Code to calculate JDI from google scholar profile

jdiFromScholar.R

# About: Code to calculate JDI and produce barplot as per
# https://scientistseessquirrel.wordpress.com/2017/08/03/my-journal-life-list/
# Additional code from
# https://www.r-bloggers.com/yet-another-post-on-google-scholar-data-analysis/
# Author: Andrew Jackson 
# http://www.tcd.ie/Zoology/research/research/theoretical/andrewjackson.php
# Date: 04-Aug-2017



library(scholar)
library(tidyverse)

# = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =
# Import data from google scholar and clean it per one's own
# requirements

# Your scholar id. This is for me, Andrew Jackson
# Andrew Jackson
my_id = "E0sB7fUAAAAJ"

# get all publications and convert automatically created factors 
# back to characters and remove the blank journals which are MixSIAR and 
# a report i wrote. I filter out blank journals containing "", and 
# pre-prints on arXiv and R packages logged as being on CRAN as indicated by
# what i hope is a unique string "Comprehensive", and remove "Preprints".

my_publications <- get_publications(my_id, cstart = 0) %>% 
  mutate_if(is.factor, as.character) %>%
  filter(journal != "") %>%
  filter(!grepl("arXiv", journal)) %>%
  filter(!grepl("Comprehensive", journal)) %>% 
  filter(!grepl("Preprints", journal))



# create a column of lower case only journal names for matching
my_publications$journal.lwr <- tolower(my_publications$journal)


# = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =


# count by journal name and create journal names as a factor ordered by their
# count
journal_counts <- my_publications %>% 
  dplyr::count(journal.lwr, sort = TRUE) %>% 
  mutate(journal.lwr = ordered(journal.lwr, 
                               levels = journal.lwr[sort(n, 
                                                      decreasing = FALSE, 
                                                      index.return = TRUE)$ix])) 



# = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =
# Calculate the JDI

# P is the total number of publications
P <- nrow(my_publications)

# J is the unique number of journals
J <- nrow(journal_counts)

# JDI is the ratio
JDI <- J / P
print(JDI)

# = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =
# Calcuate Journal Entropy Index JEI suggested by runner24 in comments on 
# https://scientistseessquirrel.wordpress.com/2017/08/03/my-journal-life-list/

p_i <- journal_counts$n / sum(journal_counts$n)

JEI <- -sum(p_i * log2(p_i)) 

# and scaled to be 0 <= JEI <= 1
JEIs <- -JEI / log2(1/sum(journal_counts$n))


print(round(c(P = P, J = J, JDI = JDI, JEI = JEI, JEIs = JEIs),2))

# = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =
# plot the count table using geom_col() and flip it to make 
# it horizontal

my_profile <- get_profile(my_id)

p1 <- ggplot(data = journal_counts, mapping = aes(x = journal.lwr, y = n)) + 
  geom_col() +
  xlab("") + 
  ylab("Number of papers") +
  ggtitle(paste0(my_profile$name, "'s JDI = ", round(JDI,2))) + 
  coord_flip()
print(p1)