Distant Reader - author-wallerEdmund-freebo

Introduction

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 2021-05-23 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.

Size

There are 30 item(s) in this carrel, and this carrel is 664,346 words long. Each item in your study carrel is, on average, 22,144 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.

Readability

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 93. 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.

Word Frequencies

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, reg, pos, facs, pc, acp, vvi, po, cs, av, will, may, sentence, unit, cc, shall, vvb, now, love, pns, vvn, great, make, hi, vvz, like, nn, us, yet, must, rendition, vvd, sir, crq, let, speaker, see, pn, though, first, know, sp, vmb, type, made, one, king, much

Using the three most frequent words, the three files containing all of those words the most are Pompey the Great a tragedy as it was acted by the servants of His Royal Highness the Duke of York / translated out of French by certain persons of honour., The maid''s tragedy altered with some other pieces / by Edmund Waller, Esq. ; not before printed in the several editions of his poems., and Fovr nevv playes viz : The seege of Vrbin, Selindra, Love and frienship, Tragy-comedies, Pandora, a comedy / written by Sr. William Killigrew ....

The most frequent two-word phrases (bigrams) include:

pc xml, pos acp, vvi reg, pos vvi, po reg, pos po, cs reg, pos av, sentence xml, unit sentence, pc unit, cc reg, pos vvb, vvb reg, pos pns, pns reg, av reg, pos cc, pos vvn, vvn reg, vvz reg, pos vvz, nn reg, rendition hi, pos vvd, vvd reg, pos cs, pos crq, pn reg, pos pn, pos vmb, vmb reg, type contract, pos pno, pno reg, ab reg, speaker xml, sp xml, vmd reg, pos vmd, sp sp, join left, contract lemma, lemma will, will pos, pos xx, xx reg, lemma shall, shall pos, pos vvg

And the three file that use all of the three most frequent phrases are Pompey the Great a tragedy as it was acted by the servants of His Royal Highness the Duke of York / translated out of French by certain persons of honour. The maid''s tragedy altered with some other pieces / by Edmund Waller, Esq. ; not before printed in the several editions of his poems., and A worthy speech made in the House of Commons this present Parliament, 1641. 1 That Parliaments are the onely way for advancing the Kings affaires. 2 That the restoring of the property of goods and freedome of the subject is a chiefe meanes to maintaine religion and obedience to His Majestie. By Mr. Waller..

While often deemed superficial or sophomoric, rudimentary frequencies and their associated "word clouds" can be quite insightful:

Keywords

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, english, world, sea, love, speaker, parliament, early, thy, queen, law, king, sun, mr., like, laws, land, lady, house, heaven, xml, war, waller, unit="sentence, type="contract2, type="contract1">''t

And now word clouds really begin to shine:

keywords

Topic Modeling

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 xml, and A discourse upon Gondibert an heroick poem / written by Sr. William D''Avenant ; with an answer to it, by Mr. Hobbs. 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:

Noun & Verbs

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, pc, l, p, pos="n1, pos="n2, pos="vvi, cs, t, love, men, pos="po, self, reg="and, text, time, way, ▪, man, r, heart, w, cc, pos="n1-nn, life, hand, power, cle, death, pos="pns, eyes, lemma="make, art, mind, av, day, others, queen, unit="sentence, name, light, work, things, care, thoughts, rest, none, lon, part, selindra

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, have, are, do, was, did, had, make, were, lemma="i, does, has, see, made, let, know, pos="pns, been, am, lemma="your, give, think, take, find, come, enter, lemma="by, pos="av_j, say, love, done, ''s, tell, go, makes, look, found, live, wish, being, leave, lemma="king, bring, set, lost, appear, pray, lemma="great, become

Proper Nouns

An extraction of proper nouns helps you determine the names of people and places in your study carrel.

w, id="a34585, id="a67336, facs="a67336, pos="acp, pos="j, pos="po, lemma="the, reg="the, xml, unit="sentence, pos="vvb, pos="cc, pos="d, pos="vvn, lemma="and, pos="vvz, reg="to, pc, lemma="be, pos="av, lemma="of, reg="and, pos="crq, reg="of, pos="pn, pos="vvi, pos="vmb, sir, lemma="a, reg="a, pos="pno, lemma="that, pos="pns, pos="cs, lemma="his, lemma="he, lemma="have, thou, reg="i, reg="his, madam, lemma="you, pos="n, duke, lemma="in, speaker, lemma="my, lemma="with, reg="in

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?"

i, you, his, my, your, he, our, their, it, her, they, me, we, him, she, us, them, thy, thee, themselves, himself, its, yours, mine, ''s, ours, ''em, theirs, one, l, lemma="throw, lemma="breast, hers, em, w, us''d, heav''n, unconcern''d, lemma="gull, e''re, >, ●, yhey, ye, wrong''d, wrap''t, whereof, vvith, vvhat, unreveng''d

Below are words cloud of your study carrel's proper & personal pronouns.

Adjectives & Verbs

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?"

pos="n1, such, great, pos="av, own, more, pos="n1-nn, other, good, reg="for, new, first, pos="cs, much, high, same, reg="we, reg="be, fair, many, early, old, true, best, happy, english, whole, little, last, worthy, reg="had, better, reg="me, greater, bold, ill, la, fit, young, late, bright, sacred, full, private, noble, present, long, free, lemma="give, mighty

not, so, then, now, too, more, thus, here, yet, as, never, well, ever, only, out, first, still, much, once, there, up, no, most, onely, long, lemma="which, away, again, off, rather, soon, just, therefore, alone, before, in, even, often, very, down, on, far, all, together, already, above, enough, online, back, better

Next steps

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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