# ------------------------------------- #
# explain variables #
# ------------------------------------- #
# Function that lists an short explanation of what the different column names refer to
# and what their levels consist of.
<- (dataset = ""){
(dataset == "books"){
("The 'books' dataset contains information on several details of the 401
different books used in the survey.
Here follows a list with the different column names and an explanation of
the information they contain:
1. short.title A short name containing the author's name and
(a part of) the title;
2. author Last name and first name of the author;
3. title Full title of the book;
4. title.english Full title of the book in English;
5. genre Genre of the book.
There are four different genres:
a) Fiction; b) Romantic; c) Suspense; d) Other;
6. book.id Unique number to identify each book;
7. riddle.code More complete list of genres of the books.
Contains 13 categories --- to see which, type
`levels(books$riddle.code)` in the terminal;
8. riddle.code.english Translation of code in column 7 in English;
9. translated 'yes' if the book has been translated,
'no' if not;
10. gender.author The gender of the author:
Female, Male, Unknown/Multiple;
11. origin.author The country of origin of the author.
Note that short country codes have been used
instead of the full country names;
12. original.language The original language of the book. Note that short
language codes have been used, instead of the full
language names;
13. inclusion.criterion In what category a book has been placed, either
a) bestseller; b) boekenweekgeschenk;
c) library; or d) literair juweeltje;
14. publication.date Publication date of the book, YYYY-MM-DD format;
15. first.print Year in which the first print appeared;
16. publisher Publishers of the books;
17. word.count Word count, or total number of words (tokens)
used in a book;
18. type.count Total number of unique words (types) used in book;
19. sentence.length.mean Average sentence length in a book (in words);
20. sentence.length.variance Standard deviation of the sentence length;
21. paragraph.count Total number of paragraphs in a book;
22. sentence.count Total number of sentences in a book;
23. paragraph.length.mean Average paragraph length in a book (in words);
24. raw.TTR Lexical diversity, or type-token ratio, which
gives an indication of how diverse the word use
in a book is;
25. sampled.TTR Unlike the raw type-token ratio, the sampled
TTR is significantly more resistant to text
size, and thus it should be preferred over the
raw TTR.
\n")
} (dataset == "reviews"){
("The 'reviews' dataset contains four different ratings that were given
to 401 different books.
Here follows a list with the different column names and an explanation of
what information they contain:
1. respondent.id Unique number for each respondent of the survey;
2. book.id Unique number to identify each book;
3. quality.read Rating on the quality of a book that a respondent
has read. Scale from 1 - 7, with 1 meaning
'very bad' and 7 meaning 'very good';
4. literariness.read Rating on how literary a respondent found a book
that s/he has read. Scale from 1 - 7, with 1 meaning
'not literary at all' and 7 meaning 'very literary';
5. quality.notread Rating on the quality of a book that a respondent
has not read. Scale from 1 - 7, with 1 meaning
'very bad' and 7 meaning 'very good';
6. literariness.notread Rating on how literary a respondent found a book that
s/he has not read. Scale from 1 - 7, with 1 meaning
'not literary at all' and 7 meaning 'very literary';
7. book.read 1 or 0: 1 indicates that the respondent read
the book, 0 indicates the respondent did not
read the book but had an opinion about
the literary quality of the book.
\n")
} (dataset == "respondents"){
("The 'respondents' dataset contains information on the people that participated
in the survey.
Here follows a list with the different column names and an explanation of
what information they contain:
1. respondent.id Unique number for each respondent of the survey;
2. gender.resp Gender of the respondent: Female, Male, NA;
3. age.resp Age of the respondent;
4. zipcode Zip code of the respondent;
5. education Education level, containing 8 levels (see which
levels by typing 'levels(respondents$education)'
in the terminal);
6. education.english English translation of education levels.
7. books.per.year Number of books read per year by each respondent;
8. typically.reads Typical genre of books that a respondent reads,
with three levels a) Fiction; b) Non-fiction;
c) both;
9. how.literary Answer to the question 'How literary a reader do
you consider yourself to be?', where respondents
could fill in a number from 1 - 7, with 1 meaning
'not literary at all' and 7 meaning 'very literary';
10. s.4a1 Answer to the question: 'I like reading novels that
I can relate to my own life'. Scale from 1 - 5, with
1 meaning 'completely disagree', and 5 meaning
'completely agree';
11. s.4a2 Answer to the question: 'The story of a novel is what
matters most to me'. Scale from 1 - 5;
12. s.4a3 Answer to the question: 'The writing style in a book
is important to me'. Scale from 1 - 5;
13. s.4a4 Answer to the question: 'I like searching for deeper
layers in a novel'. Scale from 1 - 5;
14. s.4a5 Answer to the question: 'I like reading literature'.
Scale from 1 - 5;
15. s.4a6 Answer to the question: 'I read novels to discover new
worlds and unknown time periods'. Scale from 1 - 5;
16. s.4a7 Answer to the question: 'I mostly read novels during my
vacation'. Scale from 1 - 5;
17. s.4a8 Answer to the question: 'I usually read several novels at
the same time'. Scale from 1 - 5;
18. s.12b1 Answer to the question: 'I like novels based on real
events'. Scale from 1 - 5;
19. s.12b2 Answer to the question: 'I like thinking about a novel's
structure'. Scale from 1 - 5;
20. s.12b3 Answer to the question: 'The writing style in a novel
is of more importance to me than its story'.
Scale from 1 - 5;
21. s.12b4 Answer to the question: 'I like to get carried away by
a novel'. Scale from 1 - 5;
22. s.12b5 Answer to the question: 'I like to pick my books from
the top 10 list of best sold books'. Scale from 1 - 5;
23. s.12b6 Answer to the question: 'I read novels to be challenged
intellectually'. Scale from 1 - 5;
24. s.12b7 Answer to the question: 'I love novels that are easy
to read'. Scale from 1 - 5;
25. s.12b8 Answer to the question: 'In the evening, I prefer
to read books over watching TV'. Scale from 1 - 5;
26. remarks.survey Any additional remarks that respondents filled in
at the end of the survey;
27. date.time Date and time of the moment a respondent filled in
the survey, format in YYYY-MM-DD HH:MM:SS;
28. week.nr Number of week in which the respondent filled in
the survey;
29. day Day of the week in which the respondent filled in
the survey.
\n")
} (dataset == "motivations"){
("The 'motivations' dataset contains all motivations that people provided
about why they gave a certain book a specific rating. The motivations have been
parsed to provide POS tag information
Here follows a list with the different column names and an explanation of
what information they contain:
1. motivation.id Unique number for each motivation given;
2. respondent.id Unique number for each respondent;
3. book.id Unique number of the book the motivation pertains to;
4. paragraph.id Number of paragraph within the motivation;
5. sentence.id Number of sentence within the paragraph;
6. token Token (in sentence order);
7. lemma Lemma of token;
8. upos POS tag of token;
\n")
} (dataset == "frequencies"){
("This is a dataframe containing numerical values for word frequencies
of the 5000 most frequent words (in a descending order of frequency)
of 401 literary novels in Dutch. The table contains relative frequencies,
meaning that the original word occurrences from a book were divided
by the total number of words of the book in question.
The row names coincide with the column short.title from the data frame books.
The column names list the 5000 most frequent words in the corpus.
\n")
} {
("Please specify either 'books', 'respondents', 'reviews', or 'motivations', \n e.g. explain(\"books\").")
}
}
