Distant Reader Study Carrel

About your study carrel

This page outlines the breadth & depth of your "study carrel" -- the results & analysis of your Distant Reader submission. Peruse the content of this page, and then consider learning how to dig deeper by reading the Distant Reader Study Carrel Cookbook. If you want "just the facts", then consider reading this text's synopsis.

Size & scope

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 74 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 421816 words long. [0] Each item in your study carrel is, on average, 5700.0 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 histograms and box plots illustrate the overall size of your study carrel.


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 52.0. [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 histograms and box plots illustrate the overall readability of your study carrel.

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: library, research, information, students, libraries, librarians, academic, data, literacy, study, use, college, instruction, faculty, also, university, one, journal, student, online, work, percent, may, learning, assessment. [3] Using the three most frequent words, the three files containing all of those words the most are ./txt/crl-acrl-org-5375.txt, ./txt/crl-acrl-org-6917.txt, and ./txt/crl-acrl-org-7910.txt.

The most frequent two-word phrases (bigrams) include: information literacy, research libraries, college research, available online, academic libraries, library instruction, et al, academic librarians, academic library, higher education, literacy instruction, open access, information science, data curation, academic librarianship, united states, new york, state university, accessed february, critical information, literacy skills, data management, information privilege, library value, library anxiety, and the three file that use all of the three most frequent phrases are ./txt/crl-acrl-org-6917.txt ./txt/crl-acrl-org-4055.txt, and ./txt/crl-acrl-org-7910.txt.

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




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: libraries, library, student, librarian, researcher, students, chapter, researchers, data, https, studied, studying, journal, learn, research, universities, accessed, book, course, informally, librari, literacies, researched, researching, sciences. And now word clouds really begin to shine:


Through the use of a concordance -- a keyword-in-context tool, or a "poor man's search engine" -- you can see how words are used in relation to other words. Here is a random sample of concordance entries using the two most significant keyword as input:

ources researchers perceptions of the library leadership support and communication coordin
ront ed kr roberto college research libraries january jefferson nc mcfarland emily drabins
ies minor changes or major renovation library review no conclusion julie a gedeon and rich
erformance guidelines to all areas of library work peer review was considered in developin
g and sustaining change in academic libraries and librarianship the respondents seem to re
anuary sharon bostick and bryan irwin library design in the age of technology planning for
aration for a diverse set of goals in library instruction here the authors aim to inspiret
able within the peer group used total library staff size ranged from to and student popula
t httphdlhandlenet mdp accessed april library of congress copyright office catalog of copy
age preferences of students to actual library collections services and resources further m
nita j and robert e simpson dean of libraries and university librarian all at university o
minist pedagogy feminist pedagogy for library instruction her personal narrative really he
er wrong planet member who states the library is an awesome place i like just being able t
these respondents indicating that the library was somewhat involved with these two hips wh
libraries no july doi crl sonia smith library instruction for romanized hebrew journal of 
functional to individuals with autism library media connection no aug theresa l schlabach 
n are databases n search strategies n library use in general n and the online catalog n th
gher ratings might be that in these libraries the annual evaluation gives librarians feedb
ve of those who offer both integrated library instruction and creditbearing instruction th
lts combined with the fact that alkek library has its largest door counts during the semes
temcwp pp accessed january though the library of congresss guidance on chicago style does 
ians and research a study of canadian library administrator perspectives college research 
h ethics committee college research libraries november appendix unit site news posts about
rightgovhistory actpdf accessed april library of congress copyright office catalogue of co
riting processes borrowing from the libraries instruction philosophy of meeting students a

Topic modeling

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 library, and ./txt/crl-acrl-org-4596.txt is most about that word.

If your study carrel could be summed up in three words ("topics") then those words might be: library, research, and information. And the respective files would be: ./txt/crl-acrl-org-6917.txt, ./txt/crl-acrl-org-9960.txt, and ./txt/crl-acrl-org-9557.txt.

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:

  1. information library students - ./txt/crl-acrl-org-6917.txt
  2. data library libraries - ./txt/crl-acrl-org-2293.txt
  3. information research journal - ./txt/crl-acrl-org-9557.txt
  4. library students research - ./txt/crl-acrl-org-4596.txt
  5. research authors academic - ./txt/crl-acrl-org-5375.txt

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

Nouns & 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 (library, research, student, information, %, librarian, study, literacy, journal, libraries, book, university, datum, college, faculty, instruction, survey, work, percent, assessment, year, academic, course, group, institution) helps you answer what questions; "What is discussed in this collection?" An enumeration of the lemmatized verbs (be, have, do, use, include, provide, find, make, access, see, base, develop, publish, work, need, ask, give, take, learn, show, identify, describe, help, create, report) 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:



Proper nouns & pronouns

An extraction of proper nouns (Research, Library, Libraries, Information, College, University, Academic, Literacy, Journal, Instruction, OA, Science, Librarian, Assessment, Data, al, Faculty, et, Education, New, Review, Librarians, Association, IL, Learning) helps you determine the names of people and places in your study carrel. An analysis of personal pronouns (it, they, i, we, you, them, she, he, me, us, themselves, one, itself, her, him, y, yourself, ourselves, myself, ‘, herself, ’s, ef-, himself, https://ala-ppo-apply-attachments.s3.amazonaws.com/answerable/attachment/file/26778/aia-poster-final_resize.jpg?awsaccesskeyid=akiajo4ksykhl77iofjq&signature=gicascj51dbtpmyeusutdp%2btfh0%3d&expires=1505178006) 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?" Below are words cloud of your study carrel's proper & personal pronouns.

proper nouns


Adjectives & adverbs

Learning about a corpus's adjectives (academic, other, available, such, more, many, high, important, first, good, different, new, professional, critical, own, digital, large, social, involved, specific, same, significant, most, open, current) and adverbs (not, also, more, online, only, well, as, however, most, very, often, so, even, •, then, out, just, up, rather, somewhat, still, first, here, specifically, further) 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?"




[0] Once upon a time, a corpus of a million words was deemed large.

[1] To put this into context, the typical scholarly journal article is about [NUMBER] words long, Shakespeare's Hamlet is [NUMBER] words long, and the Bible is [NUMBER] words long.

[2] In this case, a Flesch readability score is being calculated. It is based on things like the number of words in a document, the lengths of the words, the number of sentences, the lengths on the sentences, etc. In general children's stories are have lower Flesch scores while insurance documents and doctoral dissertations have higher scores.

[3] "Stop words" are sometimes called "function words", and they are words which carry little or no meaning. Every language has stop words, and in English they include but are not limited to "the", "a", "an", etc. A single set of stop words has been used through out the analysis of your collection.

[4] Concordances are one of the oldest forms of text mining, first developed in the 13th century to "read" religious documents.

[6] An unsupervised machine learning process, topic modeling is a very popular text mining operation. Assuming that a word is known by the company it keeps, topic modeling identifies sets of keywords denoted by their centrality in the text. Words which are both frequent as well as in close proximity to each other are considered significant.