2018-2022年教育期刊的引用数可视化

教程
Author

学徒

Published

December 31, 2019

Modified

March 3, 2024

(2019’s Summary) 简单的描述一下，和教育相关的意外只有Review of Educational Research。还有令我意外的是，Journal of Mixed Methods Research也有上榜，看来纯方法的期刊也可以拥有超高应用数。原因之一大概是mixed method在社会科学的统治地位。总的来说，霸榜最久的是MMWR (Morbidity and mortality weekly report)以及National vital statistics reports。另外，用R做gif果然帧数不够，真要像油管那样的话得转成mp4格式才行。

Code

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library(animation)
library(gganimate)
library(ggplot2)
library(tidyverse)
library(knitr)
library(here)
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tidize <- function(data) {
  dat.tidy <- dat %>% 
    select(Title, Ref....Doc.) %>% # average amount of references per document
    rename(Citation = Ref....Doc.) %>% 
    mutate(
      Citation = as.numeric(gsub(",", "", .$Citation)),
      rank = rank(-Citation)) %>% 
    arrange(desc(Citation)) %>% 
    .[1:10,]
  return(dat.tidy)
}
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root_dir <- "postsCN/2019-12-31-animation"
filenames <- list.files(here(root_dir), pattern = '.csv')
years <- as.numeric(unlist(regmatches(filenames, gregexpr("[[:digit:]]+", filenames))))


dat.list <- list()
length(dat.list) <- length(filenames)

# dat <- read.csv(here(root_dir, filenames[1]),  header = TRUE, sep = ";", check.names = T, stringsAsFactors = FALSE)
# colnames(dat)

for (n in seq_along(filenames)) {
  dat <- read.csv(here(root_dir, filenames[n]), header = TRUE, sep = ";", check.names = T, stringsAsFactors = FALSE)
  dat = tidize(dat)
  dat$Year = years[n]
  dat.list[[n]] <- dat
}
dat.comb <- do.call("rbind", dat.list)
dat.comb$Year <- factor(dat.comb$Year, levels = years)
dat.comb$Title <- factor(dat.comb$Title)
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staticplot <- 
  ggplot(dat.comb, 
         aes(x = rank, group = Year, fill = as.factor(Title), color = as.factor(Title))) +
  geom_tile(aes(y = Citation/2,
                height = Citation,
                width = 0.8), alpha = 0.1) +
  geom_text(aes(y = 3000, label = paste(" ",Title)), hjust = 0, color = "black") +
  geom_text(aes(y= Citation + 20,label = Citation, hjust= 0)) + # the number
  guides(color = FALSE, fill = FALSE) +
  coord_flip(clip = "off", expand = FALSE) +
  scale_y_continuous(labels = scales::comma, limits = c(0, 25000)) +
  scale_x_reverse(breaks = 1:20) +
  labs(y = "Citation") +
  theme(
    axis.title.x=element_blank(),
    axis.ticks.x=element_blank(),
    axis.text.x=element_blank(),
    axis.title.y=element_blank(),
    axis.text.y= element_blank(),
    axis.ticks.y=element_blank()) +
  theme_classic() 
staticplot + facet_wrap(~ Year, ncol = 1)

⌘+C 
(anim =  
    staticplot + 
    transition_states(Year, transition_length = 20, state_length = 1) +
    view_follow(fixed_y = TRUE, fixed_x = T) +
    labs(
      #title = 'Year: {closest_state}',  
      caption = "Author: Jihong Zhang",
      render = gifski_renderer()
    ))

Original R Code

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#setwd("~/Desktop/impact_factor/")
filenames <- list.files("~/Desktop/impact_factor/")
years <- as.numeric(unlist(regmatches(filenames, gregexpr("[[:digit:]]+", filenames))))

dat.list <- list()
length(dat.list) <- length(filenames)

for (n in seq_along(filenames)) {
  dat <- read.csv(paste0("~/Desktop/impact_factor/", filenames[n]), header = TRUE, sep = ";", check.names = T, stringsAsFactors = FALSE)
  dat = tidize(dat)
  dat$year = years[n]
  dat.list[[n]] <- dat
}
dat.comb <- do.call("rbind", dat.list)

dat.comb[dat.comb$Title == "MMWR. Recommendations and reports : Morbidity and mortality weekly report. Recommendations and reports / Centers for Disease Control", "Title"] = "MMWR:Recommendations and reports"
dat.comb[dat.comb$Title == "National vital statistics reports : from the Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System", "Title"] = "National vital statistics reports"
dat.comb[dat.comb$Title == "MMWR. Surveillance summaries : Morbidity and mortality weekly report. Surveillance summaries / CDC", "Title"] = "MMWR:Surveillance summaries"
dat.comb[dat.comb$Title == "Energy Education Science and Technology Part B: Social and Educational Studies", "Title"] = "Energy Education Science and Technology"

staticplot <- ggplot(dat.comb, aes(x = (rank), group = Title, 
       fill = as.factor(Title), color = as.factor(Title))) +
  geom_tile(aes(y = Citation/2,
                height = Citation,
                width = 1), alpha = 0.8) +
  geom_text(aes(y = 3000, label = paste(" ",Title)), hjust = 0, color = "black") +
  geom_text(aes(y= Citation + 20,label = Citation, hjust= 0)) + # the number
  guides(color = FALSE, fill = FALSE) +
  coord_flip(clip = "off", expand = FALSE) +
  scale_y_continuous(labels = scales::comma) +
  scale_x_reverse() +
  theme(
    axis.title.x=element_blank(),
    axis.ticks.x=element_blank(),
    axis.text.x=element_blank(),
    axis.title.y=element_blank(),
    axis.text.y= element_blank(),
    axis.ticks.y=element_blank()) 

(anim = staticplot + 
  transition_states(year, transition_length = 10, state_length = 1) +
  view_follow(fixed_y = TRUE) +
  labs(title = 'Citations of The year: {closest_state}',  
       subtitle  =  "Top 10 Journals in Social Sciences",
       caption = "Author: Jihong Zhang"))
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animate(anim, renderer = gifski_renderer("/Users/jzhang285/Documents/Projects/hugo-academic-jihong/static/img/citation_journals.gif"))

sources: https://www.scimagojr.com/journalrank.php?category=3304&min=0&min_type=cd

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