Remove/Replace/Extract Person Tags

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Description

Remove/replace/extract person tags from a string.

Usage

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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"), ...)

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).

Value

Returns a character string with person tags removed.

See Also

gsub, stri_extract_all_regex

Other rm_.functions: as_numeric, as_numeric2, ex_number, rm_number; as_time, as_time2, ex_time, ex_transcript_time, rm_time, rm_transcript_time; ex_abbreviation, rm_abbreviation; ex_angle, ex_bracket, ex_bracket_multiple, ex_curly, ex_round, ex_square, rm_angle, rm_bracket, rm_bracket_multiple, rm_curly, rm_round, rm_square; ex_between, ex_between_multiple, rm_between, rm_between_multiple; ex_caps_phrase, rm_caps_phrase; ex_caps, rm_caps; ex_citation_tex, rm_citation_tex; ex_citation, rm_citation; ex_city_state_zip, rm_city_state_zip; ex_city_state, rm_city_state; ex_date, rm_date; ex_default, rm_default; ex_dollar, rm_dollar; ex_email, rm_email; ex_emoticon, rm_emoticon; ex_endmark, rm_endmark; ex_hash, rm_hash; ex_nchar_words, rm_nchar_words; ex_non_ascii, rm_non_ascii; ex_non_words, rm_non_words; ex_percent, rm_percent; ex_phone, rm_phone; ex_postal_code, rm_postal_code; ex_repeated_characters, rm_repeated_characters; ex_repeated_phrases, rm_repeated_phrases; ex_repeated_words, rm_repeated_words; ex_title_name, rm_title_name; ex_twitter_url, ex_url, rm_twitter_url, rm_url; ex_white, ex_white_bracket, ex_white_colon, ex_white_comma, ex_white_endmark, ex_white_lead, ex_white_lead_trail, ex_white_multiple, ex_white_punctuation, ex_white_trail, rm_white, rm_white_bracket, rm_white_colon, rm_white_comma, rm_white_endmark, rm_white_lead, rm_white_lead_trail, rm_white_multiple, rm_white_punctuation, rm_white_trail; ex_zip, rm_zip

Examples

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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",
    "tyler.rinker@gamil.com 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")

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