subject-motionPictureIndustry-gutenberg


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 2021-06-07 by Eric Morgan <emorgan@nd.edu>. The carrel was created using the Distant Reader gutenberg process, and the input was the result of a query applied to a local mirror of Project Gutenberg -- facet_subject:"Motion picture industry". Then, for future reference, the results were saved to a Zip file complete with rudimentary bibliographics. The name of the file is input-file.zip. The Zip file was then unpacked and the contents saved to a cache as well as a directory 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 11 item(s) in this carrel, and this carrel is 538,501 words long. Each item in your study carrel is, on average, 48,954 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.

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histogram of sizes
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box plot of sizes

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 89. 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.

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histogram of readability
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box plot of readability

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:

one, ruth, mr, know, like, now, will, man, well, clancy, get, helen, see, time, just, back, miss, got, picture, little, good, says, right, girl, way, make, go, lucinda, come, tom, made, much, think, kid, first, two, never, away, old, room, janet, eyes, must, thing, even, going, us, might, tell, hand

Using the three most frequent words, the three files containing all of those words the most are Ruth Fielding in the Great Northwest; Or, The Indian Girl Star of the Movies, Linda Lee, Incorporated: A Novel, and Ruth Fielding on the St. Lawrence; Or, The Queer Old Man of the Thousand Islands.

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

ruth fielding, new york, miss deane, uncle john, red mill, miss vincent, dakota joe, indian girl, le drieux, young man, last night, de vronde, jennie stone, old man, van ness, henry thorne, moving picture, sophie carey, thousand dollars, aunt alvirah, miss williams, los angeles, lord howe, motion picture, aunt kate, tom cameron, clancy deane, florine ladue, come back, miss lee, first time, miss fielding, linda lee, uncle jabez, jack andrews, go back, young woman, betty gordon, kid scanlan, just now, right now, film city, chess copley, asked helen, miss ruth, cried helen, fifth avenue, plump girl, one thing, looked like

And the three file that use all of the three most frequent phrases are Ruth Fielding in the Great Northwest; Or, The Indian Girl Star of the Movies Ruth Fielding Down East; Or, The Hermit of Beach Plum Point, and Ruth Fielding on the St. Lawrence; Or, The Queer Old Man of the Thousand Islands.

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

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unigrams
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bigrams

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:

mr., miss, helen, tom, ruth, red, mill, hammond, york, wonota, new, mrs., joe, jennie, harold, fielding, zinn, zenith, zenda, willis, williams, west, weber, walbrough, vronde, vincent, vandervent, van, untz, uncle, totantora, tony, thorne, summerlad, stone, stanton, spofford, sophie, scanlan, sangoa, rosalie, roland, randall, potts, point, pipes, patsy, nolan, ness, nelly

And now word clouds really begin to shine:

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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 said, and Kid Scanlan 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. ruth - Linda Lee, Incorporated: A Novel
  2. clancy - Find the Woman
  3. said - Aunt Jane''s Nieces out West

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. ruth, said, clancy - Find the Woman
  2. lucinda, janet, ll - Linda Lee, Incorporated: A Novel
  3. kid, says, like - Kid Scanlan
  4. said, jones, mr - Aunt Jane''s Nieces out West
  5. roland, says, tom - Breaking into the movies

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

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topic model

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?":

man, time, picture, girl, way, room, eyes, thing, day, hand, clancy, girls, door, head, something, face, woman, night, car, nothing, people, anything, life, men, moment, money, part, business, father, story, one, name, work, place, hands, guy, things, scene, side, course, boy, matter, morning, company, voice, office, camera, mind, pictures, house

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, had, is, be, do, have, ''s, said, were, been, are, did, know, get, see, got, ''m, says, go, has, come, make, made, think, going, ''ve, ''re, tell, want, say, take, asked, let, went, came, am, knew, told, looked, look, seemed, put, give, find, thought, found, saw, does, turned, seen

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nouns
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verbs

Proper Nouns

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

_, ruth, mr., helen, miss, lucinda, tom, janet, kid, clancy, mrs., roland, wonota, jennie, carey, hammond, bel, jones, new, uncle, york, deane, john, fielding, joe, patsy, summerlad, vandervent, zenda, conwell, randall, sp, red, fanny, beiner, nolan, lontaine, bellamy, aunt, arthur, maud, lynn, enrico, mill, harold, scanlan, walbrough, rosalie, linda, spofford

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, he, she, it, her, his, him, they, me, we, my, them, your, their, us, its, herself, our, himself, ''em, myself, one, yourself, ''s, themselves, itself, yours, mine, hers, ourselves, i''m, em, oneself, you''re, theirs, andrews, ye, huh, he''sa, yourselves, you''ll, ours, i''ve, hopin, d''you, you?--the, you--_and, yer, yehself

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

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proper nouns
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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?"

little, other, good, old, more, first, young, own, last, much, sure, big, right, great, few, many, same, new, such, long, several, white, next, indian, real, best, better, ready, poor, afraid, least, most, only, able, small, open, bad, whole, possible, full, hard, glad, enough, high, true, pretty, dear, certain, second, large

n''t, not, up, so, then, out, now, just, here, as, back, down, all, too, only, never, away, again, over, very, even, there, in, more, on, well, off, ever, still, right, much, really, once, enough, quite, almost, always, rather, most, at, long, perhaps, yet, around, far, of, suddenly, finally, soon, first

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adjectives
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adverbs

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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