qdapRegex (version 0.7.5)

rm_tag: Remove/Replace/Extract Person Tags

Description

Remove/replace/extract person tags from a string.

Usage

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

Value

Returns a character string with person tags removed.

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. Default, @rm_tag uses the rm_tag regex from the regular expression dictionary from the dictionary argument.

replacement

Replacement for matched pattern.

extract

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

dictionary

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

...

Other arguments passed to gsub.

Details

The default regex pattern "(?<![@\w])@([a-z0-9_]+)\b" is more liberal and searches for the at (@) symbol followed by any word. This can be accessed via pattern = "@rm_tag". Twitter user names are more constrained. A second regex ("(?<![@\w])@([a-z0-9_]{1,15})\b") is provide that contains the latter word to substring that begins with an at (@) followed by a word composed of alpha-numeric characters and underscores, no longer than 15 characters. This can be accessed via pattern = "@rm_tag2" (see Examples).

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_citation(), 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_time(), rm_title_name(), rm_url(), rm_white(), rm_zip()

Examples

x <- c("@hadley I like #rstats for #ggplot2 work.",
    "Difference between #magrittr and #pipeR, both implement pipeline operators for #rstats:
        http://renkun.me/r/2014/07/26/difference-between-magrittr-and-pipeR.html @timelyportfolio",
    "Slides from great talk: @ramnath_vaidya: Interactive slides from Interactive Visualization
        presentation #user2014. http://ramnathv.github.io/user2014-rcharts/#1",
    "[e-mail] is my email", 
    "A non valid Twitter is @abcdefghijklmnopqrstuvwxyz"
)

rm_tag(x)
rm_tag(rm_hash(x))
ex_tag(x)

## more restrictive Twitter regex
ex_tag(x, pattern="@rm_tag2") 

## Remove only the @ sign
rm_tag(x, replacement = "\\3")
rm_tag(x, replacement = "\\3", pattern="@rm_tag2")