rm_citation {qdapRegex}

Remove/Replace/Extract Citations

Description

Remove/replace/extract APA6 style citations from a string.

Counts of normalized citations ("et al." to original author converted to author + year standarization).

Usage

rm_citation(
  text.var,
  trim = !extract,
  clean = TRUE,
  pattern = "@rm_citation",
  replacement = "",
  extract = FALSE,
  dictionary = getOption("regex.library"),
  ...
)

ex_citation(
  text.var,
  trim = !extract,
  clean = TRUE,
  pattern = "@rm_citation",
  replacement = "",
  extract = TRUE,
  dictionary = getOption("regex.library"),
  ...
)

as_count(x, ...)

Arguments

text.var

The text variable.

trim

logical. If TRUE removes leading and trailing white spaces.

clean

trim logical. If TRUE extra white spaces and escaped character will be removed.

pattern

A character string containing a regular expression (or character string for fixed = TRUE) to be matched in the given character vector (see Details for additional information). Default, @rm_citation uses the rm_citation regex from the regular expression dictionary from the dictionary argument.

replacement

Replacement for matched pattern.

extract

logical. If TRUE the dates are extracted into a list of vectors.

dictionary

A dictionary of canned regular expressions to search within if pattern begins with "@rm_".

...

Ignored.

x

The output from ex_citation.

Details

The default regular expression used by rm_citation finds in-text and parenthetical citations. This behavior can be altered by using a secondary regular expression from the regex_usa data (or other dictionary) via (pattern = "@rm_citation2" or pattern = "@rm_citation3"). See Examples for example usage.

Value

Returns a character string with citations removed.

Returns a data.frame of Authors, Years, and n (counts).

Note

This function is experimental.

See Also

gsub, stri_extract_all_regex

Other rm_ functions: rm_abbreviation(), rm_between(), rm_bracket(), rm_caps_phrase(), rm_caps(), rm_citation_tex(), rm_city_state_zip(), rm_city_state(), rm_date(), rm_default(), rm_dollar(), rm_email(), rm_emoticon(), rm_endmark(), rm_hash(), rm_nchar_words(), rm_non_ascii(), rm_non_words(), rm_number(), rm_percent(), rm_phone(), rm_postal_code(), rm_repeated_characters(), rm_repeated_phrases(), rm_repeated_words(), rm_tag(), rm_time(), rm_title_name(), rm_url(), rm_white(), rm_zip()

Examples

## All Citations
x <- c("Hello World (V. Raptor, 1986) bye",
    "Narcissism is not dead (Rinker, 2014)",
    "The R Core Team (2014) has many members.",
    paste("Bunn (2005) said, \"As for elegance, R is refined, tasteful, and",
        "beautiful. When I grow up, I want to marry R.\""),
    "It is wrong to blame ANY tool for our own shortcomings (Baer, 2005).",
    "Wickham's (in press) Tidy Data should be out soon.",
    "Rinker's (n.d.) dissertation not so much.",
    "I always consult xkcd comics for guidance (Foo, 2012; Bar, 2014).",
    "Uwe Ligges (2007) says, \"RAM is cheap and thinking hurts\""
)

rm_citation(x)
ex_citation(x)
as_count(ex_citation(x))
rm_citation(x, replacement="[CITATION HERE]")
## Not run: 
qdapTools::vect2df(sort(table(unlist(rm_citation(x, extract=TRUE)))), 
    "citation", "count")

## End(Not run)

## In-Text
ex_citation(x, pattern="@rm_citation2")

## Parenthetical
ex_citation(x, pattern="@rm_citation3")

## Not run: 
## Mining Citation
if (!require("pacman")) install.packages("pacman")
pacman::p_load(qdap, qdapTools, dplyr, ggplot2)

url_dl("http://umlreading.weebly.com/uploads/2/5/2/5/25253346/whole_language_timeline-updated.docx")

parts <- read_docx("whole_language_timeline-updated.docx") %>%
    rm_non_ascii() %>%
    split_vector(split = "References", include = TRUE, regex=TRUE)
    
parts[[1]]

parts[[1]] %>%
    unbag() %>%
    ex_citation() %>%
    c()

## Counts
parts[[1]] %>%
    unbag() %>%
    ex_citation() %>%
    as_count()
    

## By line
ex_citation(parts[[1]])

## Frequency
cites <- parts[[1]] %>%
    unbag() %>%
    ex_citation() %>%
    c() %>%
    data_frame(citation=.) %>%
    count(citation) %>%
    arrange(n) %>%
    mutate(citation=factor(citation, levels=citation))

## Distribution of citations (find locations and then plot)
cite_locs <- do.call(rbind, lapply(cites[[1]], function(x){
    m <- gregexpr(x, unbag(parts[[1]]), fixed=TRUE)
    data.frame(
        citation=x,
        start = m[[1]] -5,
        end =  m[[1]] + 5 + attributes(m[[1]])[["match.length"]]
    )
}))

ggplot(cite_locs) +
    geom_segment(aes(x=start, xend=end, y=citation, yend=citation), size=3,
        color="yellow") +
    xlab("Duration") +
    scale_x_continuous(expand = c(0,0),
        limits = c(0, nchar(unbag(parts[[1]])) + 25)) +
    theme_grey() +
    theme(
        panel.grid.major=element_line(color="grey20"),
        panel.grid.minor=element_line(color="grey20"),
        plot.background = element_rect(fill="black"),
        panel.background = element_rect(fill="black"),
        panel.border = element_rect(colour = "grey50", fill=NA, size=1),
        axis.text=element_text(color="grey50"),    
        axis.title=element_text(color="grey50")  
    )

## End(Not run)