Retrieving basic information
## $id## [1] "B7vSqZsAAAAJ"## ## $name## [1] "Richard Feynman"## ## $affiliation## [1] "California Institute of Technology"## ## $total_cites## [1] 131676## ## $h_index## [1] 62## ## $i10_index## [1] 103## ## $fields## [1] "quantum mechanics" "quantum electrodynamics"## ## $homepage## character(0)## ## $coauthors## [1] "Sort by citations" "Sort by year" "Sort by title" ## [4] "About Scholar" "Search help" ## ## $available## [1] NA## ## $not_available## [1] NARetrieving publications
get_publications() return adata.frame ofpublication records. It contains information of the publications,includingtitle,author list,page number,citation number,publication year,etc..
Thepubid is the article ID used by Google Scholar andthe identifier that is used to retrieve the citation history of aselected publication.
## title## 1 Quantum mechanics and path integration## 2 The Feynman lectures on physics## 3 Simulating physics with computers## author## 1 RP Feynman, AR Hibbs## 2 RP Feynman, RB Leighton, M Sands, SB Treiman## 3 RP Feynman## journal number cites year## 1 McGraw–Hill 37629 1965## 2 Physics Today 17, 45 23750 1964## 3 International journal of theoretical physics 21 (6), 467-488 14205 1982## cid## 1 8172747039614742666,12091496877795411869,3494294362048429920,18041911941623786099## 2 8172747039614742666,15649786516955137750,13112633961799421939,3669163321259408309## 3 15599256484525608168## pubid## 1 hMod-77fHWUC## 2 u-x6o8ySG0sC## 3 d1gkVwhDpl0CRetrieving citation data
## Get his citation history, i.e. citations to his work in a given yearct<-get_citation_history(id)## Plot citation trendlibrary(ggplot2)ggplot(ct,aes(year, cites))+geom_line()+geom_point()Users can retrieve the citation history of a particular publicationwithget_article_cite_history().
## The following publication will be used to demonstrate article citation historyas.character(p$title[1])## [1] "Quantum mechanics and path integration"## Get article citation historyach<-get_article_cite_history(id, p$pubid[1])## Plot citation trendggplot(ach,aes(year, cites))+geom_segment(aes(xend = year,yend =0),linewidth=1,color='darkgrey')+geom_point(size=3,color='firebrick')Comparing scholars
You can compare the citation history of scholars by fetching datawithcompare_scholars.
# Compare Feynman and Stephen Hawkingids<-c('B7vSqZsAAAAJ','qj74uXkAAAAJ')# Get a data frame comparing the number of citations to their work in# a given yearcs<-compare_scholars(ids)## remove some 'bad' records without sufficient informationcs<- dplyr::filter(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 citationcsc<-compare_scholar_careers(ids)ggplot(csc,aes(career_year, cites,group=name,color=name))+geom_line()+geom_point()+theme(legend.position ="inside",legend.position.inside=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('DO5oG40AAAAJ',n_coauthors =4)coauthor_network## author coauthors## qgFBNJgAAAAJ&hl Guangchuang Yu Shuangbin Xu## kRtxIw0AAAAJ&hl Guangchuang Yu Tommy Tsan-Yuk Lam## WmjCTgMAAAAJ&hl Guangchuang Yu Zhu Huachen## 1M8ux5YAAAAJ&hl Guangchuang Yu Qianwen Wang## DO5oG40AAAAJ&hl Shuangbin Xu Guangchuang Yu## 1M8ux5YAAAAJ&hl1 Shuangbin Xu Qianwen Wang## HxxRzrYAAAAJ&hl Shuangbin Xu Zhangran Chen## 4 Tommy Tsan-Yuk Lam About Scholar## kRtxIw0AAAAJ&hl1 Zhu Huachen Tommy Tsan-Yuk Lam## 1mTtPIIAAAAJ&hl Zhu Huachen Steven Riley## DO5oG40AAAAJ&hl1 Zhu Huachen Guangchuang Yu## bib_lf0AAAAJ&hl Zhu Huachen Gavin Jd Smith## DO5oG40AAAAJ&hl2 Qianwen Wang Guangchuang Yu## qgFBNJgAAAAJ&hl1 Qianwen Wang Shuangbin Xu## b-duIhMAAAAJ&hl Qianwen Wang Hon-Ming Lam## GzJd-VoAAAAJ&hl Qianwen Wang Wai-Shing YungAnd then we have a built-in function to plot this visualization.
## Warning: Removed 6 rows containing missing values or values outside the scale range## (`geom_point()`).Note however, that these are the coauthors listed in Google Scholarprofile and not coauthors from all publications.
Formatting publications for CV
Theformat_publications function can be used for examplein conjunction with thevitaepackage to format publications in APA Style. The short name of theauthor of interest (e.g., of the person whose CV is being made) can behighlighted in bold with theauthor.name argument. Thefunction after the pipe allows rmarkdown to format them properly, andthe code chunk should be set toresults = "asis".
APA style
Xu, S., Wang, Q., Wen, S., Li, J., He, N., Li, M., Hackl, T., Wang,R., Zeng, D., Wang, S., & … (2025). aplot: Simplifying the creationof complex graphs to visualize associations across diverse data types.The Innovation.
Wang, Q., Zhu, H., Deng, L., Xu, S., Xie, W., Li, M., Wang, R., Tie,L., Zhan, L., & Yu, G. (2025). Spatial Transcriptomics:Biotechnologies, Computational Tools, and Neuroscience Applications.Small Methods. 9 (5), 2401107
Gao, Y., Li, B., Jin, Y., Cheng, J., Tian, W., Ying, L., Hong, L.,Xin, S., Lin, B., Liu, C., & … (2025). Spatial multi-omics profilingof breast cancer oligo-recurrent lung metastasis.Oncogene.1-15
Chen, M., Luo, X., Xu, S., Li, L., Li, J., Xie, Z., Wang, Q., Liao,Y., Liu, B., Liang, W., & … (2025). Scalable method for exploringphylogenetic placement uncertainty with custom visualizations usingtreeio and ggtree.iMeta, e. e269
Tu, Y., Xu, S., Shu, H., Wang, X., Li, W., Yu, G., & He, L.(2025). 16S rRNA Sequencing Reveals Dysbiosis of Skin MicrobiomeAssociated With Disease Severity in Chronic Actinic Dermatitis.Photodermatology, photoimmunology & photomedicine. 41 (3),e70022
Yu, G., Xu, S., Wang, Q., Li, J., Li, J., Wang, R., Zhang, L., Xie,W., Wen, S., Li, M., & … (2025). Precise Characterization ofCellular States and Spatial Variable Patterns within SpatialTranscriptomics. **.
Numbering format
[1] Xu, S., Wang, Q., Wen, S., Li, J., He, N., Li, M., Hackl, T.,Wang, R., Zeng, D., Wang, S., & … (2025). aplot: Simplifying thecreation of complex graphs to visualize associations across diverse datatypes.The Innovation.
[2] Wang, Q., Zhu, H., Deng, L., Xu, S., Xie, W., Li, M., Wang, R., Tie,L., Zhan, L., & Yu, G. (2025). Spatial Transcriptomics:Biotechnologies, Computational Tools, and Neuroscience Applications.Small Methods. 9 (5), 2401107
[3] Gao, Y., Li, B., Jin, Y., Cheng, J., Tian, W., Ying, L., Hong, L.,Xin, S., Lin, B., Liu, C., & … (2025). Spatial multi-omics profilingof breast cancer oligo-recurrent lung metastasis.Oncogene.1-15
[4] Chen, M., Luo, X., Xu, S., Li, L., Li, J., Xie, Z., Wang, Q., Liao,Y., Liu, B., Liang, W., & … (2025). Scalable method for exploringphylogenetic placement uncertainty with custom visualizations usingtreeio and ggtree.iMeta, e. e269
[5] Tu, Y., Xu, S., Shu, H., Wang, X., Li, W., Yu, G., & He, L.(2025). 16S rRNA Sequencing Reveals Dysbiosis of Skin MicrobiomeAssociated With Disease Severity in Chronic Actinic Dermatitis.Photodermatology, photoimmunology & photomedicine. 41 (3),e70022 [6] Yu, G., Xu, S., Wang, Q., Li, J., Li, J., Wang, R., Zhang,L., Xie, W., Wen, S., Li, M., & … (2025). Precise Characterizationof Cellular States and Spatial Variable Patterns within SpatialTranscriptomics. **.