subject-royalCanadianMountedPolice-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 2021-06-09 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:"Royal Canadian Mounted Police". 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 9 item(s) in this carrel, and this carrel is 613,591 words long. Each item in your study carrel is, on average, 76,698 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 88. 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:

man, one, eyes, like, now, came, men, back, time, face, made, two, see, police, way, little, come, great, get, know, old, moment, saw, will, hand, away, just, must, went, good, head, well, long, night, even, knew, thought, first, life, half, got, voice, last, still, go, something, right, say, thing, big

Using the three most frequent words, the three files containing all of those words the most are The Law-Breakers, Policing the Plains Being the Real-Life Record of the Famous North-West Mounted Police, and The Flaming Forest.

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

mounted police, shan tung, black roger, mary josephine, john keith, rocky springs, first time, roger audemard, two men, years ago, last night, long time, came back, big brother, old man, miriam kirkstone, charlie bryant, carmin fanchet, hundred yards, father layonne, just now, dark eyes, stanley fyles, moment later, blue eyes, bram johnson, get away, concombre bateese, prince albert, brother bill, derwent conniston, one thing, kate seton, come back, marette radisson, five years, meeting house, red river, never seen, great deal, go back, four years, white men, minutes later, hour later, miles away, aunt belle, human life, anne boulain, broken man

And the three file that use all of the three most frequent phrases are Policing the Plains Being the Real-Life Record of the Famous North-West Mounted Police The River''s End, and The Luck of the Mounted: A Tale of the Royal Northwest Mounted Police.

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:

man, mr., god, sure, sergeant, pierre, north, mrs., john, inspector, good, face, eye, blake, yukon, yorke, west, wallie, tung, the.=, tell, superintendent, steele, stanley, st., springs, slavin, shan, seton, roger, rocky, river, riel, redmond, reddy, radisson, post, police, philip, pete, perry, old, olaf, o.c., o''connor, o''brien, norman, mounted, moran, miss

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 man, and The Luck of the Mounted: A Tale of the Royal Northwest Mounted Police 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. man - The Law-Breakers
  2. men - Policing the Plains Being the Real-Life Record of the Famous North-West Mounted Police
  3. pierre - The Flaming Forest

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. man, eyes, like - The Law-Breakers
  2. men, police, mounted - Policing the Plains Being the Real-Life Record of the Famous North-West Mounted Police
  3. pierre, st, david - The Flaming Forest
  4. th, man, yorke - The Luck of the Mounted: A Tale of the Royal Northwest Mounted Police
  5. behave, caps, exchanged - The Return of Blue Pete

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, eyes, men, time, face, way, moment, hand, head, night, life, something, voice, thing, things, door, hands, day, years, place, feet, country, river, heart, police, woman, side, girl, room, mind, trail, work, hair, world, arms, end, cabin, hour, lips, fire, people, part, body, window, thought, nothing, horse, light, sort, brother

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, were, be, have, is, ''s, been, do, came, said, did, made, see, are, come, get, know, saw, went, knew, got, go, seemed, looked, say, tell, ''ve, turned, going, heard, ''m, told, found, has, make, felt, think, ''re, stood, seen, left, take, gone, looking, cried, held, am, took, began

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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.

kent, kate, pierre, keith, police, st., _, charlie, bram, philip, jim, bill, david, mounted, bob, inspector, helen, fyles, carrigan, kedsty, marette, bateese, conniston, indians, yorke, john, slavin, mr., celie, fort, force, the.=, marie, god, sergeant, anne, redmond, mcdowell, north, canada, roger, west, o''brien, shan, tung, mary, th, black, commissioner, blake

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?"

he, his, it, i, you, him, her, she, they, their, them, me, we, my, himself, its, your, us, our, itself, themselves, herself, ''em, one, ''s, yourself, myself, yours, ourselves, hers, mine, em, yu, i''m, ye, ours, oneself, it''s, yourselves, meself, you''ll, on''y, zat, you''re, ya, word--"hiding, well!--time, ut''d, upi''s, theirs

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?"

other, little, great, old, good, own, more, last, big, first, few, long, many, white, same, dead, new, much, open, whole, right, full, such, small, strange, deep, low, red, dark, ready, soft, sure, young, glad, cold, black, next, human, wide, sudden, bad, huge, certain, possible, strong, high, half, hard, heavy, clear

not, up, n''t, then, out, now, so, back, again, there, down, here, just, away, only, on, even, more, still, as, too, never, almost, in, very, suddenly, all, off, well, always, ever, over, once, far, later, slowly, right, no, yet, quite, long, ahead, most, also, before, quickly, swiftly, longer, around, 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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