author-chapmanGeorge-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 2021-05-24 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 29 item(s) in this carrel, and this carrel is 4,397,405 words long. Each item in your study carrel is, on average, 151,634 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 98. 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, pos, lemma, pc, reg, acp, sentence, unit, sp, speaker, av, vvi, vvb, seg, pns, po, cs, cc, type, ab, pn, rendition, hi, vvz, contract, will, note, pno, sic, label, corr, vmb, nn, vvn, crq, vvd, join, left, shall, target, now, xx, uh, sir, unclear, good, stage, man, fw

Using the three most frequent words, the three files containing all of those words the most are Two Wise Men and All the Rest Fools, Eastward Ho, and The Gentleman Usher.

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

pc xml, pos acp, unit sentence, pos av, pos vvi, vvi xml, pos vvb, vvb xml, pos pns, pns xml, pos po, po xml, cs xml, av xml, cc xml, sp xml, pos cc, ab xml, sentence speaker, sp sp, pos pn, pn xml, rendition hi, pos vvz, type contract, pos pno, pno xml, vvz xml, pos vmb, pos vvn, vvn xml, nn xml, pos crq, pos vvd, vmb xml, pos cs, vvd xml, will pos, lemma will, join left, contract lemma, note note, seg note, sic seg, seg corr, corr seg, label sic, note target, pos xx, xx xml

And the three file that use all of the three most frequent phrases are Two Wise Men and All the Rest Fools Eastward Ho, and The Gentleman Usher.

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:

xml, speaker, pos="po, pos="pns, pos="n1-nn, pos="n1, pos="fw, pos="d, pos="crq, pos="cc, pos="av_j, pos="av, pos="acp, lemma="the, lemma="his, lemma="her, lemma="have, lemma="for, lemma="but, lemma="be, lemma="and, lemma="all, type="contract2, seg, pos="xx, pos="uh, note, lemma="you, lemma="we, lemma="shall, lemma="not, lemma="do, lemma="can, lemma="as, stage, reg="''ll, lemma="will, lemma="see, lemma="good, join="left">''silouehaue

And now word clouds really begin to shine:

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 Revenge for Honor (The Parricide) 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:

1. xml - May Day
2. xml - Two Wise Men and All the Rest Fools
3. xml - Alphonsus, Emperor of Germany

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:

1. xml, id, pos - Sir Giles Goosecap
2. xml, id, pos - The Gentleman Usher
3. xml, id, pos - Two Wise Men and All the Rest Fools
4. a18407, xml, id - Eastward Ho
5. a18403, a18427, thy - Homer''s Odysses. Translated according to ye Greeke by. Geo: Chapman

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, p, l, pos="n1, id="a31672, >, pos="vvi, id="a18421, pos="n2, cs, id="a18426, id="a18407, sic, pos="po, w, type="unclear, id="a18415, pos="n1-nn, q, r, cc, id="a18403, av, stage, x, lemma="make, g, id="a18416, reg="''ll, type="contract1">i.

id="a18427, note, lemma="i, lemma="your, is, pos="av_j, lemma="by, be, lemma="come, was, lemma="well, lemma="love, did, lemma="more, are, lemma="take, had, lemma="be, lemma="think, made, were, lemma="tell, make, see, pos="acp, let, lemma="life, lemma="great, lemma="friend, lemma="father, lemma="hand, lemma="hear, lemma="at, said, lemma="thing, being, lemma="live, take, come, lemma="king, lemma="death, lemma="speak, know, lemma="bring, lemma="bear, set, lemma="prince, lemma="first, lemma="nothing, neuer

Proper Nouns

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

w, id="a18423, pos="acp, id="a31675, id="a18415, id="a01911, pos="d, id="a18407, id="a69093, id="a18419, pos="j, id="a18413, id="a18426, pos="vvb, xml, id="a18402, pos="pns, id="a18403, pos="po, id="a18421, sp, lemma="be, pos="cc, unit="sentence"/, pos="n, speaker, pos="pn, lemma="and, lemma="the, id="a18425, pos="vvz, id="a18427, id="a31672, pos="av, �, /p, lemma="i, pos="pno, id="a18416, pos="vmb, pos="vvn, lemma="a, lemma="you, pos="crq, lemma="of, lemma="my, lemma="in, lemma="he, lemma="it, type="contract2

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?"

his, i, my, he, her, their, it, you, your, me, him, they, our, thy, she, them, we, thee, who="a18427-bostocke, lemma="thyself, w, mine, lemma="gull, vvith, vp, lemma="back, us, theirs, yours, one, lemma="himself, lemma="breast, ile, ''s, tâ, ours, lemma="throw, yâ, ye, he