#' Top-Authors' Productivity over Time
#'
#' It calculates and plots the author production (in terms of number of publications) over the time.
#' @param M is a bibliographic data frame obtained by \code{\link{convert2df}} function.
#' @param k is a integer. It is the number of top authors to analyze and plot. Default is \code{k = 10}.
#' @param graph is logical. If TRUE the function plots the author production over time graph. Default is \code{graph = TRUE}.
#' @return The function \code{authorProdOverTime} returns a list containing two objects:
#' \tabular{lll}{
#' \code{dfAU} \tab \tab is a data frame\cr
#' \code{dfpapersAU}\tab \tab is a data frame\cr
#' \code{graph} \tab \tab a ggplot object}
#'
#' @examples
#' data(scientometrics, package = "bibliometrixData")
#' res <- authorProdOverTime(scientometrics, k=10)
#' print(res$dfAU)
#' plot(res$graph)
#'
#' @seealso \code{\link{biblioAnalysis}} function for bibliometric analysis
#' @seealso \code{\link{summary}} method for class '\code{bibliometrix}'
#'
#' @export
#'
authorProdOverTime <- function(M,k=10, graph=TRUE){
M$TC <- as.numeric(M$TC)
M$PY <- as.numeric(M$PY)
M <- M[!is.na(M$PY),] #remove rows with missing value in PY
AU <- names(tableTag(M,"AU"))
k <- min(k,length(AU))
AU <- AU[1:k]
#AU=names(AU)
df <- data.frame("Author"="NA","year"=NA, "TI"="NA","SO"="NA","DOI"="NA", "TC"=NA,"TCpY"=NA,stringsAsFactors = FALSE)
Y <- as.numeric(substr(Sys.time(),1,4))
if (!("DI" %in% names(M))){M$DI="NA"}
for (i in 1:length(AU)){
ind <- which(regexpr(AU[i],M$AU)>-1)
TCpY <- M$TC[ind]/(Y-M$PY[ind]+1)
dfAU <- data.frame("Author"=rep(AU[i],length(ind)),"year"=M$PY[ind],"TI"=M$TI[ind],"SO"=M$SO[ind],"DOI"=M$DI[ind],"TC"=M$TC[ind], "TCpY"=TCpY,stringsAsFactors = TRUE)
df <- rbind(df,dfAU)
}
df <- df[-1,]
df2 <- dplyr::group_by(df, .data$Author,.data$year) %>%
dplyr::summarise(freq=length(.data$year),TC=sum(.data$TC),TCpY=sum(.data$TCpY))
df2 <- as.data.frame(df2)
df2$Author <- factor(df2$Author,levels=AU[1:k])
#theme_set(theme_bw())
x <- c(0.5,1.5*k/10)
y <- c(min(df$year),min(df$year)+diff(range(df2$year))*0.125)
#data("logo",envir=environment())
#logo <- grid::rasterGrob(logo,interpolate = TRUE)
g <- ggplot(df2, aes(x=.data$Author, y=.data$year, text = paste("Author: ", .data$Author,"\nYear: ",.data$year ,"\nN. of Articles: ",.data$freq ,"\nTotal Citations per Year: ", round(.data$TCpY,2))))+
geom_point(aes(alpha=.data$TCpY,size = .data$freq), color="dodgerblue4")+
scale_size(range=c(2,6))+
scale_alpha(range=c(0.3,1))+
scale_y_continuous(breaks = seq(min(df2$year),max(df2$year), by=2))+
guides(size = guide_legend(order = 1, "N.Articles"), alpha = guide_legend(order = 2, "TC per Year"))+
theme(legend.position = 'right'
#,aspect.ratio = 1
,text = element_text(color = "#444444")
,panel.background = element_rect(fill = 'gray97')
,panel.grid.minor = element_line(color = '#FFFFFF')
,panel.grid.major = element_line(color = '#FFFFFF')
,plot.title = element_text(size = 24)
,axis.title = element_text(size = 14, color = '#555555')
,axis.title.y = element_text(vjust = 1, angle = 90, face="bold")
,axis.title.x = element_text(hjust = .95,face="bold")
,axis.text.x = element_text(face="bold", angle = 90)
,axis.text.y = element_text(face="bold")
)+
#coord_fixed(ratio = 2/1) +
labs(title="Top-Authors' Production over Time",
x="Author",
y="Year")+
geom_line(data=df2,aes(x = .data$Author, y = .data$year, group=.data$Author),size=1.0, color="firebrick", alpha=0.3 )+
scale_x_discrete(limits = rev(levels(df2$Author)))+
coord_flip() #+
#annotation_custom(logo, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2])
df$DOI=as.character(df$DOI)
res <- list(dfAU=df2,dfPapersAU=df,graph=g)
if (isTRUE(graph)){plot(g)}
return(res)
}
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