**Simply Statistics**, and kindly contributed to R-bloggers)

There has been some discussion about whether Google Scholar or one of the proprietary software companies numbers are better for citation counts. I personally think Google Scholar is better for a number of reasons:

- Higher numbers, but consistently/adjustably higher 🙂
- It’s free and the data are openly available.
- It covers more ground (patents, theses, etc.) to give a better idea of global impact
- It’s easier to use

I haven’t seen a plot yet relating Web of Science citations to Google Scholar citations, so I made one for my papers.

GS has about 41% more citations per paper than Web of Science. That is consistent with what other people have found. It also looks reasonably linearish. I wonder what other people’s plots would look like?

Here is the R code I used to generate the plot (the names are Pubmed IDs for the papers):

library(ggplot2)

names = c(16141318,16357033,16928955,17597765,17907809,19033188,19276151,19924215,20560929,20701754,20838408, 21186247,21685414,21747377,21931541,22031444,22087737,22096506,22257669)

y = c(287,122,84,39,120,53,4,52,6,33,57,0,0,4,1,5,0,2,0)

x = c(200,92,48,31,79,29,4,51,2,18,44,0,0,1,0,2,0,1,0)

Year = c(2005,2006,2007,2007,2007,2008,2009,2009,2011,2010,2010,2011,2012,2011,2011,2011,2011,2011,2012)

q <- qplot(x,y,xlim=c(-20,300),ylim=c(-20,300),xlab=”Web of Knowledge”,ylab=”Google Scholar”) + geom_point(aes(colour=Year),size=5) + geom_line(aes(x = y, y = y),size=2)

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