This is a Distant Reader "study carrel", a set of structured data intended to help the student, researcher, or scholar use & understand a corpus.
This study carrel was created on 2021-05-25 by Eric Morgan <emorgan@nd.edu>. The carrel was created using the Distant Reader zip2carrel process, and the input was a Zip file locally cached with the name input-file.zip. Documents in the Zip file have been saved in a cache, and each of them have been transformed & saved as a set of plain text files. All of the analysis -- "reading" -- has been done against these plain text files. For example, a short narrative report has been created. This Web page is a more verbose version of that report.
All study carrels are self-contained -- no Internet connection is necessary to use them. Download this carrel for offline reading. The carrel is made up of many subdirectories and data files. The manifest describes each one in greater detail.
There are 36 item(s) in this carrel, and this carrel is 487,197 words long. Each item in your study carrel is, on average, 13,533 words long. If you dig deeper, then you might want to save yourself some time by reading a shorter item. On the other hand, if your desire is for more detail, then you might consider reading a longer item. The following charts illustrate the overall size of the carrel.
On a scale from 0 to 100, where 0 is very difficult and 100 is very easy, the documents have an average readability score of 87. Consequently, if you want to read something more simplistic, then consider a document with a higher score. If you want something more specialized, then consider something with a lower score. The following charts illustrate the overall readability of the carrel.
By merely counting & tabulating the frequency of individual words or phrases, you can begin to get an understanding of the carrel's "aboutness". Excluding "stop words", some of the more frequent words include:
xml, id, lemma, pos, pc, tobacco, reg, shall, will, may, one, good, haue, great, yet, acp, sentence, much, unit, time, now, first, man, also, like, many, tabacco, men, make, sp, speaker, must, take, bee, wine, made, thereof, nature, text, well, doth, selfe, therefore, without, vpon, tcp, vvb, say, body, av
Using the three most frequent words, the three files containing all of those words the most are Wine, Beer, and Ale Together by the Ears, Anno Regni Caroli II. Regis Angliæ, Scotiæ, Franciæ, & Hiberniæ, duodecimo. At the Parliament begun at Westminster, the five and twentieth day of April, an. Dom. 1660 In the twelfth year of the reign of our most gracious soveraign lord Charles, by the grace of God, of England, Scotland, France, and Ireland, King, Defender of the Faith, &c., and Tobacco tortured, or, The filthie fume of tobacco refined shewing all sorts of subiects, that the inward taking of tobacco fumes, is very pernicious vnto their bodies; too too profluuious for many of their purses; and most pestiferous to the publike state. Exemplified apparently by most fearefull effects: more especially, from their treacherous proiects about the Gun-powder Treason; from their rebellious attempts of late, about their preposterous disparking of certaine inclosures: as also, from sundry other their prodigious practices. ....
The most frequent two-word phrases (bigrams) include:
pc xml, pos acp, unit sentence, pos vvb, vvb xml, pos av, pos vvi, vvi xml, pos pns, pns xml, av xml, sp xml, cs xml, pos pn, pn xml, sp sp, cc xml, po xml, pos po, pos cc, type contract, pos vvz, pc speaker, pos vvn, vvn xml, english books, early english, pos pno, pno xml, vvz xml, books online, pos crq, pos vmb, lemma wine, wine pos, ab xml, one thousand, lemma beer, vmb xml, beer pos, reg beer, contract lemma, join left, beer beere, rendition hi, lemma ale, creation partnership, text creation, ale pos, pos cs
And the three file that use all of the three most frequent phrases are Wine, Beer, and Ale Together by the Ears Hymnus tabaci a poem in honour of tabaco. Heroïcally composed by Raphael Thorius: made English by Peter Hausted Mr of Arts Camb., and The complaint of many free-holders, farmer, and others, of the Common-wealth of England Against the unlawfull planting of English tobacco. With an act of Parliament prohibiting the same..
While often deemed superficial or sophomoric, rudimentary frequencies and their associated "word clouds" can be quite insightful:
Sets of keywords -- statistically significant words -- can be enumerated by comparing the relative frequency of words with the number of times the words appear in an entire corpus. Some of the most statistically significant keywords in the carrel include:
tcp, tobacco, man, nature, great, good, english, vse, tabacco, king, haue, time, thing, stomach, pipe, like, god, early, disease, common, body, bee, vnguent, thy, thou, spirits, sir, sin, selfe, scurvy, roman, rec, poet, plant, majesty, maiesties, iohn, indorum, hot, herb, foliorum, england, drunkards, drink, doe, bacchus, ana, act, xml, wounds
And now word clouds really begin to shine:
Topic modeling is another popular approach to connoting the aboutness of a corpus. If the study carrel could be summed up in a single word, then that word might be a01425, and By the King a proclamation restraining the abusive venting of tobacco. is most about that word.
If the study carrel could be summed up in three words ("topics") then those words and their significantly associated titles include:
If the study carrel could be summed up in five topics, and each topic were each denoted with three words, then those topics and their most significantly associated files would be:
Moreover, the totality of the study carrel's aboutness, can be visualized with the following pie chart:
Through an analysis of your study carrel's parts-of-speech, you are able to answer question beyonds aboutness. For example, a list of the most frequent nouns helps you answer what questions; "What is discussed in this collection?":
xml, id="a01425, pc, p, time, man, men, pos="n1, nature, body, persons, part, selfe, text, smoke, things, others, thing, reason, pos="vvi, day, capn, way, parts, place, person, matter, bodies, vse, pos="n2, people, use, doth, fume, water, life, nothing, head, cs, texts, euery, works, bodie, hath, good, themselues, times, places, tobacco, mouth
An enumeration of the verbs helps you learn what actions take place in a text or what the things in the text do. Very frequently, the most common lemmatized verbs are "be", "have", and "do"; the more interesting verbs usually occur further down the list of frequencies:
is, be, are, was, do, being, were, said, have, make, made, take, had, say, been, haue, did, taken, let, see, id="a01425, found, bee, according, put, come, brought, called, set, know, aforesaid, concerning, hath, encoded, am, learned, use, bring, done, vsed, thought, sent, drink, lemma="wine, selfe, pray, appointed, makes, neuer, taking
An extraction of proper nouns helps you determine the names of people and places in your study carrel.
w, id="a01425, tobacco, pos="acp, tabacco, 〉, thou, ◊, 〈, pos="d, pos="vvb, tcp, god, hath, haue, sir, xml, pos="pns, /p, england, lemma="be, sp, pos="pn, speaker, pos="j, hydr, doe, act, english, king, bee, lemma="you, iohn, pos="cc, thomas, pos="vvz, lord, yea, lemma="i, lemma="and, ●, pos="vvn, mr., pos="av, text, county, pos="pno, lemma="the, c., eebo
An analysis of personal pronouns enables you to answer at least two questions: 1) "What, if any, is the overall gender of my study carrel?", and 2) "To what degree are the texts in my study carrel self-centered versus inclusive?"
it, their, i, his, they, them, our, you, he, my, we, your, him, thy, me, her, thee, us, its, themselves, she, himself, vp, one, ours, theirs, yours, mine, u, lemma="thyself, vnto, p, ye, whereof, o, yee, y, th, s, l, hee, whosoever, vvith, there, ob, lemma="vapour, lemma="throw, lemma="himself, k, id="a01425-e106140
Below are words cloud of your study carrel's proper & personal pronouns.
Learning about a corpus's adjectives and adverbs helps you answer how questions: "How are things described and how are things done?" An analysis of adjectives and adverbs also points to a corpus's overall sentiment. "In general, is my study carrel positive or negative?"
such, other, good, same, great, pos="n1, many, unit="sentence">.not, so, then, also, very, now, more, most, yet, therefore, thereof, as, well, much, first, thus, out, too, onely, here, forth, rather, there, away, else, before, together, all, especially, in, up, long, never, at, thereby, likewise, otherwise, ever, only, often, no, once, namely, further, sometimes, still, surely, easily, over, down
There is much more to a study carrel than the things outlined above. Use this page's menubar to navigate and explore in more detail. There you will find additional features & functions including: ngrams, parts-of-speech, grammars, named entities, topic modeling, a simple search interface, etc.
Again, study carrels are self-contained. Download this carrel for offline viewing and use.
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