First, the simple things. Your study carrel was created through the submission of a [SINGLE URL|FILE OF URLS|FILE FROM YOUR COMPUTER|ZIP FILE]. This ultimately resulted in a collection of 99 item(s). The original versions of these items have been saved in a cache, and each of them have been transformed & saved as a set of plain text files. All of the following analysis has been done against these plain text files.
Your study carrel is 865,064 words long. [0] Each item in your study carrel is, on average, 20,596 words long. [1] 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 your study carrel.
histogram of sizes
box plot of sizes
Readability
On a scale from 0 to 100, where 0 is very difficult and 100 is very easy, your documents have an average readability score of 69. [2] 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 your study carrel.
histogram of readability
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 your carrel's "aboutness". Excluding "stop words", some of the more frequent words include: [3]
The most frequent two-word phrases (bigrams) include:
href http, li li, td td, edu sandbox, linked data, com blog, src http, open source, text mining, img src, ul li, li strong, li ul, digital humanities, content uploads, blog wp, td tr, source software, edu emorgan, notre dame, code lib, plain text, span nbsp, target blank, com alex, sandbox eebo, align center, alex concordance, wordsearch phrase, zzzz word, segsize usepre, word zzzz, cmd wordsearch, phrase zzzz, usepre word, zzzz bookcode, full text, align right, water collection, sandbox htrc, great books, search results, travel log, tr tr, tr td, emorgan files, sandbox readings, distant reader, great ideas, open access
While often deemed superficial or sophomoric, rudimentary frequencies and their associated "word clouds" can be quite insightful:
unigrams
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 your study carrel include:
Topic modeling is another popular approach to connoting the aboutness of a corpus. If your study carrel could be summed up in a single word, then that word might be li, and is most about that word.
If your 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:
Moreover, the totality of the study carrel's aboutness, can be visualized with the following pie chart:
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?":
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, are, be, was, have, do, were, used, has, use, linked, given, called, been, create, make, using, see, get, based, find, read, created, described, does, done, think, had, provide, written, need, know, go, made, published, describes, include, learn, being, intended, comes, reading, understand, take, creating, named, learned, want, making, found
nouns
verbs
Proper Nouns
An extraction of proper nouns helps you determine the names of people and places in your study carrel.
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?"
Here is a prioritized list of next steps to thus get more out of your study carrel:
browse, sort, and search the content of the menu items named Ngrams, POS, Grammars, and Others found at the top of this page to acquire more detail about your carrel
read standard-output.txt, as it will both summarize and elaborate upon this narrative report
read MANIFEST.htm to both inventory your study carrel as well as learn how to answer more specific questions of it