R/tableTag.R

In bibliometrix: Comprehensive Science Mapping Analysis

#' Tabulate elements from a Tag Field column
#'
#' It tabulates elements from a Tag Field column of a bibliographic data frame.
#'
#' \code{tableTag} is an internal routine of main function \code{\link{biblioAnalysis}}.
#'
#' @param M is a data frame obtained by the converting function \code{\link{convert2df}}.
#'        It is a data matrix with cases corresponding to articles and variables to Field Tag in the original WoS or SCOPUS file.
#' @param Tag is a character object. It indicates one of the field tags of the
#'   standard ISI WoS Field Tag codify.
#' @param sep is the field separator character. This character separates strings in each column of the data frame. The default is \code{sep = ";"}.
#' @param ngrams is an integer between 1 and 3. It indicates the type of n-gram to extract from titles or abstracts.
#' @param remove.terms is a character vector. It contains a list of additional terms to delete from the documents before term extraction. The default is \code{remove.terms = NULL}.
#' @param synonyms is a character vector. Each element contains a list of synonyms, separated by ";",  that will be merged into a single term (the first word contained in the vector element). The default is \code{synonyms = NULL}.
#' @return an object of class \code{table}
#' @examples
#'
#' data(scientometrics, package = "bibliometrixData")
#' Tab <- tableTag(scientometrics, Tag = "CR", sep = ";")
#' Tab[1:10]
#'
#' @export
tableTag <- function(M, Tag = "CR", sep = ";", ngrams = 1, remove.terms = NULL, synonyms = NULL) {
  ## check and remove duplicated
  M <- M[!duplicated(M$SR), ]

  if (Tag %in% c("AB", "TI")) {
    M <- termExtraction(M, Field = Tag, stemming = F, verbose = FALSE, ngrams = ngrams, remove.terms = remove.terms, synonyms = synonyms)
    i <- which(names(M) == paste(Tag, "_TM", sep = ""))
    remove.terms <- NULL
    synonyms <- NULL
  } else {
    i <- which(names(M) == Tag)
  }

  if (Tag == "C1") {
    M$C1 <- gsub("\\[.+?]", "", M$C1)
  }

  Tab <- unlist(strsplit(as.character(M %>% dplyr::pull(i)), sep))

  ### inserted to remove punct and extra spaces ####
  Tab <- trimws(gsub("\\s+|\\.|\\,", " ", Tab))
  ####
  # Tab<-Tab[Tab!=""]
  Tab <- Tab[nchar(Tab) > 0]

  # Merge synonyms in the vector synonyms
  if (length(synonyms) > 0 & is.character(synonyms)) {
    s <- strsplit(toupper(synonyms), ";")
    snew <- trimws(unlist(lapply(s, function(l) l[1])))
    sold <- (lapply(s, function(l) trimws(l[-1])))
    for (i in 1:length(s)) {
      Tab[Tab %in% unlist(sold[[i]])] <- snew[i]
    }
  }

  Tab <- sort(table(Tab), decreasing = TRUE)
  # remove terms from ID and DE
  if ((Tag %in% c("DE", "ID", "KW_Merged")) & (!is.null(remove.terms))) {
    term <- setdiff(names(Tab), toupper(remove.terms))
    Tab <- Tab[term]
  }

  return(Tab)
}