R/zzz.R

In bibliometrix: Comprehensive Science Mapping Analysis

#utils::globalVariables("where")
#utils::globalVariables("any_of")
#utils::globalVariables("if_all")

#' @import stats
#' @import dimensionsR
#' @import ggplot2
#' @import bibliometrixData
#' @import forcats
#' @import ggrepel
# @import ggnetwork
#' @import pubmedR
#' @import shiny
#' @import readr
#' @import readxl
#' @import stringi
#' @import tidytext
#' @import openalexR
#' @import ca
#' @importFrom dplyr %>%
#' @importFrom dplyr bind_cols
#' @importFrom dplyr across
#' @importFrom dplyr row_number
#' @importFrom dplyr tibble
#' @importFrom dplyr as_tibble
#' @importFrom dplyr between
## @importFrom dplyr filter
#' @importFrom dplyr arrange
#' @importFrom dplyr do
#' @importFrom dplyr distinct
#' @importFrom dplyr join_by
#' @importFrom dplyr n
#' @importFrom dplyr slice
#' @importFrom dplyr slice_max
#' @importFrom dplyr if_all
#' @importFrom dplyr any_of
#' @importFrom dplyr cummean
#' @importFrom dplyr count
#' @importFrom dplyr desc
#' @importFrom dplyr bind_rows
#' @importFrom dplyr group_by
#' @importFrom dplyr mutate
#' @importFrom dplyr mutate_at
#' @importFrom dplyr mutate_if
#' @importFrom dplyr ungroup
#' @importFrom dplyr rename
#' @importFrom dplyr rename_with
#' @importFrom dplyr rowwise
#' @importFrom dplyr summarise
#' @importFrom dplyr summarize
#' @importFrom dplyr select
#' @importFrom dplyr anti_join
#' @importFrom dplyr inner_join
#' @importFrom dplyr left_join
#' @importFrom dplyr right_join
#' @importFrom dplyr top_n
#' @importFrom dplyr relocate
#' @importFrom dplyr slice_head
#' @importFrom dplyr slice_tail
#' @importFrom dplyr reframe
#' @importFrom plotly add_annotations
#' @importFrom plotly add_lines
#' @importFrom plotly config
#' @importFrom plotly ggplotly
#' @importFrom plotly layout
#' @importFrom plotly plot_ly
#' @importFrom plotly subplot
#' @importFrom plotly toRGB
# #' @import shinycssloaders
# #' @import shinythemes
#' @importFrom openxlsx write.xlsx
#' @importFrom tidyr gather
#' @importFrom tidyr spread
#' @importFrom tidyr pivot_wider
#' @importFrom tidyr pivot_longer
#' @importFrom tidyr replace_na
#' @importFrom tidyr separate
#' @importFrom tidyr drop_na
#' @importFrom tidyr unite
#' @importFrom tidyr starts_with
#' @importFrom tidyr unnest
#' @importFrom graphics abline
#' @importFrom grDevices adjustcolor
#' @importFrom grDevices dev.off
#' @importFrom grDevices pdf
#' @importFrom grDevices chull
#' @importFrom grDevices heat.colors
#' @importFrom DT DTOutput
#' @importFrom DT renderDT
#' @importFrom DT datatable
#' @importFrom stringdist stringdistmatrix
#' @importFrom rscopus affiliation_retrieval
#' @importFrom rscopus author_df_orig
#' @importFrom rscopus author_search
#' @importFrom rscopus get_complete_author_info
# @importFrom RColorBrewer brewer.pal
# @importFrom FactoMineR MCA
# @importFrom FactoMineR CA
# @importFrom FactoMineR PCA
# @importFrom factoextra get_mca_var
# @importFrom factoextra get_mca_ind
# @importFrom factoextra get_ca_row
# @importFrom factoextra get_ca_col
# @importFrom factoextra fviz_nbclust
# @importFrom factoextra fviz_cluster
# @importFrom factoextra fviz_dend
# @importFrom factoextra hcut
#' @importFrom igraph as_long_data_frame
#' @importFrom igraph get.edgelist
#' @importFrom igraph graph_from_data_frame
#' @importFrom igraph as_adjacency_matrix
#' @importFrom igraph graph.adjacency
#' @importFrom igraph degree
#' @importFrom igraph plot.igraph
#' @importFrom igraph delete.vertices
#' @importFrom igraph decompose.graph
#' @importFrom igraph E
#' @importFrom igraph E<-
#' @importFrom igraph V
#' @importFrom igraph V<-
#' @importFrom igraph vcount
#' @importFrom igraph graph_attr
#' @importFrom igraph edge_density
#' @importFrom igraph transitivity
#' @importFrom igraph diameter
#' @importFrom igraph degree_distribution
#' @importFrom igraph centr_degree
#' @importFrom igraph centr_clo
#' @importFrom igraph centr_betw
#' @importFrom igraph centr_eigen
#' @importFrom igraph mean_distance
#' @importFrom igraph closeness
#' @importFrom igraph induced_subgraph
#' @importFrom igraph page.rank
#' @importFrom igraph eigen_centrality
#' @importFrom igraph arpack_defaults
#' @importFrom igraph authority_score
#' @importFrom igraph page_rank
#' @importFrom igraph hub_score
#' @importFrom igraph graph_from_incidence_matrix
#' @importFrom igraph graph_from_adjacency_matrix
#' @importFrom igraph simplify
#' @importFrom igraph layout.auto
#' @importFrom igraph layout.circle
#' @importFrom igraph layout.sphere
#' @importFrom igraph layout.mds
#' @importFrom igraph layout.kamada.kawai
#' @importFrom igraph layout.fruchterman.reingold
#' @importFrom igraph layout.star
#' @importFrom igraph write.graph
#' @importFrom igraph cluster_walktrap
#' @importFrom igraph cluster_leiden
#' @importFrom igraph cluster_optimal
#' @importFrom igraph cluster_infomap
#' @importFrom igraph cluster_edge_betweenness
#' @importFrom igraph cluster_fast_greedy
#' @importFrom igraph cluster_louvain
#' @importFrom igraph cluster_leading_eigen
#' @importFrom igraph cluster_spinglass
#' @importFrom igraph count_multiple
#' @importFrom igraph membership
#' @importFrom igraph layout.norm
#' @importFrom igraph delete.edges
#' @importFrom igraph betweenness
#' @importFrom Matrix %&%
#' @importFrom Matrix abIseq
#' @importFrom Matrix abIseq1
#' @importFrom Matrix all.equal
#' @importFrom Matrix anyDuplicatedT
#' @importFrom Matrix Arith
#' @importFrom Matrix as.array
#' @importFrom Matrix as.matrix
#' @importFrom Matrix band
#' @importFrom Matrix bandSparse
#' @importFrom Matrix bdiag
#' @importFrom Matrix cbind2
#' @importFrom Matrix chol
#' @importFrom Matrix chol2inv
#' @importFrom Matrix Cholesky
#' @importFrom Matrix coerce
#' @importFrom Matrix colMeans
#' @importFrom Matrix colSums
#' @importFrom Matrix Compare
#' @importFrom Matrix condest
#' @importFrom Matrix cov2cor
#' @importFrom Matrix crossprod
#' @importFrom Matrix det
#' @importFrom Matrix determinant
#' @importFrom Matrix diag
#' @importFrom Matrix diag<-
#' @importFrom Matrix diagN2U
#' @importFrom Matrix Diagonal
#' @importFrom Matrix diagU2N
#' @importFrom Matrix diff
#' @importFrom Matrix drop
#' @importFrom Matrix drop0
#' @importFrom Matrix expand
#' @importFrom Matrix expm
#' @importFrom Matrix fac2sparse
#' @importFrom Matrix forceSymmetric
#' @importFrom Matrix format
#' @importFrom Matrix formatSparseM
#' @importFrom Matrix formatSpMatrix
#' @importFrom Matrix head
#' @importFrom Matrix image
#' @importFrom Matrix invPerm
#' @importFrom Matrix is.null.DN
#' @importFrom Matrix isDiagonal
#' @importFrom Matrix isLDL
#' @importFrom Matrix isSymmetric
#' @importFrom Matrix isTriangular
#' @importFrom Matrix kronecker
#' @importFrom Matrix Logic
#' @importFrom Matrix lu
#' @importFrom Matrix Math
#' @importFrom Matrix Math2
#' @importFrom Matrix Matrix
#' @importFrom Matrix MatrixClass
#' @importFrom Matrix mean
#' @importFrom Matrix nnzero
#' @importFrom Matrix norm
#' @importFrom Matrix onenormest
#' @importFrom Matrix Ops
#' @importFrom Matrix pack
#' @importFrom Matrix print
#' @importFrom Matrix printSpMatrix
#' @importFrom Matrix printSpMatrix2
#' @importFrom Matrix qr
#' @importFrom Matrix qr.coef
#' @importFrom Matrix qr.fitted
#' @importFrom Matrix qr.Q
#' @importFrom Matrix qr.qty
#' @importFrom Matrix qr.qy
#' @importFrom Matrix qr.R
#' @importFrom Matrix qr.resid
#' @importFrom Matrix qrR
#' @importFrom Matrix rankMatrix
#' @importFrom Matrix rbind2
#' @importFrom Matrix rcond
#' @importFrom Matrix readHB
#' @importFrom Matrix readMM
#' @importFrom Matrix rep2abI
#' @importFrom Matrix rowMeans
#' @importFrom Matrix rowSums
#' @importFrom Matrix rsparsematrix
#' @importFrom Matrix show
#' @importFrom Matrix skewpart
#' @importFrom Matrix solve
#' @importFrom Matrix sparse.model.matrix
#' @importFrom Matrix sparseMatrix
#' @importFrom Matrix sparseVector
#' @importFrom Matrix spMatrix
#' @importFrom Matrix summary
#' @importFrom Matrix Summary
#' @importFrom Matrix symmpart
#' @importFrom Matrix t
#' @importFrom Matrix tail
#' @importFrom Matrix tcrossprod
#' @importFrom Matrix tril
#' @importFrom Matrix triu
#' @importFrom Matrix uniqTsparse
#' @importFrom Matrix unname
#' @importFrom Matrix unpack
#' @importFrom Matrix update
#' @importFrom Matrix updown
#' @importFrom Matrix which
#' @importFrom Matrix writeMM
# #' @importFrom stringr str_locate_all
# #' @importFrom stringr str_extract_all
# #' @importFrom stringr str_replace_all
#' @importFrom graphics barplot
#' @importFrom graphics legend
#' @importFrom graphics lines
#' @importFrom graphics plot
#' @importFrom graphics par
#' @importFrom grDevices colorRampPalette
#' @importFrom grDevices as.raster
#' @importFrom utils capture.output
#' @importFrom utils data
#' @importFrom utils adist
#' @importFrom utils read.csv
#' @importFrom utils write.csv
#' @importFrom SnowballC wordStem
#' @importFrom SnowballC getStemLanguages
# @importFrom rio import
.onAttach<-function(...){
  packageStartupMessage("Please note that our software is open source and available for use, distributed under the MIT license.\nWhen it is used in a publication, we ask that authors properly cite the following reference:\n\nAria, M. & Cuccurullo, C. (2017) bibliometrix: An R-tool for comprehensive science mapping analysis, 
                        Journal of Informetrics, 11(4), pp 959-975, Elsevier.\n\nFailure to properly cite the software is considered a violation of the license.
                        \nFor information and bug reports:
                        - Take a look at https://www.bibliometrix.org
                        - Send an email to info@bibliometrix.org   
                        - Write a post on https://github.com/massimoaria/bibliometrix/issues
                        \nHelp us to keep Bibliometrix and Biblioshiny free to download and use by contributing with a small donation to support our research team (https://bibliometrix.org/donate.html)\n
                        \nTo start with the Biblioshiny app, please digit:
biblioshiny()\n")
}


# ### extract data from igraph class object
# ### Credits to François Briatte. Function is a fork of the package ggnetwork
# dataFromIgraph <- function(
#     model,
#     data = NULL,
#     layout = igraph::nicely(),
#     arrow.gap = ifelse(igraph::is.directed(model), 0.025, 0),
#     by = NULL,
#     scale = TRUE,
#     stringsAsFactors = getOption("stringsAsFactors"),
#     ...
# ) {
#   # node placement
#   if (inherits(layout, "matrix") && identical(dim(layout), c(igraph::gorder(model), 2L))) {
#     nodes <- layout[, 1:2 ]
#   } else if (inherits(layout, "matrix")) {
#     stop("layout matrix dimensions do not match network size")
#   } else {
#     nodes <- igraph::layout_(model, layout, ...)
#   }
#   
#   format_igraph(
#     model = model,
#     nodes = nodes,
#     weights = "none",
#     arrow.gap = arrow.gap,
#     by = by,
#     scale = scale,
#     stringsAsFactors = stringsAsFactors,
#     .list_vertex_attributes_fun = igraph::list.vertex.attributes,
#     .get_vertex_attributes_fun = igraph::get.vertex.attribute,
#     .list_edges_attributes_fun = igraph::list.edge.attributes,
#     .get_edges_attributes_fun = igraph::get.edge.attribute,
#     .as_edges_list_fun = igraph::as_edgelist
#   )
# }
# 
# ### Credits to François Briatte. Function is a fork of the package ggnetwork
# format_igraph <- function(
#     model,
#     nodes = NULL,
#     weights = NULL,
#     arrow.gap = ifelse(network::is.directed(model), 0.025, 0),
#     by = NULL,
#     scale = TRUE,
#     stringsAsFactors = getOption("stringsAsFactors"),
#     .list_vertex_attributes_fun = NULL,
#     .get_vertex_attributes_fun = NULL,
#     .list_edges_attributes_fun = NULL,
#     .get_edges_attributes_fun = NULL,
#     .as_edges_list_fun = NULL
# ) {
#   # store coordinates
#   nodes <- data.frame(nodes)
#   colnames(nodes) <- c("x", "y")
#   
#   # rescale coordinates
#   if (scale) {
#     nodes$x <- scale_data(nodes$x)
#     nodes$y <- scale_data(nodes$y)
#   }
#   
#   # import vertex attributes
#   if (length(.list_vertex_attributes_fun(model)) > 0) {
#     nodes <- cbind.data.frame(
#       nodes,
#       sapply(
#         X = .list_vertex_attributes_fun(model),
#         Y = model,
#         FUN = function(X, Y) .get_vertex_attributes_fun(Y, X),
#         simplify = FALSE
#       ),
#       stringsAsFactors = stringsAsFactors
#     )
#   }
#   
#   # edge list
#   if (inherits(model, "igraph")) {
#     edges <- .as_edges_list_fun(model, names = FALSE)
#   } else {
#     edges <- .as_edges_list_fun(model, attrname = weights)
#   }
#   
#   # edge list (if there are duplicated rows)
#   if (nrow(edges[, 1:2, drop = FALSE]) > nrow(unique(edges[, 1:2, drop = FALSE]))) {
#     warning("duplicated edges detected")
#   }
#   
#   edges <- data.frame(nodes[edges[, 1], c("x", "y")], nodes[edges[, 2], c("x", "y")])
#   colnames(edges) <- c("x", "y", "xend", "yend")
#   
#   # arrow gap (thanks to @heike and @ethen8181 for their work on this issue)
#   if (arrow.gap > 0) {
#     x.length <- edges$xend - edges$x
#     y.length <- edges$yend - edges$y
#     arrow.gap <- arrow.gap / sqrt(x.length^2 + y.length^2)
#     edges$xend <- edges$x + (1 - arrow.gap) * x.length
#     edges$yend <- edges$y + (1 - arrow.gap) * y.length
#   }
#   
#   # import edge attributes
#   if (length(.list_edges_attributes_fun(model)) > 0) {
#     edges <- cbind.data.frame(
#       edges,
#       sapply(
#         X = .list_edges_attributes_fun(model),
#         Y = model,
#         FUN = function(X, Y) .get_edges_attributes_fun(Y, X),
#         simplify = FALSE
#       ),
#       stringsAsFactors = stringsAsFactors
#     )
#   }
#   
#   if (nrow(edges) > 0) {
#     # drop "na" columns created by 'network' methods
#     # this is to ensure consistency with 'igraph' methods
#     if ("na" %in% colnames(nodes)) nodes$na <- NULL
#     if ("na" %in% colnames(edges)) edges$na <- NULL
#     
#     # merge edges and nodes data
#     edges <- merge(nodes, edges, by = c("x", "y"), all = TRUE)
#     
#     # add missing columns to nodes data
#     nodes$xend <- nodes$x
#     nodes$yend <- nodes$y
#     # names(nodes) <- names(edges)[1:ncol(nodes)] # columns are already named from 'nodes' and 'edges'
#     
#     # make nodes data of identical dimensions to edges data
#     nodes[, setdiff(names(edges), names(nodes))] <- NA
#     
#     # panelize nodes (for temporal networks)
#     if (!is.null(by)) {
#       nodes <- lapply(sort(unique(edges[, by])), function(x) {
#         y <- nodes
#         y[, by] <- x
#         y
#       })
#       nodes <- do.call(rbind, nodes)
#     }
#     
#     return(unique(rbind(edges[!is.na(edges$xend), ], nodes)))
#   } else {
#     # add missing columns to nodes data
#     nodes$xend <- nodes$x
#     nodes$yend <- nodes$y
#     return(nodes)
#   }
# }
# 
# 
# ### scale coordinates
# ### Credits to François Briatte. Function is a fork of the package ggnetwork
scale_data <- function(x, scale = diff(range(x))) {
  if (!scale) {
    x <- rep(0.5, length.out = length(x))
  } else {
    x <- scale(x, center = min(x), scale = scale)
  }
  as.vector(x)
}


# ## Plot edges using ggplot2
# ### Credits to François Briatte. Function is a fork of the package ggnetwork
geom_network_edges <- function(
    mapping = NULL,
    data = NULL,
    position = "identity",
    arrow = NULL,
    curvature = 0,
    angle = 90,
    ncp = 5,
    na.rm = FALSE,
    show.legend = NA,
    inherit.aes = TRUE,
    ...
) {
  if (!curvature) {
    geom <- ggplot2::GeomSegment
    params <- list(arrow = arrow, na.rm = na.rm, ...)
  } else {
    geom <- ggplot2::GeomCurve
    params <- list(
      arrow = arrow,
      curvature = curvature,
      angle = angle,
      ncp = ncp,
      na.rm = na.rm,
      ...
    )
  }

  ggplot2::layer(
    data = data,
    mapping = mapping,
    stat = StatEdges,
    geom = geom,
    position = position,
    show.legend = show.legend,
    inherit.aes = inherit.aes,
    params = params
  )
}

# ### Credits to François Briatte. Function is a fork of the package ggnetwork
geom_network_nodes <- function(
    mapping = NULL,
    data = NULL,
    position = "identity",
    na.rm = FALSE,
    show.legend = NA,
    inherit.aes = TRUE,
    ...
) {
  ggplot2::layer(
    data = data,
    mapping = mapping,
    stat = StatNodes,
    geom = ggplot2::GeomPoint,
    position = position,
    show.legend = show.legend,
    inherit.aes = inherit.aes,
    params = list(
      na.rm = na.rm,
      ...
    )
  )
}
# 
# ### Credits to François Briatte. Function is a fork of the package ggnetwork
StatEdges <- ggplot2::ggproto("StatEdges", ggplot2::Stat,
                              compute_layer = function(data, scales, params) {
                                unique(subset(data, !(x == xend & y == yend)))
                              }
)

### Credits to François Briatte. Function is a fork of the package ggnetwork
StatNodes <- ggplot2::ggproto("StatNodes", ggplot2::Stat,
                              compute_layer = function(data, scales, params) {
                                if (all(c("xend", "yend") %in% names(data))) {
                                  unique(subset(data, select = c(-xend, -yend)))
                                } else {
                                  unique(data)
                                }
                              }
)

### Credits to Patrick Barks. Function is a fork of the package Abbrev
AbbrevTerm <- function(x, check = TRUE) {
  
  if (check == FALSE) {
    out <- x
  } else {
    # check for invalid x
    if(length(x) > 1) {
      stop('Please provide a single string (length(x) should equal 1)')
    } else if (grepl('[[:space:]]', x)) {
      warning('The provided string contains spaces. This function is only designed to abbreviate a single word.')
    }
    
    # check whether x is title case
    ch1 <- substr(x, 1, 1)
    is_title <- ch1 == toupper(ch1)
    
    # check for whole word match
    # TODO: find way to deal with multiple whole word matches (e.g. w/ and w/o diacritics)
    int_whole_match <- stringi::stri_cmp_equiv(x, ltwa_singles$WORD, strength = 1)
    ind_whole_match <- which(int_whole_match == TRUE)
    
    if (length(ind_whole_match > 0)) {
      # if whole-word match is found, return corresponding abbrev (if no abbrev,
      #  return original x)
      abbrev <- ltwa_singles$ABBREVIATIONS[ind_whole_match]
      word <- ltwa_singles$WORD[ind_whole_match]
      out <- ifelse(is.na(abbrev), word, abbrev)
    } else {
      # else, find matching prefix
      # TODO: give preference to matches with higher strength
      lgl_prefix <- stringi::stri_startswith_coll(x, ltwa_prefix$WORD, strength = 1)
      ind_prefix <- which(lgl_prefix == TRUE)
      
      # choose abbrev based on number of matching prefixes (0, 1, or 2+)
      if (length(ind_prefix) == 0) {
        # if no matching prefixes, return original x
        out <- x
      } else if (length(ind_prefix) == 1) {
        # if one matching prefixes, return corresponding abbrev
        out <- ltwa_prefix$ABBREVIATIONS[ind_prefix]
        if (is.na(out)) out <- x
      } else {
        # if multiple matching prefixes, choose abbrev from longest match
        ind_prefix <- ind_prefix[which.max(nchar(ltwa_prefix$WORD[ind_prefix]))]
        out <- ltwa_prefix$ABBREVIATIONS[ind_prefix]
      }
    }
    
    # if x contains only latin chars, remove any diacritics from abbrev
    if (stringi::stri_trans_general(x, 'Latin-ASCII') == x) {
      out <- stringi::stri_trans_general(out, 'Latin-ASCII')
    }
    
    # if x is title case, convert out to title case
    if (is_title == TRUE) {
      out <- ToTitleCase(out)
    }
  }
  
  # return
  return(out)
}


### Credits to Patrick Barks. Function is a fork of the package Abbrev
AbbrevTitle <- function(x) {
  ind <- rank(-nchar(ltwa_phrase$WORD), ties.method = "last")
  ltwa_phrase[ind,] <- ltwa_phrase

  # check for invalid x
  if(length(x) > 1) {
    stop('Please provide a single string (length(x) should equal 1)')
  }
  
  # remove parentheses and punctuation, and split string into vector of
  #  individual words/terms
  x <- gsub('[[:space:]]\\(.+\\)|\\,|\\.', '', x)
  xv <- unlist(strsplit(x, ' '))
  
  # if title contains only one word, return that word
  if (length(xv) == 1) {
    out <- ToTitleCase(xv)
  } else {
    # otherwise... check for matching multi-word phrases
    
    # vector to track which elements of xv already abbreviated
    xv_which_abb <- logical(length(xv))
    
    # search for multi-word matches (e.g. South Pacific)
    lgl_phrase <- sapply(ltwa_phrase$WORD, function(y) grepl(y, tolower(x)), USE.NAMES = FALSE)
    ind_phrase <- which(lgl_phrase)
    
    # if any matching multi-word phrases
    if (length(ind_phrase) > 0) {
      
      for (i in 1:length(ind_phrase)) {
        match_phrase <- unlist(strsplit(ltwa_phrase$WORD[ind_phrase[i]], '[[:space:]]'))
        match_abb <- ltwa_phrase$ABBREVIATIONS[ind_phrase[i]]
        ind_match <- sapply(match_phrase, function(y) grep(y, tolower(xv)), USE.NAMES = FALSE) # should only find sequential matches
        if (length(ind_match[[1]])>0){
        ind <- ind_match[[1]]:(ind_match[[1]]+length(ind_match)-1)
        xv[ind[1]] <- match_abb
        xv <- c(xv[-ind[-1]])
        xv_which_abb[ind[1]] <- TRUE
        xv_which_abb <- c(xv_which_abb[-ind[-1]])
        }
      }
    }
    
    # if title fully matches multi-word phrase(s), return
    if (all(xv_which_abb == TRUE)) {
      out <- xv
    } else {
      # otherwise... deal with prepositions, articles, and conjunctions
      
      # remove prepositions not at beginning of word
      ind_rem_prep <- c(FALSE, mapply(CheckPrep, USE.NAMES = F, x = xv[-1], check = !xv_which_abb[-1]))
      xv <- xv[!ind_rem_prep]
      xv_which_abb <- xv_which_abb[!ind_rem_prep]
      
      # remove articles and conjunctions
      ind_rem_artcon <- mapply(CheckArtCon, USE.NAMES = F, x = xv, check = !xv_which_abb)
      xv <- xv[!ind_rem_artcon]
      xv_which_abb <- xv_which_abb[!ind_rem_artcon]
      
      # remove d' and l', if followed by character
      xv <- gsub("^d'(?=[[:alpha:]])|^l'(?=[[:alpha:]])", "", xv, ignore.case = TRUE, perl = TRUE)
      
      # if title fully matches multi-word phrase(s) (minus articles/conjunctions), return
      if (all(xv_which_abb == TRUE)) {
        out <- xv
      } else {
        # otherwise... check for hyphenated words
      
        # check for hyphenated words
        ind_dash <- grep('[[:alpha:]]-[[:alpha:]]', xv)
        if (length(ind_dash) > 0) {
          # if hyphens, split hyphenated strings into vectors
          xv <- unlist(strsplit(xv, '-'))
          
          # update xv_which_abb based on hyphens
          for(i in length(ind_dash):1) {
            xv_which_abb <- append(xv_which_abb, FALSE, ind_dash[i])
          }
        }
        
        # abbreviate all words in title (excluding multi-word phrases)
        abbrev_full <- mapply(AbbrevTerm, x = xv, check = !xv_which_abb, USE.NAMES = F)
        
        # add dashes back in, if applicable
        if (length(ind_dash) > 0) {
          for(i in 1:length(ind_dash)) {
            dashed_terms <- abbrev_full[c(ind_dash[i], ind_dash[i] + 1)]
            abbrev_full[ind_dash[i]] <- paste(dashed_terms, collapse = '-')
            abbrev_full <- abbrev_full[-(ind_dash[i] + 1)]
          }
        }
        
        # collapse title to vector
        out <- paste(abbrev_full, collapse = ' ')
      }
    }
  }
  return(out)
}

ToTitleCase <- function(x) {
  paste0(toupper(substr(x, 1, 1)), substr(x, 2, nchar(x)))
}

CheckPrep <- function(x, check) {
  if(check == TRUE) {
    return(ifelse(tolower(x) %in% df_prep$word, TRUE, FALSE))
  } else {
    return(FALSE)
  }
}

CheckArtCon <- function(x, check) {
  if(check == TRUE) {
    return(ifelse(tolower(x) %in% df_artcon$word, TRUE, FALSE))
  } else {
    return(FALSE)
  }
}

# color palette
colorlist <- function(){
  c("#E41A1C","#377EB8","#4DAF4A","#984EA3","#FF7F00","#A65628","#F781BF","#999999","#66C2A5","#FC8D62","#8DA0CB","#E78AC3","#A6D854","#FFD92F"
             ,"#B3B3B3","#A6CEE3","#1F78B4","#B2DF8A","#33A02C","#FB9A99","#E31A1C","#FDBF6F","#FF7F00","#CAB2D6","#6A3D9A","#B15928","#8DD3C7","#BEBADA"
             ,"#FB8072","#80B1D3","#FDB462","#B3DE69","#D9D9D9","#BC80BD","#CCEBC5")
}

#Initial to upper case
firstup <- function(x) {
  x <- tolower(x)
  substr(x, 1, 1) <- toupper(substr(x, 1, 1))
  x
}