chunking, and author nationality, gender and time-themes relationship analyses. The thematic data from the LDA model reveal the degree to which author nationality, author gender, and date of publication could be predicted by the thematic signals expressed in the nineteenth-century novels corpus.
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Uncharted: Big Data As a Lens on Human Culture. Penguin Publishing Group, 2014.

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Book chapters on the topic "Ngram Viewer"

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Peccatte, Patrick. "L’interprétation des graphiques produits par Ngram Viewer." In Read/Write Book 2, 231–38. OpenEdition Press, 2012. http://dx.doi.org/10.4000/books.oep.284.

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Finke, Roger, and Jennifer M. Mcclure. "Reviewing Millions of Books." In Faithful Measures. NYU Press, 2017. http://dx.doi.org/10.18574/nyu/9781479875214.003.0011.

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Despite the importance of trend data for understanding key substantive and theoretical questions on American religion, almost no such data exist. This chapter reviews how the Google Ngram Viewer and the Google book collection can generate detailed measures on religious trends. After demonstrating how the trends are generated, the authors evaluate the promise and potential limitations of these measures. Do the trends charted by the Ngram Viewer match known cultural and religious trends, and is the pool of book authors and readers representative of the larger culture? The chapter concludes with a discussion on how the tool can be used most effectively for future research.
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Hai-Jew, Shalin. "Querying Google Books Ngram Viewer's Big Data Text Corpuses to Complement Research." In Enhancing Qualitative and Mixed Methods Research with Technology, 514–55. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-6493-7.ch020.

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If qualitative and mixed methods researchers have a tradition of gleaning information from all possible sources, they may well find the Google Books Ngram Viewer and its repository of tens of millions of digitized books yet another promising data stream. This free cloud service enables easy access to big data in terms of querying the word frequency counts of a range of terms and numerical sequences (and languages) from 1500 – 2000, a 500-year span of book publishing, with new books being added continually. The data queries that may be made with this tool are virtually unanswerable otherwise. The word frequency counts provide a lagging indicator of both instances and trends, related to language usage, cultural phenomena, popularity, technological innovations, and a wide range of other insights. The text corpuses contain de-contextualized words used by the educated literati of the day sharing their knowledge in formalized texts. The enablements of the Google Books Ngram Viewer provide complementary information sourcing for designed research questions as well as free-form discovery. This tool allows downloading of the “shadowed” (masked or de-identified) extracted data for further analyses and visualizations. This chapter provides both a basic and advanced look at how to extract information from the Google Books Ngram Viewer for light research.
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Weiss, Andrew Philip. "Massive Digital Libraries (MDLs)." In Encyclopedia of Information Science and Technology, Fourth Edition, 5226–36. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2255-3.ch454.

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Massive Digital Library (MDL) is a term coined to define a class of digital libraries gathering mass-digitized print books and monographs, which rival the size of brick-and-mortar libraries. Specific examples of MDLs, including Google Books, HathiTrust, DPLA, Internet Archive, et al., are presented. The issues raised by MDLs include the following: mass-aggregation of digital content and the ability to maintain source-material accuracy and veracity; copyright, Fair Use and the mass-digitization of materials not in the Public Domain; and disparities in the level of diversity, especially with regard to Spanish-language, Japanese-language, and Hawaii-Pacific materials. Finally, the impact of MDLs on Digital Humanities, especially with regard to the Google Books digital corpus and the Google Ngram Viewer, will be investigated.
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Weiss, Andrew Philip. "Massive Digital Libraries (MDLs)." In Advances in Library and Information Science, 476–88. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7659-4.ch038.

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Massive digital library (MDL) is a term coined to define a class of digital libraries gathering mass-digitized print books and monographs, which rival the size of brick-and-mortar libraries. Specific examples of MDLs, including Google Books, HathiTrust, DPLA, Internet Archive, et al., are presented. The issues raised by MDLs include mass-aggregation of digital content and the ability to maintain source-material accuracy and veracity; copyright, fair use, and the mass-digitization of materials not in the public domain; and disparities in the level of diversity, especially with regard to Spanish-language, Japanese-language, and Hawaii-Pacific materials. Finally, the impact of MDLs on Digital Humanities, especially with regard to the Google Books digital corpus and the Google Ngram Viewer, will be investigated.
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Hai-Jew, Shalin. "Static Text-Based Data Visualizations." In Advances in Multimedia and Interactive Technologies, 203–302. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8696-0.ch007.

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Data visualizations have enhanced human understandings of various types of quantitative data for many years. Of late, text-based data visualizations have been used informally and formally on the WWW and Internet as well as for research. This chapter describes this phenomenon of text-based data visualizations by describing how many of the most common ones are created, where the underlying textual datasets are extracted from, how text-based data visualizations are analyzed, and the limits of such graphical depictions. While this work does not provide a comprehensive view of static (non-dynamic) text-based data visualizations, many of the most common ones are introduced. These visualizations are created using a variety of common commercial and open-source tools including Microsoft Excel, Google Books Ngram Viewer, Microsoft Visio, NVivo 10, Maltego Tungsten, CASOS AutoMap and ORA NetScenes, FreeMind, Wordle, UCINET and NetDraw, and Tableau Public. It is assumed that readers have a basic knowledge of machine-based text analysis.
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Monteiro, Licio Caetano do Rego. "Linhas cruzadas: geografia política e geopolítica no século XX através do Google Ngram Viewer e o debate no Brasil." In Geografia política, geopolítica e gestão do território: a integração sul-americana e a inserção das regiões periféricas, 96–113. Editora Letra1, 2018. http://dx.doi.org/10.21826/9788563800367-06.

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Hollowa, Steven W. "Chapter 17 Big Data, Big Deal: Use of Google Books Ngram Viewer and JSTOR Data for Research for Charting the Rise of Assyriology." In Perspectives on the History of Ancient Near Eastern Studies, 299–325. Penn State University Press, 2020. http://dx.doi.org/10.1515/9781646020898-018.

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Conference papers on the topic "Ngram Viewer"

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Mann, Jason, David Zhang, Lu Yang, Dipanjan Das, and Slav Petrov. "Enhanced Search with Wildcards and Morphological Inflections in the Google Books Ngram Viewer." In Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations. Stroudsburg, PA, USA: Association for Computational Linguistics, 2014. http://dx.doi.org/10.3115/v1/p14-5020.

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