R/tweet_min_scores.R

In saotd: Sentiment Analysis of Twitter Data

#' @title Twitter Data Minimum Scores
#'
#' @description Determines the minimum scores for either the entire dataset or 
#'   the minimum scores associated with a hashtag or topic analysis.
#'
#' @param DataFrameTidyScores DataFrame of Twitter Data that has been tidy'd 
#'   and scored.
#' @param HT_Topic If using hashtag data select:  "hashtag".  If using topic 
#'   data select:  "topic".
#' @param HT_Topic_Selection The hashtag or topic to be investigated.  NULL will 
#'   find min across entire dataframe.
#'
#' @importFrom dplyr arrange filter quo
#' @importFrom utils head
#' @importFrom tidyr unnest
#'
#' @return A Tibble.
#'
#' @examples
#' \dontrun{
#' library(saotd)
#' data <- raw_tweets
#' tidy_data <- Tidy(DataFrame = data)
#' score_data <- tweet_scores(DataFrameTidy = tidy_data,
#'                            HT_Topic = "hashtag")
#' min_scores <- tweet_min_scores(DataFrameTidyScores = score_data,
#'                                HT_Topic = "hashtag")
#'                             
#' data <- raw_tweets
#' tidy_data <- Tidy(DataFrame = data)
#' score_data <- tweet_scores(DataFrameTidy = tidy_data,
#'                      HT_Topic = "hashtag")
#' min_scores <- tweet_min_scores(DataFrameTidyScores = score_data,
#'                                HT_Topic = "hashtag",
#'                                HT_Topic_Selection = "icecream")
#' }
#' @export

tweet_min_scores <- function(DataFrameTidyScores,
                             HT_Topic,
                             HT_Topic_Selection = NULL) {

  # input checks
  if (!is.data.frame(DataFrameTidyScores)) {
    stop("The input for this function is a data frame.")
  }

  if (!(("hashtag" %in% HT_Topic) | ("topic" %in% HT_Topic))) {
    stop("HT_Topic requires an input of either hashtag for analysis using 
         hashtags, or topic for analysis looking at topics.")
  }

  # configure defusing operators for packages checking
  hashtags <- dplyr::quo(hashtags)
  Topic <- dplyr::quo(Topic)
  TweetSentimentScore <- dplyr::quo(TweetSentimentScore)

  # function main body
  if (HT_Topic == "hashtag" & is.null(HT_Topic_Selection)) {

    TD_HT_noSel_Min_Scores <- DataFrameTidyScores %>%
      dplyr::arrange((TweetSentimentScore)) %>%
      utils::head()

    return(TD_HT_noSel_Min_Scores)

  } else if (HT_Topic == "hashtag" & !is.null(HT_Topic_Selection)) {

    TD_HT_Sel_Min_Scores <- DataFrameTidyScores %>%
      tidyr::unnest(
        cols = hashtags,
        keep_empty = FALSE) %>%
      dplyr::filter(hashtags == HT_Topic_Selection) %>%
      dplyr::arrange((TweetSentimentScore)) %>%
      utils::head()

    return(TD_HT_Sel_Min_Scores)

  } else if (HT_Topic == "topic" & is.null(HT_Topic_Selection)) {

    TD_Topic_noSel_Min_Scores <- DataFrameTidyScores %>%
      dplyr::arrange((TweetSentimentScore)) %>%
      utils::head()

    return(TD_Topic_noSel_Min_Scores)

  } else {

    TD_Topic_Sel_Min_Scores <- DataFrameTidyScores %>%
      dplyr::filter(Topic == HT_Topic_Selection) %>%
      dplyr::arrange((TweetSentimentScore)) %>%
      utils::head()

    return(TD_Topic_Sel_Min_Scores)

  }

}