rtweet: Collecting Twitter Data

#' Emojis codes and descriptions data.
#'
#' This data comes from "Unicode.org",
#' \url{http://unicode.org/emoji/charts/full-emoji-list.html}. The data are
#' codes and descriptions of Emojis.
#'
#' @docType data
#' @name emojis
#' @format A tibble with two variables and 2,623 observations.
#' @examples
#' emojis
"emojis"

#' Language codes recognized by Twitter data.
#'
#' This data comes from the Library of Congress,
#' \url{http://www.loc.gov/standards/iso639-2/ISO-639-2_utf-8.txt}. The data are
#' descriptions and codes associated with internationally recognized languages.
#' Variables include translations for each language represented as
#' bibliographic, terminologic, alpha, english, and french.
#'
#' @docType data
#' @name langs
#' @format A tibble with five variables and 486 observations.
#' @examples
#' langs
"langs"


#' Twitter stop words in multiple languages data.
#'
#' This data comes form a group of Twitter searches conducted at
#' several times during the calendar year of 2017. The data are
#' commonly observed words associated with 10 different languages,
#' including \code{c("ar", "en", "es", "fr", "in", "ja", "pt", "ru",
#' "tr", "und")}. Variables include \code{"word"} (potential stop
#' words), \code{"lang"} (two or three word code), and \code{"p"}
#' (probability value associated with frequency position along a
#' normal distribution with higher values meaning the word occurs more
#' frequently and lower values meaning the words occur less
#' frequently).
#'
#' @docType data
#' @name stopwordslangs
#' @format A tibble with three variables and 24,000 observations
#' @examples
#' stopwordslangs
"stopwordslangs"