This is the good thing about open database. Although Google Scholar (GS) is not a completely open database, but people at Google let us to do the following things using R and Scholar. The following post was my first trial to the scholar package to harvest GS data.

Jump Hasbi, jump… (Credit: flickr/d_erwin_irawan, CC-BY)

Installing packages

In this trial, I used the following packages:

1. scholar
2. tidyverse

# Ommit the '#' sign if you haven't installed the packages
#install.packages("scholar")
library(scholar)
#install.packages("tidyverse")
library(tidyverse)
#install.packages("gridExtra")

Getting your GS ID

Your GS ID will be written in the url of your profile, for instance:

1. Erwin: url https://scholar.google.co.id/citations?user=Myvc78MAAAAJ&hl=en&authuser=1; GS ID “Myvc78MAAAAJ&hl””
2. Prof. Edy Soewono: url https://scholar.google.co.id/citations?user=6U_YtvMAAAAJ&hl=en&authuser=1; GS ID “6U_YtvMAAAAJ&hl”
3. Prof. Khairurrijal: url https://scholar.google.co.id/citations?user=4_asJ0MAAAAJ&hl=en&authuser=1; GS ID “4_asJ0MAAAAJ&hl”
4. Dr. Jon Tennant: url https://scholar.google.co.id/citations?user=P7FvGMEAAAAJ&hl=en; GS ID “P7FvGMEAAAAJ&hl”

Storing GS ID

Here we saved the GS ID of each author.

E <- "Myvc78MAAAAJ&hl"  #hydrogeology
ES <- "6U_YtvMAAAAJ&hl" #math
Kh <- "4_asJ0MAAAAJ&hl" #physics
JT <- "P7FvGMEAAAAJ&hl" #paleontology

Getting GS profiles information

We can show the profile information using the following function.

E.profile <- get_profile(E)
ES.profile <- get_profile(ES)
Kh.profile <- get_profile(Kh)
JT.profile <- get_profile(JT)

E.profile
ES.profile
Kh.profile
JT.profile

How many papers have they published?

Function get_num_articles() gathers total number of articles.

E.num <- get_num_articles(E)
ES.num <- get_num_articles(ES)
Kh.num <- get_num_articles(Kh)
JT.num <- get_num_articles(JT)

num <- c(E.num, ES.num, Kh.num, JT.num)
barplot(num, names.arg=c("E", "ES", "Kh", "JT")) 

Comparing career

This is an interesting function in scholar. This function calculates the number of years since the first publication (assuming this as the starting year of the career).

IDs <- c(ES, Kh, JT)
compare_scholar_careers(IDs, career = TRUE)

Getting citation history

This is a bit strange, E.cite.year failed to run.

ES.cite.year <- get_citation_history(ES)  # success
Kh.cite.year <- get_citation_history(Kh)  # success
JT.cite.year <- get_citation_history(JT)  # success
# E.cite.year <- get_citation_history(E)   # hmm, error, strange

Plotting citation history

This functions use ggplot2, but you can always use base function to plot.

ES.hist <- ggplot(ES.cite.year, aes(year,cites)) + 
  geom_bar(stat='identity',fill=colors()[128]) +
  scale_x_continuous(
    breaks = c(2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017))

Kh.hist <- ggplot(Kh.cite.year, 
       aes(year,cites)) + 
  geom_bar(stat='identity',fill=colors()[120]) +
  scale_x_continuous(
    breaks = c(2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017))

JT.hist <- ggplot(JT.cite.year, 
                aes(year,cites)) + 
  geom_bar(stat='identity',fill=colors()[118]) +
  scale_x_continuous(
    breaks = c(2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017))

ES.hist
Kh.hist
JT.hist

## My work around
E.cite.year <- get_publications(E)
E.cite.year <- as.data.frame(lapply(E.cite.year,
                                 function(x) if (is.factor(x)) as.character(x) else x))
w <-grep("Ultrafast", E.cite.year$title) 
E.cite.year$title[w]
E.cite.year$pubid[w] 
E.cite.year <- get_article_cite_history(E, E.cite.year$pubid[w])

E.hist <- ggplot(E.cite.year, aes(year, cites)) +
  geom_bar(stat='identity',fill=colors()[110]) +
  scale_x_continuous(
    breaks = c(2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017))+
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

Getting number of unique journals

get_num_distinct_journals(E)
get_num_distinct_journals(ES)
get_num_distinct_journals(Kh)
get_num_distinct_journals(JT)

Getting number of top journals

get_num_top_journals(E)
get_num_top_journals(ES)
get_num_top_journals(Kh)
get_num_top_journals(JT)

When did they become scientists?

get_oldest_article(E)
get_oldest_article(ES)
get_oldest_article(Kh)
get_oldest_article(JT)

Getting publications and write to a csv file

E.pubs <- get_publications(E)
write.csv(pubs, file = "citations.csv")

Predict their h-index

E.x <- predict_h_index(E)
ES.x <- predict_h_index(ES)
Kh.x <- predict_h_index(Kh)
JT.x <- predict_h_index(JT)