Retrieving basic information
## Define the id for Richard Feynman
id <- 'B7vSqZsAAAAJ'
## Get his profile
l <- get_profile(id)
## Print his name and affliation
l$name## [1] "Richard Feynman"l$affiliation## [1] "California Institute of Technology"## Print his citation index
l$h_index## [1] 60l$i10_index## [1] 92Retrieving publications
get_publications() return a data.frame of publication records. It contains information of the publications, including title, author list, page number, citation number, publication year, etc..
The pubid is the article ID used by Google Scholar and the identifier that is used to retrieve the citation history of a selected publication.
## Get his publications (a large data frame)
p <- get_publications(id)
head(p, 3)## title
## 1 Quantum mechanics and path integration
## 2 The Feynman lectures on physics
## 3 Simulating physics with computers
## author
## 1 RP Feynman, AR Hibbs
## 2 RP Feynman, RB Leighton, M Sands, SB Treiman
## 3 RP Feynman
## journal number cites year
## 1 McGraw–Hill 27757 1965
## 2 Physics Today 17, 45 16125 1964
## 3 International journal of theoretical physics 21 (6), 467-488 6407 1982
## cid
## 1 14769952204323476283,12549707430555464374,16081691140030299281
## 2 14769952204323476283,15649786516955137750,9010733094641920532,948993425682989482,13112633961799421939,3669163321259408309
## 3 10235205812612705711
## pubid
## 1 hMod-77fHWUC
## 2 u-x6o8ySG0sC
## 3 d1gkVwhDpl0CRetrieving citation data
## Get his citation history, i.e. citations to his work in a given year
ct <- get_citation_history(id)
## Plot citation trend
library(ggplot2)
ggplot(ct, aes(year, cites)) + geom_line() + geom_point()
Users can retrieve the citation history of a particular publication with get_article_cite_history().
## The following publication will be used to demonstrate article citation history
as.character(p$title[1])## [1] "Quantum mechanics and path integration"## Get article citation history
ach <- get_article_cite_history(id, p$pubid[1])
## Plot citation trend
ggplot(ach, aes(year, cites)) +
geom_segment(aes(xend = year, yend = 0), size=1, color='darkgrey') +
geom_point(size=3, color='firebrick')
Comparing scholars
You can compare the citation history of scholars by fetching data with compare_scholars.
# Compare Feynman and Stephen Hawking
ids <- c('B7vSqZsAAAAJ', 'qj74uXkAAAAJ')
# Get a data frame comparing the number of citations to their work in
# a given year
cs <- compare_scholars(ids)
## remove some 'bad' records without sufficient information
cs <- subset(cs, !is.na(year) & year > 1900)
ggplot(cs, aes(year, cites, group=name, color=name)) + geom_line() + theme(legend.position="bottom")
## Compare their career trajectories, based on year of first citation
csc <- compare_scholar_careers(ids)
ggplot(csc, aes(career_year, cites, group=name, color=name)) + geom_line() + geom_point() +
theme(legend.position=c(.2, .8))
Visualizing and comparing network of coauthors
# Be careful with specifying too many coauthors as the visualization of the
# network can get very messy.
coauthor_network <- get_coauthors('amYIKXQAAAAJ&hl', n_coauthors = 7)
coauthor_network## author coauthors
## 1 Herman G. Van De Werfhorst Thijs Bol
## 2 Herman G. Van De Werfhorst Daniele Checchi
## 3 Herman G. Van De Werfhorst Frank Van Tubergen
## 4 Herman G. Van De Werfhorst Wiemer Salverda
## 5 Herman G. Van De Werfhorst Gerbert Kraaykamp
## 6 Herman G. Van De Werfhorst Ive Marx
## 7 Herman G. Van De Werfhorst Jonathan Jan Benjamin Mijs
## 8 Thijs Bol Herman G. Van De Werfhorst
## 9 Thijs Bol Jaap Dronkers
## 10 Thijs Bol Kim A. Weeden
## 11 Thijs Bol Andrea G. Forster
## 12 Thijs Bol Bram Lancee
## 13 Thijs Bol Valentina Di Stasio
## 14 Thijs Bol Matthijs Kalmijn
## 15 Daniele Checchi Massimiliano Bratti
## 16 Daniele Checchi Giorgio Brunello
## 17 Daniele Checchi Vito Peragine
## 18 Daniele Checchi Marco Leonardi
## 19 Daniele Checchi Giuseppe Bertola
## 20 Daniele Checchi Carlo V. Fiorio
## 21 Daniele Checchi Herman G. Van De Werfhorst
## 22 Frank Van Tubergen Ineke Maas
## 23 Frank Van Tubergen Matthijs Kalmijn
## 24 Frank Van Tubergen Agnieszka Kanas
## 25 Frank Van Tubergen Herman G. Van De Werfhorst
## 26 Frank Van Tubergen Marcel Coenders
## 27 Frank Van Tubergen Borja Martinovic
## 28 Frank Van Tubergen Tanja Van Der Lippe
## 29 Wiemer Salverda Ive Marx
## 30 Wiemer Salverda Stephen Bazen
## 31 Wiemer Salverda Herman G. Van De Werfhorst
## 32 Wiemer Salverda Daniele Checchi
## 33 Wiemer Salverda Peter Mühlau
## 34 Wiemer Salverda Anthony Atkinson
## 35 Wiemer Salverda Bram Lancee
## 36 Gerbert Kraaykamp Nan Dirk De Graaf
## 37 Gerbert Kraaykamp Paul M. De Graaf
## 38 Gerbert Kraaykamp Matthijs Kalmijn
## 39 Gerbert Kraaykamp Natascha Notten
## 40 Gerbert Kraaykamp Tim Huijts
## 41 Gerbert Kraaykamp Christiaan Monden
## 42 Gerbert Kraaykamp Maurice Gesthuizen
## 43 Ive Marx Bea Cantillon
## 44 Ive Marx Sarah Marchal
## 45 Ive Marx Wiemer Salverda
## 46 Ive Marx Herman G. Van De Werfhorst
## 47 Ive Marx Daniele Checchi
## 48 Ive Marx Johan Fritzell
## 49 Ive Marx Gert G. Wagner
## 50 Jonathan Jan Benjamin Mijs Herman G. Van De Werfhorst
## 51 Jonathan Jan Benjamin Mijs Maurice Crul
## 52 Jonathan Jan Benjamin Mijs Philipp Schnell
## 53 Jonathan Jan Benjamin Mijs Bowen Paulle
## 54 Jonathan Jan Benjamin Mijs Michele Lamont
## 55 Jonathan Jan Benjamin Mijs Elyas Bakhtiari
## 56 Jonathan Jan Benjamin Mijs James S. ColemanAnd then we have a built-in function to plot this visualization.
plot_coauthors(coauthor_network)
Note however, that these are the coauthors listed in Google Scholar profile and not coauthors from all publications.