Distant Reader - our-little-cousin-from-haithi

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 2021-04-21 by Eric Morgan <emorgan@nd.edu>. The carrel was created using the Distant Reader trust process, and the input was a HaithTrust metadata (TSV) file locally cached with the name metadata.tsv. Given the metadata file, associated PDF documents where saved to a a cache and a second set of documents were saved to a set of plain text files. All of the analysis -- "reading" -- has been done against the 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

The study carrel is 237,492 words long. Each item in the study carrel is, on average, 16,963 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 illustrate the overall size of the study 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 91. 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 illustrate the overall readability of the study 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:

little, cousin, one, said, will, great, time, people, story, like, see, many, now, long, day, father, good, mother, must, children, made, home, old, two, house, go, well, came, much, country, boys, us, every, new, cloth, illustrated, young, way, boy, come, city, away, around, place, soon, man, decorative, never, think, men

Using the three most frequent words, the three files containing all of those words the most are: 1) Our little English cousin by Blanche McManus ; illustrated by the author, 2) Our little Russian cousin by M.H. Wade. Illustrated by L.J. Bridgman, and 3) Our little Italian cousin by Mary Hazelton Wade; illustrated by L.J. Bridgman.

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

cloth decorative, little colonel, trade mark, yung pak, little russian, russian cousin, little girl, little argentine, argentine cousin, every one, little english, young people, little italian, swiss cousin, little swiss, italian cousin, english cousin, per volume, norwegian cousin, little norwegian, japanese cousin, little japanese, little korean, korean cousin, chie lo, little roumanian, little siamese, siamese cousin, irish cousin, roumanian cousin, armenian cousin, large mo, viking cousin, little armenian, little irish, little turkish, little viking, turkish cousin, new york, miss green, page company, lotus blossom, let us, long time, long ago, little boy, blue bonnet, years ago, blanche mcmanus, square mo

And the three file that use all of the three most frequent phrases are: 1) Our little Italian cousin by Mary Hazelton Wade; illustrated by L.J. Bridgman, 2) Our little Roumanian cousin by Clara Vostrovsky Winlow ... illustrated by Charles E. Meister, and 3) Francisco, our little Argentine cousin Illustrated by John Goss.

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 study carrel include:

little african cousin, little japanese cousin, little canadian cousin, little norwegian cousin, little italian cousin, little argentine cousin, little australian cousin, little chinese cousin, little philippine cousin, little hungarian cousin, little english cousin, little armenian cousin, little porto rican cousin, little mexican cousin, little irish cousin, little french cousin, little cuban cousin, little indian cousin, little cousin series, little brown cousin, little brazilian cousin, little swiss cousin, little russian cousin, little korean cousin, little jewish cousin, little dutch cousin, little turkish cousin, little scotch cousin, little eskimo cousin, little belgian cousin, little siamese cousin, little hindu cousin, little hawaiian cousin, little egyptian cousin, little bohemian cousin cousin, little boer cousin, little west indian cousin, little viking cousin, little spanish cousin, little roumanian cousin, little portuguese cousin, little jugoslav cousin, little girl, little german cousin, little colonel books, little bohemian cousin, bohemian cousin cousin, yung pak, wonder chin, vikings

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 little, and Our little Italian cousin by Mary Hazelton Wade; illustrated by L.J. Bridgman 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 your 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:

little, cousin, said - Our little English cousin by Blanche McManus ; illustrated by the author
little, cousin, said - Our little Roumanian cousin by Clara Vostrovsky Winlow ... illustrated by Charles E. Meister
little, francisco, cousin - Francisco, our little Argentine cousin Illustrated by John Goss
little, cousin, pak - Our little Korean cousin by H. Lee M. Pike; illustrated by L.J. Bridgman
lotus, naked, woke - Our little Japanese cousin by Mary Hazelton Wade; illustrated by L. J. Bridgman

Moreover, the totality of the study carrel's aboutness, can be visualized with the following pie chart:

Noun & Verbs

Through an analysis of the 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?":

time, people, story, day, mother, father, children, boys, boy, house, country, way, man, men, place, home, cloth, city, one, room, life, book, night, water, side, things, girl, eyes, family, years, stories, morning, work, books, girls, days, king, volume, river, land, chapter, friends, world, child, part, head, hand, 12mo, cousin, thing

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:

was, is, were, had, are, be, have, said, do, been, see, did, has, made, go, came, come, think, went, get, make, tell, look, take, know, told, illustrated, called, looked, asked, seen, let, heard, am, seemed, say, saw, like, put, left, cried, found, took, began, passed, going, brought, keep, thought, hear

Proper Nouns

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

Cousin, Little, Francisco, Carl, Colonel, Pak, Jonitza, Yung, Tessa, Mrs., Mari, Biarne, Chin, Edith, Artin, New, Norah, Eric, Osman, Mark, Trade, L., PAGE, English, E., America, Ole, Boston, Mr., Miss, Beppo, Leif, C., Nicolaia, Petrovna, Vikings, Jose, Thor, Lo, England, York, Lucy, Adelaide, Chie, Swiss, Uncle, London, Green, Siamese, Ireland

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, he, they, his, our, i, you, their, her, them, she, we, him, my, us, me, its, your, himself, themselves, herself, one, itself, myself, yourself, ours, 's, thee, ourselves, theirs, yours, thy, ’s, ye, our-, mine, hers, him-, be-, you,—you, tht, thou, sea-, oneself, hor-, fifty-, eng-, cer-, ani-

Below are words cloud of the 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 this study carrel positive or negative?"

little, great, many, good, other, old, long, young, decorative, beautiful, big, own, large, small, new, more, much, such, ready, last, white, same, few, full, poor, bright, red, fine, first, high, next, strange, best, russian, several, korean, interesting, glad, dear, happy, wonderful, whole, sure, italian, blue, lovely, hard, strong, illustrated, turkish

not, so, very, up, now, then, out, as, n't, only, here, down, well, away, there, soon, never, just, too, back, much, once, all, again, ever, on, more, even, far, over, always, also, off, most, still, quite, home, together, long, enough, often, first, almost, indeed, ago, in, perhaps, however, along, before

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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