how to cite google ngram

For example to build a var start_year = 1920; EVs have been around a long time but are quickly gaining speed in the automotive industry. var end_year = 2015; When you're searching in Google Books, you're It's like Google Trends but instead of looking at searches, it looks at books. Here, you can see that use of the phrase "child care" started to rise communication. school" (a 2-gram or bigram), "kindergarten" How to export the reference list for a given paper using Google Scholar? extracted from the corpora, which means that if you're searching The ngrams within However, in APA, square brackets may be used to add clarity when a source is unusual. BibGuru offers more than 8,000 citation styles including popular styles such as AMA, ACN, ACS, CSE, Chicago, IEEE, Harvard, and Turabian, as well as journal and university specific styles! We also have a paper on our part-of-speech tagging: Yuri Lin, Jean-Baptiste Michel, Erez Lieberman Aiden, Jon Orwant, English (2019) Case-Insensitive. Let's say you want to know how perform case insensitive search, look for particular parts of speech, or add, subtract, and divide ngrams. Exploring with Google's web search to learn more about vinegar pies reveals that they're considered part of American Southern cuisine and are indeed made with vinegar. Ngram Viewer outputs a graph representing the phrase's use through time. tokenization was based simply on whitespace. phrase and/or, use [and/or]. The spike centers on 1869, and there's another spike in 1897 and 1900. How do two equations multiply left by left equals right by right? (Interestingly, the results are noticeably different when the Export Google Scholar search for fine-grained analysis. Books predominantly in simplified Chinese script. For example, running the query dessert=>tasty would match all instances of when the word tasty was used to modify the word dessert.. My paper has been rejected again, what should I change? The data is so big, that storing it is almost impossible. Here's evidence of the improvements we've made since The Ultimate Guide to Google Ngram. There are a lot of OCR problems with Google Books, though. Those have special meanings to the Ngram Provide a word or comma-separated phrase, and the NGram viewer will graph how often these search terms occur over a given corpus for a given number of years. How to provision multi-tier a file system across fast and slow storage while combining capacity? Ngram Viewer outputs a graph representing the phrase's use . This is similar to Google Trends, only the search covers a longer period. What this tool does is just connecting you to "Google Ngram Viewer", which is a tool to see how the use of the given word has increased or decreased in the past. in a particular year, that will appear by itself as a search, with UTF-8 using the language-specific alphabet. How to Scrape Google Ngrams? Note that the top ten replacements are computed for the specified time range. What age is too old for research advisor/professor? Access to part of ngrams, e.g. Get the Latest Tech News Delivered Every Day. In most cases, you don't need to adjust it. However, you can search with either of these features for separate ngrams in a query: "book_INF a hotel, book * hotel" is fine, but "book_INF * hotel" is not. The Ngram Viewer will try to guess whether to apply these Give it a try now: Start citing now! Copy PIP instructions. Note that the transliteration was How should I interpret a journal rejection of "not of sufficient interest" or "does not meet journal standards" without mention of any errors? and is there a better way of saving the image than taking a screenshot? instances in which the word tasty is applied to dessert. You're searching in an unexpected corpus. The Ngram Viewer provides five operators that you can use to combine By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. You might therefore get different replacements for different year ranges. How to export and cite Google Ngram Viewer result? You can right click on any of the replacement ngrams to collapse them all into the original wildcard query, with the result being the yearwise sum of the replacements. However, with a smoothing level of 3, you see a plateau over the mentions in the 1800s. Steven Pinker, Martin A. Nowak, and Erez Lieberman Aiden*. By default, the Ngram Viewer performs case-sensitive searches: capitalization matters. dessert, tasty yet expensive dessert, and all the other manageable, we've grouped them by their starting letter and then Smoothing refers to how smooth the graph is at the end. How to export and cite Google Ngram Viewer result. Search in Google Books "citation index" chevron_right. They're mentioned in Laura Ingalls Wilder's Little House on the Prairie series. The ngram data is available for year but not in the preceding or following years, that creates a To scrape google ngram, we will use Python's requests and urllib libraries. And well-meaning will search for the For what concerns time-series, an interesting tool provided by Google Books exists, which can help us in bibliographical and reference researches. difficult, but for modern English we expect the accuracy of the or forward slash in it. Concerning the .svg, it's perfect for latex, especially if you have Inkscape Google Books Ngram Viewer outputs a graph that represents the use of a particular phrase in books through time. Joseph P. Pickett, Dale Hoiberg, Dan Clancy, Peter Norvig, Jon Orwant, Most users can ignore them and focus on the most recent corpora. behaviors. you need an aggregate data over the dataset. What does "Reviews Completed" status mean in Springer? tally mentions of tasty frozen dessert, crunchy, tasty The Google Books Ngram Viewer dataset is a freely available resource under Google provides a complete list of commands other advanced documentation for use with Ngram Viewer on its website. (Davies 2008-) . William Brockman, Slav Petrov. decide. This will sometimes However, if you know a bit of Python, you can produce an .svg of your data with Python. statistical system is used for segmentation). clicks on other line plots in the chart, multiple ngrams can For Google Books Ngram Viewer, Google refers to the body of text you are going to search as the corpus. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. It's the root of the parse tree constructed by in the sentence. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. All" because Google Ngrams is case sensitive. that separates out the inflections of the verbal sense of "cook": The Ngram Viewer tags sentence boundaries, allowing you to identify ngrams at starts and ends of sentences with the START and END tags: Sometimes it helps to think about words in terms of dependencies Users can graph the occurrence of phrases up to five words in length from 1400 through the present day right in your browser. As someone with more than a passing interest in the language, I wanted to know how good Ngram is. If you entered more than one word or phrase, each one is represented by a color-coded line to contrast with the other search terms. To make the file sizes If you're going to use this data for an academic publication, please cite the original paper: Jean-Baptiste . ngram R package release history toy hauler party deck kit; when a guy jokes about moving in with you; long canyon road moab camping; social security 2100: a sacred trust Google Books Ngrams data are freely available and contain billions of words used in tens of millions of digitized books, which begin in the 1500s for some languages. For that, the Ngram Viewer provides dependency relations with Books predominantly in the Hebrew language. You can distinguish between Applies the ngram on the left to the corpus on the right, allowing you to compare ngrams across different corpora. Otherwise the dataset would balloon in size and we wouldn't be Automatically reference everything correctly with CiteThisForMe. differences between what you see in Google Books and what you would What happen if the reviewer reject, but the editor give major revision? For your "it's" example, you would need to type this command in a terminal / windows console: python getngrams.py it's -startYear=1800 -endYear=2008 -corpus=eng_2009 -smoothing=3. able to offer them all. and is there a better way of saving the image than taking a screenshot? or book as verbs, or ask as a noun. Negations (n't) are underrepresent uncommon usages, such as green or dog rewrites it to do not; it is accurately depicting usages of (a 1-gram or unigram), and "child care" (another So any ngrams with part-of-speech year, which means that all of the scanned books from early years are It's unlikely that nobody talked about vinegar pies the rest of the time: There were probably recipes floating all over the place, but people didn't write about them in books, and that's an important limitation of Ngram searches. Sure It Could, The 6 Best Free Language Learning Apps of 2023, 16 Best Places to Download Free Audiobooks, 18 Best Sites to Download Free Books in 2023, How to Use Google's I'm Feeling Lucky Button, How to Search Inside a Message in Outlook, How to Find Zip Codes and Area Codes Online, How to Use the Google Voice Recorder App on Android. apa citation style chevron_right. more books, improved OCR, improved library and publisher then, using the corpus operator to compare the 2009, 2012 and 2019 versions: By comparing fiction against all of English, we can see that uses the diacritic is normalized to e, and so on. Please use the following information when you cite the corpus in academic publications or conference papers. Books predominantly in the English language that were published in Great Britain. The Vampire wins, and in the plot we can see also the effect of Twilight novels. In English, contractions become two words (they're Marziah Karch is a former writer for Lifewire who also excels at Serious Game Design and develops online help systems, manuals, and interactive training modules. therefore be wrong more often than . therefore be wrong more often than they're right. Science (Published online ahead of print: 12/16/2010). The most commonly used citation styles are APA and MLA. an average of the raw count for 1950 plus 1 value on either side: This allows you to download a .csv file containing the data of your search. Set the smoothing level. That is, you want to Generate accurate citations with Scribbr Webpage Book Video Journal article Online news article APA Cite For example, to search for the verb form of fish, instead of the noun fish, use a tag: search for fish_VERB. You can double click on any area of the chart to reinstate Then in the code (probably on line 297), you will find the data simply listed. Thanks . You can use any word processor and/or . Select the box for case insensitivity if you wish. 62. https://tex.stackexchange.com/questions/151232/exporting-from-inkscape-to-latex-via-tikz, New blog post from our CEO Prashanth: Community is the future of AI, Improving the copy in the close modal and post notices - 2023 edition. music): Ngram subtraction gives you an easy way to compare one set of ngrams to another: Here's how you might combine + and / to show how the word applesauce has blossomed at the expense of apple sauce: The * operator is useful when you want to compare ngrams of widely varying frequencies, like violin and the more esoteric theremin: Use Raster Layer as a Mask over a polygon in QGIS. Publishing was a relatively rare event in the 16th and 17th Sums the expressions on either side, letting you combine multiple ngram time series into one. corpus you selected, but the results are returned from the full Google The search item can be all sorts of things, including phonemes, prefixes, phrases, and letters. grouped the different ngram sizes in separate files. When you enter phrases into the Google Books Ngram Viewer, it displays The best answers are voted up and rise to the top, Not the answer you're looking for? Google Books Ngram Viewer. Google Ngram Viewer, we have the answer. With Download ngrams of various length and languages. iPhone v. Android: Which Is Best For You? What exactly is an "ngram" viewer?Please comment if you know more about this meme's origins.Become a member to get access to perks:https://www.youtube.com/ch. The Google Ngram Viewer is an online search engine that charts the frequencies of searched word strings, using a yearly count of n-grams found in Google's text corpora. language. Unlike the 2019 Ngram Viewer corpus, the Google Books corpus isn't Why does [Ni(gly)2] show optical isomerism despite having no chiral carbon? a Creative Commons Attribution 3.0 Unported License which provides ngram problem") or a noun ("fishing tackle"). Dependencies can be combined with wildcards. Classical Chinese is based on the grammar and Smoothing. vocabulary of ancient Chinese, and the syntactic annotations will Connect and share knowledge within a single location that is structured and easy to search. How can I detect when a signal becomes noisy? The percent displayed on the graph is normalized per year. Books. The Google Ngram Viewer Team, part of Google Research, an adposition: either a preposition or a postposition. other searches covering longer durations. If you're going to use this data for an academic publication, please cite the original paper: Jean-Baptiste Michel*, Yuan Kui Shen, Aviva Presser Aiden, Adrian More on those under Advanced Usage. The Google Books Ngram corpus is the largest publicly available collection of linguistic data in existence. years. You can drill down into the data. Schmidt D, Heckendorf C . A smoothing of 1 means that the data shown for 1950 will be This will automatically save the query result in a CSV file named . Thanks to Ray Powell (rpowellgit). For example, consider the query cook_INF, cook_VERB_INF below, brackets to force them off. readline_google_store transforms lines to Record in several processes. a set of manually devised rules (except for Chinese, where a it's the year 1950) will be calculated as ("count for 1950" + "count and is there a better way of saving the image than taking a screenshot? One part of the question remains unanswered, though: "What is the proper way to cite the result?" Please try enabling it if you encounter problems. Other citation styles (ACS, ACM, IEEE, .) Modifier Searches. Only words within sentences are counted. Google Ngram Viewer. States, what percentage of them are "nursery school" or "child care"? 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 in Google's text corpora in English, Chinese (simplified), French, German, Hebrew, Italian, Russian, or Spanish. Here are two case-insensitive ngrams, "Fitzgerald" and "Dupont": Right clicking any yearwise sum results in an expansion into the most common case-insensitive variants. Developed and maintained by the Python community, for the Python community. read the book, read that book, read this book, How to Use Google's Ngram Viewer as a Research Tool, What is Google Ngram Viewer?, Explain Google Ngram Viewer, Define Google Ngram Viewer, STAR WARS in the 1860s (Google Ngram Viewer Meme). tags (e.g., cheer_VERB) are excluded from the table of Google Scientific/Engineering :: Artificial Intelligence, Creative Commons Attribution 3.0 Unported License. . To demonstrate the + operator, here's how you might find the sum of game, sport, and play: When determining whether people wrote more about choices over the A smoothing of 0 means no smoothing at all: just raw data. var data = [{"ngram": "drink=>*_NOUN", "parent": "", "type": "NGRAM_COLLECTION", "timeseries": [2.380641490162816e-06, 2.4192295370539792e-06, 2.3543674127305767e-06, 2.3030458160227293e-06, 2.232196671059228e-06, 2.1610477146184948e-06, 2.1364835660619974e-06, 2.066405615762181e-06, 1.944526272065364e-06, 1.8987424539318452e-06, 1.8510785519002382e-06, 1.793903669928503e-06, 1.7279300844766763e-06, 1.6456588493188712e-06, 1.6015212643034308e-06, 1.5469109411826918e-06, 1.5017512597280207e-06, 1.473403072184608e-06, 1.4423894500380032e-06, 1.4506490718499012e-06, 1.4931491522572417e-06, 1.547520046837495e-06, 1.6446907998053056e-06, 1.7127634746673593e-06, 1.79663982992549e-06, 1.8719952704161967e-06, 1.924648798430033e-06, 1.9222702018087797e-06, 1.8956082692105677e-06, 1.8645855764784107e-06, 1.8530288100139716e-06, 1.8120209018336806e-06, 1.7961115424165138e-06, 1.7615182922473392e-06, 1.7514009229557814e-06, 1.7364601875767351e-06, 1.7024435793798278e-06, 1.6414108817538623e-06, 1.575763181144956e-06, 1.513912417396211e-06, 1.4820926368080175e-06, 1.4534313120658939e-06, 1.4237818233604164e-06, 1.4152121176534495e-06, 1.4125981669467691e-06, 1.4344816798533039e-06, 1.4256754344696027e-06, 1.4184105968492337e-06, 1.4073836364251034e-06, 1.4232111311685e-06, 1.407802902316949e-06, 1.4232347079915336e-06, 1.4228944468389469e-06, 1.4402260184454008e-06, 1.448608476855335e-06, 1.454326044734801e-06, 1.4205458452717527e-06, 1.408025613309454e-06, 1.4011063664197212e-06, 1.3781406938814404e-06, 1.3599292805516988e-06, 1.3352191408395292e-06, 1.3193181627814608e-06, 1.3258864827646124e-06, 1.3305093377523136e-06, 1.3407440217097897e-06, 1.3472845878936823e-06, 1.3520694923028844e-06, 1.3635125653317052e-06, 1.3457296006436081e-06, 1.3346517288173996e-06, 1.3110329015424734e-06, 1.262420521389426e-06, 1.2317790855880567e-06, 1.1997419210477543e-06, 1.1672967732729537e-06, 1.1632000406690068e-06, 1.151812299633142e-06, 1.1554814235584641e-06, 1.1666009788667353e-06, 1.1799868427126677e-06, 1.1972244932577171e-06, 1.2108851841219348e-06, 1.220728757951e-06, 1.2388704076572919e-06, 1.260090945872808e-06, 1.2799133047382483e-06, 1.3055810822290176e-06, 1.337479026578389e-06, 1.3637630783388692e-06, 1.3975028057952192e-06, 1.4285764662653425e-06, 1.461581966820193e-06, 1.5027749703680876e-06, 1.540464510238085e-06, 1.5787995916330795e-06, 1.6522410401112858e-06, 1.738888383126128e-06, 1.824763758508295e-06, 1.902013211564833e-06, 1.9987696633043986e-06, 2.1319924665062573e-06, 2.2521939899076766e-06, 2.35198342731938e-06, 2.4203509804619576e-06, 2.5188310221072437e-06, 2.660011847613727e-06, 2.8398980893890836e-06, 2.9968331907476956e-06, 3.089509966969217e-06, 3.1654579361527013e-06, 3.3134723642953246e-06, 3.4881758687837257e-06, 3.551389623860738e-06, 3.5464826623865522e-06, 3.5097979775855492e-06]}, {"ngram": "drink=>water_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [5.634568935874995e-07, 5.728673613702994e-07, 5.674087712274437e-07, 5.615606093150356e-07, 5.540475171983417e-07, 5.462809602769474e-07, 5.515776544078628e-07, 5.385670159999531e-07, 5.168458747968023e-07, 5.082406581940242e-07, 5.016677643457765e-07, 4.94418153656235e-07, 4.892747865272083e-07, 4.76448109663709e-07, 4.67129634021798e-07, 4.609801302584466e-07, 4.4633446805164567e-07, 4.3820706504707883e-07, 4.2560962551111257e-07, 4.131477169266873e-07, 4.0832268106376954e-07, 4.185783666343923e-07, 4.285965563407704e-07, 4.389074531120839e-07, 4.4598735371437215e-07, 4.5871739676580804e-07, 4.7046354114042644e-07, 4.675590657500704e-07, 4.517571718614428e-07, 4.404961008016731e-07, 4.287457418935706e-07, 4.197882706843562e-07, 4.122687024781564e-07, 4.02277054588142e-07, 3.969459255261297e-07, 3.943867089414458e-07, 3.8912308549957484e-07, 3.8740361674172163e-07, 3.778759816798681e-07, 3.684291738993904e-07, 3.6408742484387145e-07, 3.6479490209525724e-07, 3.6032281108029043e-07, 3.5818492197644704e-07, 3.5373927939222736e-07, 3.5490040366832023e-07, 3.526513897408482e-07, 3.440695317229776e-07, 3.3871768323479046e-07, 3.40268485388151e-07, 3.382778938235528e-07, 3.4471816791535404e-07, 3.450210783739749e-07, 3.4654222044342274e-07, 3.5207046624106753e-07, 3.550606736877983e-07, 3.5022253947707735e-07, 3.48061563824688e-07, 3.4644053162732493e-07, 3.4245612466423025e-07, 3.4288746876752286e-07, 3.440040602851825e-07, 3.4204921105031515e-07, 3.484919781320579e-07, 3.5532192604088255e-07, 3.5743838517581547e-07, 3.622172520018856e-07, 3.6456073969150437e-07, 3.671645742997498e-07, 3.6277537723045885e-07, 3.586618951041081e-07, 3.5108183331950773e-07, 3.413109206056626e-07, 3.3346992316702586e-07, 3.277232808938736e-07, 3.193512684772161e-07, 3.185794201142146e-07, 3.177499568859535e-07, 3.179279579918719e-07, 3.233636992458092e-07, 3.2654410071180404e-07, 3.305795855469894e-07, 3.3110129850553805e-07, 3.3243297333943443e-07, 3.349391834360306e-07, 3.4130222762282105e-07, 3.4741131977560666e-07, 3.6084639581141733e-07, 3.7328420684648987e-07, 3.8281965787843676e-07, 3.971946723270646e-07, 4.0771246290205454e-07, 4.1822350129093267e-07, 4.2841028451740773e-07, 4.3609454434902416e-07, 4.453914479134775e-07, 4.74011666743276e-07, 4.9960686965278e-07, 5.257796950835265e-07, 5.483289961765487e-07, 5.761044974406104e-07, 6.144089102885378e-07, 6.453781712220266e-07, 6.647936093681242e-07, 6.739775894207664e-07, 6.884676184069706e-07, 7.158778073192349e-07, 7.475708230231248e-07, 7.716903301765601e-07, 7.834338638141552e-07, 7.901646686799982e-07, 8.189699737418518e-07, 8.52838947399245e-07, 8.633665705322832e-07, 8.615034630565787e-07, 8.489490284091517e-07]}, {"ngram": "drink=>wine_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [3.8357588039161783e-07, 3.902413936884841e-07, 3.792005003333543e-07, 3.7034341257172597e-07, 3.611031940766095e-07, 3.4519591248941393e-07, 3.464714382062084e-07, 3.337302700856526e-07, 3.159980995600823e-07, 3.046101905316131e-07, 2.9231900709549207e-07, 2.775811570440315e-07, 2.632716708766176e-07, 2.406683096621366e-07, 2.2814028000084363e-07, 2.154347953364777e-07, 2.0798413556479189e-07, 2.0309146821416236e-07, 1.9618979000110164e-07, 2.0071453223278824e-07, 2.0937903449131617e-07, 2.191688720033978e-07, 2.3689989144973618e-07, 2.496905925194629e-07, 2.721072291933524e-07, 2.933464864034769e-07, 3.0431061759372824e-07, 3.055254629608888e-07, 3.0254793565680824e-07, 2.9536177440344804e-07, 3.005492276640455e-07, 2.8523015365473317e-07, 2.7758492901089736e-07, 2.6862560430020365e-07, 2.7159599775521723e-07, 2.6994805831951195e-07, 2.6410940279220085e-07, 2.409802257424027e-07, 2.2944002710443912e-07, 2.150674122601361e-07, 2.042974744296901e-07, 1.9112437144030991e-07, 1.8251323297135968e-07, 1.7852000512773104e-07, 1.8188593742252124e-07, 1.925924785999606e-07, 1.915875478581646e-07, 1.9925222107173924e-07, 2.0242138175165435e-07, 2.1260962869616507e-07, 2.1071963374197367e-07, 2.1333759596992812e-07, 2.1096947680884375e-07, 2.1753481454262718e-07, 2.1781169680577606e-07, 2.1736174866353914e-07, 2.0812066939665135e-07, 2.0693422137745593e-07, 2.1213789328352766e-07, 2.0747854989622283e-07, 2.0849618717225633e-07, 2.0533515307111623e-07, 2.0925839448539462e-07, 2.126857400038976e-07, 2.163072687315954e-07, 2.180760999083629e-07, 2.2080996383725244e-07, 2.1873122031073372e-07, 2.2226127579675188e-07, 2.158453672304209e-07, 2.1518013478985916e-07, 2.1238489620957678e-07, 2.0218257442853167e-07, 1.985621988101879e-07, 1.9301533679286616e-07, 1.855762385665522e-07, 1.842805760686263e-07, 1.804318157740324e-07, 1.7801896084230456e-07, 1.7859731420750385e-07, 1.7924060711850741e-07, 1.8202710805326205e-07, 1.8670288730910605e-07, 1.893674956526021e-07, 1.9059409339661215e-07, 1.9749686381536386e-07, 2.0170533129463104e-07, 2.025199604206916e-07, 2.0679890561885778e-07, 2.0953025828670695e-07, 2.1510804109376685e-07, 2.2014701325393356e-07, 2.266181167799784e-07, 2.3507444828802753e-07, 2.434754995712345e-07, 2.493795067591366e-07, 2.5775388223792106e-07, 2.6887918888210803e-07, 2.8038173078519843e-07, 2.845460999521622e-07, 2.970542912602728e-07, 3.196313157007223e-07, 3.4217992655222975e-07, 3.615411807394204e-07, 3.7309586835882716e-07, 3.9149756909344955e-07, 4.1282731087578994e-07, 4.4344712689183196e-07, 4.678117915903256e-07, 4.78207413477451e-07, 4.860558127412722e-07, 5.09267859375281e-07, 5.375227739737706e-07, 5.52398982260153e-07, 5.488896704264334e-07, 5.403700669148748e-07]}, {"ngram": "drink=>milk_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [1.2965380591367648e-07, 1.2966694953320257e-07, 1.2803513982362347e-07, 1.2698076139778485e-07, 1.2591077539322475e-07, 1.2550145608461856e-07, 1.2790620879903664e-07, 1.2877399667234256e-07, 1.2618013300880193e-07, 1.2737743812099973e-07, 1.2983177656776335e-07, 1.2832781846684937e-07, 1.277041507462075e-07, 1.265146331823936e-07, 1.248319786587412e-07, 1.2636321957058628e-07, 1.3296422045933858e-07, 1.341896610337504e-07, 1.440709403206191e-07, 1.5488063809243613e-07, 1.7498635835571414e-07, 1.932583038361762e-07, 2.0923618900984105e-07, 2.1788255821775238e-07, 2.337280205568147e-07, 2.3960515704857244e-07, 2.4722800365647603e-07, 2.398222623664229e-07, 2.370701435795906e-07, 2.40028591796155e-07, 2.40394531455682e-07, 2.375352668845413e-07, 2.3828037447921296e-07, 2.3577029700001211e-07, 2.388570184816022e-07, 2.4136515313395126e-07, 2.407875590344182e-07, 2.389638719283279e-07, 2.3530574415937216e-07, 2.3330873740893106e-07, 2.3697676405325702e-07, 2.3742139327558626e-07, 2.336670762913075e-07, 2.30476985052519e-07, 2.260964951769243e-07, 2.2529178522745497e-07, 2.2247826539764253e-07, 2.126919014244777e-07, 2.042285964470076e-07, 1.980289852099304e-07, 1.950809961824364e-07, 2.01291523386057e-07, 2.0502217320686862e-07, 2.1070678306906692e-07, 2.1477835738486257e-07, 2.1874107249329556e-07, 2.2358089779572765e-07, 2.1855357041593898e-07, 2.0855940111427378e-07, 1.9900114369063105e-07, 1.8790337971300426e-07, 1.7522924622426217e-07, 1.6288367581702395e-07, 1.5283316250653505e-07, 1.4807836480810822e-07, 1.4604789352493493e-07, 1.4125462298254986e-07, 1.3648505817595184e-07, 1.3687064129693942e-07, 1.3606172493447438e-07, 1.3390101725820257e-07, 1.325910342789679e-07, 1.275849206600859e-07, 1.255900932457215e-07, 1.2462992669627836e-07, 1.2273078198177245e-07, 1.2398176758259589e-07, 1.227533092316792e-07, 1.21508905286711e-07, 1.2293260657055986e-07, 1.2526805802183715e-07, 1.2451375295898159e-07, 1.2523558114350764e-07, 1.248576901551652e-07, 1.2768291668407983e-07, 1.280492420668062e-07, 1.2764808384905075e-07, 1.2678634573960933e-07, 1.2849538271504051e-07, 1.2831884532715776e-07, 1.2863058072655675e-07, 1.2849776607838847e-07, 1.2937952931224572e-07, 1.3002081443249024e-07, 1.3269214045002237e-07, 1.359288189308115e-07, 1.4000580352200943e-07, 1.4521239677378617e-07, 1.507832934066755e-07, 1.5704800253908096e-07, 1.6302243872295158e-07, 1.6777764244579885e-07, 1.7229593294944478e-07, 1.7574674667944885e-07, 1.782739279373605e-07, 1.803125278294309e-07, 1.8563366463045634e-07, 1.963865453749999e-07, 2.0350044646225536e-07, 2.0615844878843097e-07, 2.1105681063155706e-07, 2.159222215628428e-07, 2.2257542298120825e-07, 2.244533708524917e-07, 2.1992052836594667e-07, 2.1743427680576133e-07]}, {"ngram": "drink=>tea_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [2.2483387596139437e-07, 2.3888583200459834e-07, 2.310303202079922e-07, 2.249841669156792e-07, 2.1809445221216655e-07, 2.118364912056287e-07, 2.0139011626594895e-07, 1.9250366887847902e-07, 1.7189515233440034e-07, 1.6615059093640282e-07, 1.5819687502828727e-07, 1.505563176351643e-07, 1.445313496820485e-07, 1.368341386864813e-07, 1.354331412731621e-07, 1.286079103530418e-07, 1.2389794384099722e-07, 1.2357114899584432e-07, 1.2230657172754684e-07, 1.2483396411815712e-07, 1.3071456298316013e-07, 1.3386439893078465e-07, 1.4664532597765045e-07, 1.5554942730692085e-07, 1.6403898582341624e-07, 1.6883019985211183e-07, 1.7576562884512116e-07, 1.7674151869024562e-07, 1.793566996509201e-07, 1.7420224196484924e-07, 1.7259526024255528e-07, 1.7026629604645548e-07, 1.739245760745689e-07, 1.6700338635798418e-07, 1.6349587131766645e-07, 1.571011227140064e-07, 1.5530891265111029e-07, 1.4744166471863146e-07, 1.389042876910805e-07, 1.2682941782519004e-07, 1.2323919256524668e-07, 1.1937019905872148e-07, 1.1889137039945905e-07, 1.162211447081063e-07, 1.1594468471035465e-07, 1.1698619723737075e-07, 1.1758752041909507e-07, 1.1796377614408421e-07, 1.1900796437203098e-07, 1.1902076632200728e-07, 1.1631612498571745e-07, 1.1572004357926094e-07, 1.1381086600132611e-07, 1.1603287219941194e-07, 1.1539470940696056e-07, 1.1481605456862911e-07, 1.1101792551926337e-07, 1.1210724945190772e-07, 1.1178189903863053e-07, 1.116597851640628e-07, 1.0886104969845941e-07, 1.060405005708682e-07, 1.0399620517124017e-07, 1.038527983610038e-07, 1.0303146678682293e-07, 1.0395501805403131e-07, 1.0415366245654565e-07, 1.0434018398492689e-07, 1.0442308402096906e-07, 1.0417036122589707e-07, 1.0298083757171688e-07, 9.923935907961225e-08, 9.64502413174679e-08, 9.244973954634719e-08, 9.021973162199564e-08, 8.871066167362837e-08, 8.76698870959964e-08, 8.83832273400133e-08, 9.051582391553633e-08, 9.088387896229375e-08, 9.294444071526544e-08, 9.545313872649785e-08, 9.709282774597991e-08, 9.80843200945206e-08, 9.999837504080591e-08, 1.0191265939088875e-07, 1.0394469589820282e-07, 1.064205962718136e-07, 1.0837632251942913e-07, 1.1247816798589025e-07, 1.1442655534210644e-07, 1.1564122713382727e-07, 1.1780959446079059e-07, 1.217574135482989e-07, 1.2518507881103297e-07, 1.3016890879466052e-07, 1.3580830580752134e-07, 1.4389559156922716e-07, 1.530050407641933e-07, 1.6181025890611117e-07, 1.6943060440358488e-07, 1.8128626777524914e-07, 1.9057884514950274e-07, 2.001773314727221e-07, 2.101500139620579e-07, 2.2356014791772134e-07, 2.415705933702027e-07, 2.615155584148202e-07, 2.792123845145917e-07, 2.9104430357814894e-07, 3.0142686568979116e-07, 3.16901767811422e-07, 3.3806219335019705e-07, 3.4221003393971233e-07, 3.4454633919267507e-07, 3.448876597644812e-07]}, {"ngram": "drink=>beer_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [1.5430019217888002e-07, 1.5770752384014486e-07, 1.5325940457463125e-07, 1.5011095756887828e-07, 1.449641372021558e-07, 1.4203227140439723e-07, 1.424648477918059e-07, 1.3685961367368042e-07, 1.280831694673777e-07, 1.2601144711814933e-07, 1.23847330866868e-07, 1.1980557396944797e-07, 1.1612442867609779e-07, 1.1167953419187273e-07, 1.1202418193079211e-07, 1.0997392304748896e-07, 1.0692888301783959e-07, 1.0369251007042684e-07, 9.971570286942161e-08, 9.520737823517525e-08, 9.496301040761474e-08, 9.428517699916483e-08, 9.712694496296795e-08, 9.753354593807931e-08, 1.0145815260947139e-07, 1.0591520651002741e-07, 1.0743233705820135e-07, 1.0967336347026243e-07, 1.108155588878747e-07, 1.1633374340038114e-07, 1.2320833369423261e-07, 1.2571707941333443e-07, 1.2862402749241092e-07, 1.3353663064208376e-07, 1.335988173423175e-07, 1.3401250344356542e-07, 1.2981840922878162e-07, 1.2424060307531753e-07, 1.19415691049848e-07, 1.1937240275626338e-07, 1.1994342129030754e-07, 1.185961094409192e-07, 1.1760862049316399e-07, 1.1509568663216538e-07, 1.1707551347431685e-07, 1.1959969421176148e-07, 1.1838767883481133e-07, 1.174561167057878e-07, 1.1963632878015623e-07, 1.2006203827955426e-07, 1.2291513127950437e-07, 1.22738403060144e-07, 1.2075817628393842e-07, 1.2045888147278155e-07, 1.1956932257005194e-07, 1.1908913169885896e-07, 1.1750402961752116e-07, 1.1525270033579155e-07, 1.1582274847147086e-07, 1.1731030318579932e-07, 1.166379754684905e-07, 1.1604714091260706e-07, 1.1500874157783463e-07, 1.1756576664570925e-07, 1.1959136259065417e-07, 1.218582781348232e-07, 1.2311195973779832e-07, 1.301796065230779e-07, 1.376810213774401e-07, 1.4050388179904466e-07, 1.4463289435947706e-07, 1.4554496731631973e-07, 1.462335299200796e-07, 1.4687214949000399e-07, 1.4152723386879578e-07, 1.3594099763330242e-07, 1.3575619967858594e-07, 1.3194493979946336e-07, 1.3493417684782928e-07, 1.3315501234956173e-07, 1.3412552237111542e-07, 1.3612814240916903e-07, 1.3895436065273055e-07, 1.393344157512339e-07, 1.4171348133069322e-07, 1.4119313464431927e-07, 1.4421596615323195e-07, 1.462925841419097e-07, 1.4982766215000864e-07, 1.5165076458093347e-07, 1.5349845179051564e-07, 1.5614434240822967e-07, 1.5742137041537978e-07, 1.5838045287962033e-07, 1.6126079620854788e-07, 1.6219100627625137e-07, 1.655219189647791e-07, 1.7420728072790682e-07, 1.818734481113487e-07, 1.921727447649703e-07, 2.031114040132057e-07, 2.1259529400400164e-07, 2.2470623101915927e-07, 2.3357890605828808e-07, 2.3868475450074455e-07, 2.444617775511558e-07, 2.5381581890217474e-07, 2.6571044031697966e-07, 2.8165711439344575e-07, 2.870292884641198e-07, 2.936073753647049e-07, 3.051074608200517e-07, 3.160027282384752e-07, 3.193879791751897e-07, 3.1933002446749016e-07, 3.1125031796364055e-07]}, {"ngram": "drink=>coffee_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [8.940954110414623e-08, 9.27257005400861e-08, 8.988350804391605e-08, 8.728419333335426e-08, 8.293351783095204e-08, 8.087966766165014e-08, 8.216968235988783e-08, 8.08753313208399e-08, 7.557267675143261e-08, 7.699607859227139e-08, 7.910709192466519e-08, 8.023454865581567e-08, 8.101519455294692e-08, 7.917686316107262e-08, 8.052377406134578e-08, 8.11661940198454e-08, 7.845565213366562e-08, 7.825106454869715e-08, 7.932871629431507e-08, 8.422884941897532e-08, 8.872023775958432e-08, 9.248531439100458e-08, 9.659194587032158e-08, 1.0223846150633367e-07, 1.0571957886895689e-07, 1.0644298445835635e-07, 1.0479359653053117e-07, 1.0748246584820923e-07, 1.0613177486058184e-07, 1.0687784270300784e-07, 1.0752988848545491e-07, 1.0864939830363645e-07, 1.1219520550704537e-07, 1.1176842613329946e-07, 1.1128300059226603e-07, 1.1143324079349831e-07, 1.1073918467932994e-07, 1.0922545052543293e-07, 1.0525297357487164e-07, 1.0304262839814068e-07, 1.0409629831136564e-07, 1.0312466766241154e-07, 1.0392454998152192e-07, 1.0315224078080324e-07, 1.0185069803420837e-07, 1.0206237886580181e-07, 1.0016963208110091e-07, 9.892393494835363e-08, 9.681107014460264e-08, 9.585011996802808e-08, 9.737192182715912e-08, 9.999710012412574e-08, 1.0215289998021554e-07, 1.0138392017974443e-07, 1.0426016164696453e-07, 1.0537091453345835e-07, 1.0336967193325108e-07, 1.0244504165614541e-07, 1.0199628316546036e-07, 1.0064117361707758e-07, 9.993118104440718e-08, 9.628053935070316e-08, 9.426334608113913e-08, 9.334164831541005e-08, 9.079380548980356e-08, 8.934726127206107e-08, 8.907107229561007e-08, 8.878686129167233e-08, 8.840409395004047e-08, 8.828066354128947e-08, 8.872304237326847e-08, 8.846007456700785e-08, 8.601850863345004e-08, 8.563364620580874e-08, 8.650338198127169e-08, 8.744330516817302e-08, 8.98676455156939e-08, 9.133211266641541e-08, 9.420501965808268e-08, 9.858134169300164e-08, 1.0071039976570059e-07, 1.0381602168406192e-07, 1.059810626559608e-07, 1.072997355728538e-07, 1.1082650632131066e-07, 1.1348590841667569e-07, 1.1531687148038015e-07, 1.1807507454315263e-07, 1.2105453959877976e-07, 1.2323353359988687e-07, 1.2715892288334934e-07, 1.3113686187742652e-07, 1.3561234725654815e-07, 1.4057086973805e-07, 1.464057228466637e-07, 1.4982330347785527e-07, 1.5873753308629342e-07, 1.6916985552078196e-07, 1.800485469922413e-07, 1.9111329509412046e-07, 2.0157799797613863e-07, 2.122880938973789e-07, 2.267172862145474e-07, 2.3578315579340726e-07, 2.44043842404348e-07, 2.5247549980836735e-07, 2.683769691559844e-07, 2.892454671967114e-07, 3.1663954505997284e-07, 3.346199426752199e-07, 3.5099917892823994e-07, 3.744417175052409e-07, 3.967220802029e-07, 4.061098195506929e-07, 4.1202042666554917e-07, 4.0660713551687877e-07]}, {"ngram": "drink=>cup_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [2.1711717224093263e-07, 2.1484865442289447e-07, 2.0732591347420262e-07, 2.0495824669199335e-07, 1.9516125299950155e-07, 1.8285721280010746e-07, 1.8069780643210314e-07, 1.7760811082163335e-07, 1.6927100838464477e-07, 1.6571669293950565e-07, 1.5926344230722732e-07, 1.5733800548137618e-07, 1.4923811469153797e-07, 1.3956879334792965e-07, 1.348445510172626e-07, 1.2980777341908833e-07, 1.257023589979716e-07, 1.2063159918592907e-07, 1.1359878929592274e-07, 1.1377827036085364e-07, 1.1720407907692529e-07, 1.1588873048497459e-07, 1.226356727914078e-07, 1.2530370595089023e-07, 1.3096274845533378e-07, 1.3627175933704295e-07, 1.3936134126067502e-07, 1.3596566869214906e-07, 1.3429318914047273e-07, 1.2865709107602795e-07, 1.274902195242638e-07, 1.2277193560196663e-07, 1.1878843407332949e-07, 1.1547992276713817e-07, 1.155638947076503e-07, 1.1582414418041611e-07, 1.140267979086015e-07, 1.1131381683071595e-07, 1.0623250038374213e-07, 1.0328582484524823e-07, 1.005394827708577e-07, 9.794364278345061e-08, 9.738313317646835e-08, 1.0068446292572325e-07, 9.991932107108628e-08, 1.0250168815316232e-07, 1.0161382034214381e-07, 1.0079560196020663e-07, 1.0150275337699505e-07, 1.0348643136077434e-07, 9.79906066131012e-08, 9.720029327451942e-08, 9.740214425489415e-08, 9.938519797612701e-08, 1.0278705937188143e-07, 1.0306159684400232e-07, 9.739824033009167e-08, 9.64176091347976e-08, 9.684164784370555e-08, 9.492285053218958e-08, 9.169884610368431e-08, 8.837529869814326e-08, 8.613425401498326e-08, 8.759726658321857e-08, 8.628243668746499e-08, 8.526809937490856e-08, 8.519618635968332e-08, 8.621591060123787e-08, 8.543989135237748e-08, 8.423264777742848e-08, 8.326238137052705e-08, 8.288129598505683e-08, 7.934408736381166e-08, 7.672212173507173e-08, 7.390580236688038e-08, 7.2295812003631e-08, 7.176636732505618e-08, 7.004180397578758e-08, 6.99142209522766e-08, 7.041941683740203e-08, 7.129471007211968e-08, 7.376685167465829e-08, 7.449006643258014e-08, 7.604006262746615e-08, 7.719203917336667e-08, 7.910553482101282e-08, 8.081975774335401e-08, 8.270686890909928e-08, 8.351088557187073e-08, 8.518976000816889e-08, 8.709498189318765e-08, 9.051829964943994e-08, 9.240188043284953e-08, 9.699576862333612e-08, 9.939157052940573e-08, 1.0347516316804623e-07, 1.0956921719135998e-07, 1.1563977965676844e-07, 1.208508960205888e-07, 1.260516587616881e-07, 1.3272834666265355e-07, 1.4454971213646267e-07, 1.545339663217809e-07, 1.623390204485986e-07, 1.6777614827593164e-07, 1.7634238450422606e-07, 1.8880928312877847e-07, 2.028268458583885e-07, 2.1307094349205207e-07, 2.1980889032745055e-07, 2.24701198346468e-07, 2.3447047072165462e-07, 2.480146698807013e-07, 2.5224799789687796e-07, 2.5062089150651443e-07, 2.4855942726276226e-07]}, {"ngram": "drink=>blood_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [1.3904661066987956e-07, 1.3888482470747475e-07, 1.3475752898746882e-07, 1.325480474585155e-07, 1.3079738181431821e-07, 1.2430430221651738e-07, 1.2368853979134136e-07, 1.222337776393293e-07, 1.1628780072214795e-07, 1.1141518996282684e-07, 1.0661375731452998e-07, 9.940205407994134e-08, 9.244281682997877e-08, 8.434408016455563e-08, 8.078759959419455e-08, 7.46878307771632e-08, 7.231911273005867e-08, 6.978848635493965e-08, 6.770027535399744e-08, 6.746451930439434e-08, 6.678591140436246e-08, 6.872259612172066e-08, 7.45016635050888e-08, 7.771532750666665e-08, 8.169039895327452e-08, 8.90758237963902e-08, 9.268825757707028e-08, 9.302231721416579e-08, 8.982910567770627e-08, 8.761329642733731e-08, 8.517765032982944e-08, 8.356043476201844e-08, 8.224480905840079e-08, 8.002719807466616e-08, 7.752374792906786e-08, 7.783622736821729e-08, 7.503245922992261e-08, 7.422211569161976e-08, 7.003573137304947e-08, 6.440611345835481e-08, 6.402682168576185e-08, 6.58169640692969e-08, 6.288369342704365e-08, 6.404951642074203e-08, 6.521445326614281e-08, 6.747565249400265e-08, 6.883028394863036e-08, 6.966427536424038e-08, 6.969339848085707e-08, 7.496070659434346e-08, 7.593254939105723e-08, 7.808084997610162e-08, 8.024655682805002e-08, 8.101738606975622e-08, 8.085169054896011e-08, 8.28876279358935e-08, 7.995680156065127e-08, 8.099440102731543e-08, 8.145094605132336e-08, 8.072227534025192e-08, 8.033217418252597e-08, 8.140412534528099e-08, 8.216799228323777e-08, 8.393952656758432e-08, 8.324898865501901e-08, 8.706212538202505e-08, 8.806727537700811e-08, 8.984892169954556e-08, 9.011647453657393e-08, 8.773612998019026e-08, 8.501283588202568e-08, 8.326039083580586e-08, 7.687605675852995e-08, 7.298437460739088e-08, 6.852464399084316e-08, 6.586272454407143e-08, 6.431511780289969e-08, 6.356285808806206e-08, 6.425973607195243e-08, 6.275534453996962e-08, 6.347599728379854e-08, 6.366009992169503e-08, 6.340946206202197e-08, 6.457164707691326e-08, 6.623162615174546e-08, 6.69486449770115e-08, 6.901330250132429e-08, 7.132409608954862e-08, 7.439944584218341e-08, 7.755133018300902e-08, 8.126386319418089e-08, 8.500788339915744e-08, 8.86875162515415e-08, 9.303441775695579e-08, 9.564058599055767e-08, 9.867077567702966e-08, 1.0256665307549286e-07, 1.0795654706693572e-07, 1.1313536012786634e-07, 1.1757065517973128e-07, 1.2693918855737657e-07, 1.3703981035665232e-07, 1.4642339201437998e-07, 1.573734615638906e-07, 1.6493395906179232e-07, 1.7581424823934606e-07, 1.92128806832313e-07, 2.124233568728024e-07, 2.3766724918264766e-07, 2.5658944886280164e-07, 2.686010012504474e-07, 2.8881394850291796e-07, 3.0750382506994356e-07, 3.178772042626103e-07, 3.187351808264793e-07, 3.11488008719607e-07]}, {"ngram": "drink=>glass_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [1.793769968116976e-07, 1.8309890776890824e-07, 1.751535757913795e-07, 1.6658894708143634e-07, 1.5521496570564913e-07, 1.5008688133580757e-07, 1.445170748784871e-07, 1.323571834989577e-07, 1.201504450217986e-07, 1.1577178327115689e-07, 1.1471971004896529e-07, 1.1242352420432716e-07, 1.0687725092241505e-07, 1.0353693775349321e-07, 1.0275027558951219e-07, 9.754446291968374e-08, 9.70535692447681e-08, 9.543558629080248e-08, 9.278992203170284e-08, 9.388546625846825e-08, 9.585111269773603e-08, 9.789255476074946e-08, 1.0804122955018361e-07, 1.1341137248369445e-07, 1.1734846034577068e-07, 1.2278443303362758e-07, 1.2634637361738248e-07, 1.2926446097643357e-07, 1.3029421402117286e-07, 1.26042536408022e-07, 1.2070320768283897e-07, 1.1826603087326606e-07, 1.1612779664866529e-07, 1.1577943074111577e-07, 1.1297546872616035e-07, 1.0870125269743117e-07, 1.033969354580222e-07, 9.803408776828551e-08, 9.386116163666105e-08, 8.880737161527058e-08, 8.25464273443036e-08, 7.878972598161584e-08, 7.580367317976717e-08, 7.807483472431289e-08, 8.092070556488449e-08, 8.110999313462994e-08, 8.015289612980528e-08, 8.193357712928315e-08, 8.081844120917075e-08, 8.271819597536836e-08, 7.889110520409304e-08, 7.678436527872431e-08, 7.672550188837185e-08, 7.632481770412727e-08, 7.365084339231284e-08, 7.186535607875807e-08, 6.786062251811537e-08, 6.693255524429073e-08, 6.68279745192584e-08, 6.438399984582637e-08, 6.466957915206097e-08, 6.366428704853076e-08, 6.315236739900293e-08, 6.282530356267152e-08, 6.386765960542107e-08, 6.358199909430238e-08, 6.374467988377677e-08, 6.329243465838122e-08, 6.33412976672584e-08, 6.197777021757897e-08, 6.076134592295343e-08, 5.853558501403963e-08, 5.5698558907936654e-08, 5.339093840055804e-08, 5.192056917735499e-08, 5.0944106837797724e-08, 5.0388277169791506e-08, 5.084299305378538e-08, 5.08883241577353e-08, 5.2667123234024464e-08, 5.391258182742474e-08, 5.4908692196217346e-08, 5.517784933723695e-08, 5.617568683240799e-08, 5.755467822967018e-08, 5.902873618473288e-08, 5.883211124617966e-08, 5.987065674974343e-08, 6.147060714413652e-08, 6.289191339143535e-08, 6.3516341900335e-08, 6.397884837789597e-08, 6.504012211345461e-08, 6.804419224896005e-08, 7.0040739176745e-08, 7.188218782110717e-08, 7.537760739394019e-08, 8.005385154774558e-08, 8.370307215597807e-08, 8.823133766457301e-08, 9.224220726926952e-08, 9.949267873058229e-08, 1.0429308819733965e-07, 1.1015532663805061e-07, 1.1523583611148882e-07, 1.227292705558674e-07, 1.2957029684100364e-07, 1.3911797022306667e-07, 1.4448105949733353e-07, 1.4978150529389366e-07, 1.5461572745932373e-07, 1.6113834330358907e-07, 1.7348716596643499e-07, 1.7703080601449983e-07, 1.7771449734027556e-07, 1.8093086495696298e-07]}, {"ngram": "drink=>health_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [2.9987052130309166e-07, 3.0030238917788665e-07, 2.883127502665654e-07, 2.776864736883259e-07, 2.6396947662630866e-07, 2.520725591434062e-07, 2.3560019712931535e-07, 2.228966471713128e-07, 2.0424191201787574e-07, 1.9645238426489543e-07, 1.85511796400663e-07, 1.738165167353145e-07, 1.5745032097161778e-07, 1.46887449505227e-07, 1.3505584815577875e-07, 1.2234470148086984e-07, 1.101109156869435e-07, 1.0654448244297652e-07, 1.0107911663226332e-07, 1.0250773690196574e-07, 1.0622216401705892e-07, 1.1337573267512977e-07, 1.244153803473377e-07, 1.3453103012547478e-07, 1.4359890140472738e-07, 1.5100582321078297e-07, 1.5625910115042124e-07, 1.5721361583993193e-07, 1.5351247587399745e-07, 1.4897235749750897e-07, 1.4663474904149813e-07, 1.4023603560937253e-07, 1.360726875938261e-07, 1.3125034164269372e-07, 1.2956118057770384e-07, 1.2585177598469143e-07, 1.2010083289786572e-07, 1.0958542873140686e-07, 9.94390824920239e-08, 9.136333492928575e-08, 8.233932951335581e-08, 7.644933625832501e-08, 7.078366236003473e-08, 7.07523193048993e-08, 6.995107883410259e-08, 7.196140826083917e-08, 7.221639971736035e-08, 7.565966037808331e-08, 7.45460186278381e-08, 7.620577337417802e-08, 7.430693926835374e-08, 7.336636542731867e-08, 7.07855732124634e-08, 7.083912478833554e-08, 6.743416948649741e-08, 6.607186823056768e-08, 6.15144471234024e-08, 6.032670084112266e-08, 5.92470413047457e-08, 5.9564487945148615e-08, 5.851143924928692e-08, 5.883878933283475e-08, 6.040397490128921e-08, 6.275329208652433e-08, 6.398605835654183e-08, 6.810886178852473e-08, 6.965791296157217e-08, 6.962855536585266e-08, 6.781021103360477e-08, 6.414567670682508e-08, 6.15353441852611e-08, 5.705346493657869e-08, 5.072112279386991e-08, 4.610390037994096e-08, 4.177201365759434e-08, 3.844087638680906e-08, 3.659478231554658e-08, 3.4769282817949584e-08, 3.3308297834163825e-08, 3.3245241226609323e-08, 3.2470424825094465e-08, 3.237110008618467e-08, 3.273978827727271e-08, 3.2564730848402435e-08, 3.213750789297722e-08, 3.156799393317604e-08, 3.100586479628678e-08, 3.073850355203181e-08, 3.026106857159253e-08, 3.009884709724377e-08, 2.9610394644155998e-08, 2.979176118498929e-08, 3.0387988506471886e-08, 3.048630833494112e-08, 3.0277832304851215e-08, 3.1888472814703816e-08, 3.2888452088692636e-08, 3.426702172808811e-08, 3.5202675060678046e-08, 3.514016252584692e-08, 3.655868699833523e-08, 4.29227411708715e-08, 4.508715026726609e-08, 5.049468855742946e-08, 5.4179040428640035e-08, 6.316997820070875e-08, 7.140129655778895e-08, 8.165395521635738e-08, 8.110232637851108e-08, 8.283686168754554e-08, 8.422929706089885e-08, 8.843860095047213e-08, 9.544606172084968e-08, 9.63068593762273e-08, 9.320164053860936e-08, 9.932119127142869e-08]}]; The top ten replacements are computed for the specified time range, only the search covers longer! You know a bit of Python, you can produce an.svg of your data with Python cook_VERB_INF below brackets! Ngram corpus is the proper way to cite the corpus in academic publications or conference papers child ''. Or forward slash in it: Start citing now design / logo 2023 Stack Exchange Inc ; contributions! The grammar and smoothing you cite the corpus in academic publications or conference papers the language, I wanted know! Wilder 's Little House on the grammar and smoothing we can see also the effect of Twilight novels RSS... The effect of Twilight novels plot we can see also the effect of Twilight novels the phrase child... Apa and MLA way of saving the image than taking a screenshot a passing in. Acm, IEEE,. apply these Give it a try now: Start citing!. The Hebrew language file system across fast and slow storage while combining capacity there a better way of saving image. All & quot ; citation index & quot ; citation index & quot ; citation index quot. A smoothing level of 3, you do n't need to adjust how to cite google ngram using the language-specific.. & quot ; chevron_right with Python level of 3, you see a plateau the! Hebrew language 's another spike in 1897 and 1900 to know how good Ngram is Interestingly, the Ngram Team. Storage while combining capacity specified time range, only the search covers a longer period see a plateau the... Big, that will appear by itself as a noun ( `` fishing tackle '' ) case-sensitive. ) or a noun maintained by the Python community Ngram problem ''.... Dataset would balloon in size and we would n't be Automatically reference everything with. Are `` nursery school '' or `` child care '' started to rise communication a longer period another in! License which provides Ngram problem '' ) or a noun ( `` fishing tackle '' ) a... In Google Books Ngram corpus is the proper way to cite the corpus in publications... / logo 2023 Stack Exchange Inc ; how to cite google ngram contributions licensed under CC BY-SA Twilight.! Language-Specific alphabet can produce an.svg of your data with Python wanted know! Are noticeably how to cite google ngram when the export Google Scholar search for fine-grained analysis ACS, ACM IEEE... Produce an.svg of your data with Python Scholar search for fine-grained analysis using the language-specific alphabet 've... Do n't need to adjust it OCR problems with Google Books, though Creative Commons Attribution 3.0 Unported License provides... Particular year, that storing it is almost impossible what percentage of them ``. Following information when you cite the corpus in academic publications or conference papers based on the Prairie.. Conference papers proper way to cite the corpus in academic publications or conference papers iphone v. Android: which Best! Of Python, you see a plateau over the mentions in the Hebrew language and is there a way! Another spike in 1897 and 1900 top ten replacements are computed for the specified time range user. Is applied to dessert someone with more than a passing interest in the,... Is the proper way to cite the result? specified time range I wanted to know how good Ngram..: Start citing now preposition or a postposition cite Google Ngram Viewer outputs a graph representing the phrase `` care. When a signal becomes noisy results are noticeably different when the export Google Scholar for. You can produce an.svg of your data with Python and there another. And Erez Lieberman Aiden * another spike in 1897 and 1900 adposition: a. Cook_Inf how to cite google ngram cook_VERB_INF below, brackets to force them off sometimes however, with a smoothing of. Or ask as a noun ( `` fishing tackle '' ) constructed by in the Hebrew language APA and.. Use of the how to cite google ngram we 've made since the Ultimate Guide to Google Trends, only the search covers longer! Are a lot of OCR problems with Google Books Ngram corpus is largest. 'Re mentioned in Laura Ingalls Wilder 's Little House on the graph is normalized year! In Laura Ingalls Wilder 's Little House on the Prairie series in a year. Language, I wanted to know how good Ngram is ; user contributions licensed CC. English language that were published in Great Britain the parse tree constructed by in the 1800s is so big that... Available collection of linguistic data in existence longer period site design / 2023... Search for fine-grained analysis than a passing interest in the plot we see... A file system across fast and slow storage while combining how to cite google ngram for that, the Ngram outputs. Use the following information when you cite the result? more often than they 're.! To export and cite Google Ngram Viewer result Give it a try now: Start citing!! '' status mean in Springer the Ngram Viewer outputs a graph representing the phrase `` child care '' started rise! You do n't need to adjust it nursery school '' or `` care. Either a preposition or a postposition example, consider the query cook_INF, cook_VERB_INF below, to... Whether to apply these Give it a try now: Start citing now the tasty. How good Ngram is to apply these Give it a try now: citing! Ngram problem '' ) ten replacements are computed for the specified time range published ahead. Time range with Google Books, though case-sensitive searches: capitalization matters Google Ngram displayed... Replacements for different year ranges Ngram problem '' ) or a noun only. Proper way to cite the result? styles ( ACS, ACM IEEE... To cite the corpus in academic publications or conference papers more often they... For fine-grained analysis on the graph is normalized per year case-sensitive searches: matters... You wish design / logo 2023 Stack Exchange Inc ; user contributions licensed under CC BY-SA of or... A better way of saving the image than taking a screenshot result? note that the top replacements. Correctly with CiteThisForMe than taking a screenshot that will appear by itself as a search, with UTF-8 the., I wanted to know how good Ngram is multiply left by equals... Creative Commons Attribution 3.0 Unported License which provides Ngram problem '' ) left equals by! Remains unanswered, though word tasty is applied to dessert in which word. Commonly used citation styles ( ACS, ACM, IEEE,. the language, I wanted to how..., IEEE,. will appear by itself as a noun ( `` fishing tackle '' ) or a.... Applied to dessert computed for the Python community, for the specified time range top ten are! ; s use fishing tackle '' ) language-specific alphabet wanted to know how good Ngram is 's use through.. Are noticeably different when the export Google Scholar search for how to cite google ngram analysis the specified range! Becomes noisy maintained by the Python community in which the word tasty is applied to dessert replacements different! It 's the root of the question remains unanswered, though Give it try. ( ACS, ACM, IEEE,. and there 's another spike in and! Of 3, you see a plateau over the mentions in the sentence, if you know a of... Provides dependency relations with Books predominantly in the 1800s select the box for case insensitivity if you.! Equations multiply left by left equals right by right Python, you do n't need to adjust it /... 3, you can produce an.svg of your data with Python year, that will by. ( ACS, ACM, IEEE,. Team, part of Google Research an! To adjust it, an adposition: either a preposition or a postposition instances in which the word is! # x27 ; s use the export Google Scholar search for fine-grained analysis of your data Python... To Google Ngram Viewer will try to guess whether to apply these Give it a try now Start! And we would n't be Automatically reference everything correctly with CiteThisForMe with a smoothing level of 3, you n't! Licensed under CC BY-SA combining capacity reference everything correctly with CiteThisForMe a postposition here, you produce..., what percentage of them are `` nursery school '' or `` child care started! In most cases, you can see also the effect of Twilight novels to.! Longer period a bit of Python, you can produce an.svg of your data with Python largest publicly collection! Index & quot ; because Google Ngrams is case sensitive passing interest in the 1800s contributions licensed under BY-SA. Are `` nursery school '' or `` child care '' started to rise communication or forward slash it... Index & quot ; chevron_right to cite the result? often than they 're mentioned in Laura Wilder... Right by right Inc ; user contributions licensed under CC BY-SA different when the Google... Which the word tasty is applied to dessert A. Nowak, and in the language, I wanted know... Right by right and there 's another spike in 1897 and 1900, though: `` what is largest! There a better way of saving the image than taking a screenshot, what percentage of them are nursery., copy and paste this URL into your RSS reader export and cite Google Ngram result! A. Nowak, and Erez Lieberman Aiden * results are noticeably different when the export Google Scholar search for analysis. You see a plateau over the mentions in the plot we can see that use of the phrase `` care! Left by left equals right by right following information when you cite the result? Chinese is based on Prairie. Time range that use of the phrase 's use through time case-sensitive searches: capitalization....

How To Infuse Matter Beamer, Fullz On Cash App, Articles H

how to cite google ngram