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Research Article Quantitative Analysis of Culture Using Millions of Digitized Books Jean-Baptiste Michel,’?***+ Yuan Kui Shen,° Aviva Presser Aiden,° Adrian Veres,’ Matthew K. Gray,* The Google Books Team,° Joseph P. Pickett,’ Dale Hoiberg,”” Dan Clancy,® Peter Norvig,® Jon Orwant,® Steven Pinker,’ Martin A. Nowak,)!)” Erez Lieberman Aiden! !7!*!4:15-6#+ ‘Program for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138, USA. “Institute for Quantitative Social Sciences, Harvard University, Cambridge, MA 02138, USA. *Department of Psychology, Harvard University, Cambridge, MA 02138, USA. “Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA. °Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA. °Harvard Medical School, Boston, MA, 02115, USA. "Harvard College, Cambridge, MA 02138, USA. ®Google, Inc., Mountain View, CA, 94043, USA. "Houghton Mifflin Harcourt, Boston, MA 02116, USA. '’Encyclopaedia Britannica, Inc., Chicago, IL 60654, USA. ''Dept of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA. '*Dept of Mathematics, Harvard University, Cambridge, MA 02138, USA. “Broad Institute of Harvard and MIT, Harvard University, Cambridge, MA 02138, USA. School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA. Harvard Society of Fellows, Harvard University, Cambridge, MA 02138, USA. '°L aboratory-at-Large, Harvard University, Cambridge, MA 02138, USA. *These authors contributed equally to this work. +To whom correspondence should be addressed. E-mail: jb.michel@gmail.com (J.B.M.); erez@erez.com (E.A.). We constructed a corpus of digitized texts containing about 4% of all books ever printed. Analysis of this corpus enables us to investigate cultural trends quantitatively. We survey the vast terrain of “culturomics”, focusing on linguistic and cultural phenomena that were reflected in the English language between 1800 and 2000. We show how this approach can provide insights about fields as diverse as lexicography, the evolution of grammar, collective memory, the adoption of technology, the pursuit of fame, censorship, and historical epidemiology. “Culturomics” extends the boundaries of rigorous quantitative inquiry to a wide array of new phenomena spanning the social sciences and the humanities. Reading small collections of carefully chosen works enables scholars to make powerful inferences about trends in human thought. However, this approach rarely enables precise measurement of the underlying phenomena. Attempts to introduce quantitative methods into the study of culture (/-6) have been hampered by the lack of suitable data. We report the creation of a corpus of 5,195,769 digitized books containing ~4% of all books ever published. Computational analysis of this corpus enables us to observe cultural trends and subject them to quantitative investigation. “Culturomics” extends the boundaries of scientific inquiry to a wide array of new phenomena. The corpus has emerged from Google’s effort to digitize books. Most books were drawn from over 40 university libraries around the world. Each page was scanned with custom equipment (7), and the text digitized using optical character recognition (OCR). Additional volumes — both physical and digital — were contributed by publishers. Metadata describing date and place of publication were provided by the libraries and publishers, and supplemented with bibliographic databases. Over 15 million books have been digitized [12% of all books ever published (7)]. We selected a subset of over 5 million books for analysis on the basis of the quality of their OCR and metadata (Fig. 1A) (7). Periodicals were excluded. The resulting corpus contains over 500 billion words, in English (361 billion), French (45B), Spanish (45B), German (37B), Chinese (13B), Russian (35B), and Hebrew (2B). The oldest works were published in the 1500s. The early decades are represented by only a few books per year, comprising several hundred thousand words. By 1800, the corpus grows to 60 million words per year; by 1900, 1.4 billion; and by 2000, 8 billion. The corpus cannot be read by a human. If you tried to read only the entries from the year 2000 alone, at the reasonable pace of 200 words/minute, without interruptions for food or sleep, it would take eighty years. The sequence of letters is one thousand times longer than the human genome: if you wrote it out in a straight line, it would reach to the moon and back 10 times over (8). To make release of the data possible in light of copyright constraints, we restricted our study to the question of how often a given “1-gram” or “n-gram” was used over time. A 1- gram is a string of characters uninterrupted by a space; this includes words (“banana”, “SCUBA”) but also numbers Sciencexpress / www.sciencexpress.org / 16 December 2010 / Page 1 / 10.1126/science.1199644 HOUSE_OVERSIGHT_016996 Downloaded from www.sciencemag.org on December 16, 2010