Online Trick

I have updated the Google Scholar Web-Scraper Function GScholarScaper_2 to GScholarScraper_3 (and GScholarScaper_3.1) as it was outdated due to changes in the Google Scholar html-code. The new script is more slender and faster. It returns a dataframe or optionally a CSV-file with the titles, authors, publications & links. Feel free to report bugs, etc.



Update 11-07-2013: bug fixes due to google scholar code changes - https://github.com/gimoya/onlinetrickpdf-Archives/blob/master/R/Functions/GScholarScraper_3.2.R. Note that since lately your IP will be blocked by Google at about the 1000th search result (cumulated) - so there's not much fun when you want to do some extensive bibliometrics..

NOTE: You'll find the update HERE and HERE.

NOTE: The script is currently not working because the code of the Google-Scholar site has changed...
I'll see for this as soon as I find some spare time for it!

NOTE: If you try to access GoogleScholar programatically consider this words of caution:
http://stackoverflow.com/questions/7523961/google-scholar-with-matlab/7587994#7587994
...

Based on my previous post on Web Scraping I coded and uploaded the Function "GScholarScraper" HERE for testing!
The function will pull all (!) results, processing pages in chunks of 100 results/titles, and return a file with all titles, links, etc. It will also produce a word cloud using the words in the publication titles.

Please try your own search strings and report errors, etc.!

Build and run properly under:
R version 2.13.0 (2011-04-13) and R version R-2.13.2 (2011-09-30)

Platform: i386-pc-mingw32/i386 (32-bit) locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] stringr_0.5 tm_0.5-6 wordcloud_1.2 Rcpp_0.9.7

loaded via a namespace (and not attached):
[1] plyr_1.5.1 slam_0.1-23

PS: Errors reported lately (see comments) were resolved, the source code was updated..

NOTE: Please see the update HERE and HERE!

...When reading Scott Chemberlain's last post about web-scraping I felt it was time to pick up and complete an idea that I was brooding over for some time now:

When a scientist aims out for a new project the first thing to do is to evaluate if other people already have come along to answer the very questions he is about to work on. I.e., I was interested if there has been done any research regarding amphibian diversity at regional/geographical scales correlated to environmental/landscape parameters. Usually I would got to Google-Scholar and search something like - intitle:amphibians AND intitle:richness OR intitle:diversity AND environment OR landscape - and then browse thru the results. But, this is often tedious and a way for a quick visual examination would be of great benefit.

The code I present will solve this task. It may be awkward in places and there might be a more effective way to yield the same result - but it may serve as a starter and I would very much appreciate people more literate than me picking up the torch...

For my example-search it is shown that there has not been very much going on regarding amphibian diversity correlated to environment and landscape...

See code HERE.

PS: I'd be happy about collaboration / tips / editing - so feel free to contact me and I will add you to the list of editors - you then could edit / comment / add to the script on Google Docs.

...some drawbacks need to be considered:

• Maximum no. of search results = 100
• Only titles are considered. Additionally considering abstracts may yield more representative results.. but abstracts are truncated in the search result and I don't know if it is possible to retrieve the full abstracts.
• Also, long titles may be truncated...
• A more illustrative result would be achieved if one could get rid of all other words than nouns, verbs and adjectives - don't know how to do this, but I am sure this is possible.
• more drawbacks? you tell..
  

Replying to Ben Bolker's post Google Scholar (still) sucks:

Ben,

thanks for illustrating the issue in your post!

The main purpose of my function GScholarScraper is to retrieve titles - just because this is the best we can get from Google Scholar. Abstracts are truncated and thus shouldn't be used for meta-analysis. Also titles are truncated, as you said, and there is no way around. Though, this is not as often and severe as with abstracts, i.e.

The CSV is optional, the df with word frequencies and the word cloud are always returned - for any other output one can easily add some appropriate lines to the script.

My opinion:
My function is good for a quick summary and illustration of a query-result.

Tony's function is evidently better if you want to pull all fields of a given query (authors, titles, abstracts,..)

I wonder if people came across ROpenSci? I guess that might be very interesting in this context!

Last remark: Of course, a Google Scholar API would resolve all our problems in this regard..

Best,
Kay

Here's a short follow-up on how to produce a word cloud for a search result from GScholarScraper_3.1:

# File-Name: GScholarScraper_3.1.R
# Date: 2012-08-22
# Author: Kay Cichini
# Email: kay.cichini@gmail.com
# Purpose: Scrape Google Scholar search result
# Packages used: XML
# Licence: CC BY-SA-NC
#
# Arguments:
# (1) input:
# A search string as used in Google Scholar search dialog
#
# (2) write:
# Logical, should a table be writen to user default directory?
# if TRUE ("T") a CSV-file with hyperlinks to the publications will be created.
#
# Difference to version 3:
# (3) added "since" argument - define year since when publications should be returned..
# defaults to 1900..
#
# (4) added "citation" argument - logical, if "0" citations are included
# defaults to "1" and no citations will be included..
# added field "YEAR" to output 
#
# Caveat: if a submitted search string gives more than 1000 hits there seem
# to be some problems (I guess I'm being stopped by Google for roboting the site..)
#
# And, there is an issue with this error message:
# > Error in htmlParse(URL): 
# > error in creating parser for http://scholar.google.com/scholar?q
# I haven't figured out his one yet.. most likely also a Google blocking mechanism..
# Reconnecting / new IP-address helps..


GScholar_Scraper <- function(input, since = 1900, write = F, citation = 1) {

    require(XML)

    # putting together the search-URL:
    URL <- paste("http://scholar.google.com/scholar?q=", input, "&as_sdt=1,5&as_vis=", 
                 citation, "&as_ylo=", since, sep = "")
    cat("\nThe URL used is: ", "\n----\n", paste("* ", "http://scholar.google.com/scholar?q=", input, "&as_sdt=1,5&as_vis=", 
                 citation, "&as_ylo=", since, " *", sep = ""))
    
    # get content and parse it:
    doc <- htmlParse(URL)
    
    # number of hits:
    h1 <- xpathSApply(doc, "//div[@id='gs_ab_md']", xmlValue)
    h2 <- strsplit(h1, " ")[[1]][2] 
    num <- as.integer(sub("[[:punct:]]", "", h2))
    cat("\n\nNumber of hits: ", num, "\n----\n", "If this number is far from the returned results\nsomething might have gone wrong..\n\n", sep = "")
    
    # If there are no results, stop and throw an error message:
    if (num == 0 | is.na(num)) {
        stop("\n\n...There is no result for the submitted search string!")
    }
    
    pages.max <- ceiling(num/100)
    
    # 'start' as used in URL:
    start <- 100 * 1:pages.max - 100
    
    # Collect URLs as list:
    URLs <- paste("http://scholar.google.com/scholar?start=", start, "&q=", input, 
                  "&num=100&as_sdt=1,5&as_vis=", citation, "&as_ylo=", since, sep = "")
    
    scraper_internal <- function(x) {
        
        doc <- htmlParse(x, encoding="UTF-8")
        
        # titles:
        tit <- xpathSApply(doc, "//h3[@class='gs_rt']", xmlValue)
        
        # publication:
        pub <- xpathSApply(doc, "//div[@class='gs_a']", xmlValue)
        
        # links:
        lin <- xpathSApply(doc, "//h3[@class='gs_rt']/a", xmlAttrs)
        
        # summaries are truncated, and thus wont be used..  
        # abst <- xpathSApply(doc, '//div[@class='gs_rs']', xmlValue)
        # ..to be extended for individual needs
        options(warn=(-1))
        dat <- data.frame(TITLES = tit, PUBLICATION = pub, 
                          YEAR = as.integer(gsub(".*\\s(\\d{4})\\s.*", "\\1", pub)),
                          LINKS = lin)
        options(warn=0)
        return(dat)
    }

    result <- do.call("rbind", lapply(URLs, scraper_internal))
    if (write == T) {
      result$LINKS <- paste("=Hyperlink(","\"", result$LINKS, "\"", ")", sep = "")
      write.table(result, "GScholar_Output.CSV", sep = ";", 
                  row.names = F, quote = F)
      shell.exec("GScholar_Output.CSV") 
      } else {
      return(result)
    }
}

# EXAMPLE:

input <- "allintitle:amphibian+diversity"
df <- GScholar_Scraper(input, since = 1980, citation = 1)

#install.packages("tm")
library(tm)

#install.packages("wordcloud")
library(wordcloud)

corpus <- Corpus(VectorSource(df$TITLES))
corpus <- tm_map(corpus, function(x)removeWords(x, c(stopwords(), "PDF", "B", "DOC", "HTML", "BOOK", "CITATION")))
corpus <- tm_map(corpus, removePunctuation)
tdm <- TermDocumentMatrix(corpus)
m <- as.matrix(tdm)
v <- sort(rowSums(m), decreasing = TRUE)
d <- data.frame(word = names(v), freq = v)

# remove numbers from strings:
d <- d[-grep("[0-9]", d$word), ]

# print wordcloud:
wordcloud(d$word, d$freq)

A commentator on my blog brought up this nice idea of how to use the GScholarScraper function for bibliometrics..
I altered the code a little bit which enables to set a year since when results should be returned and added a field to the output collecting the year of publication. With this you can simply do something like this:

input <- "intitle:metapopulation"
df <- GScholar_Scraper(input, since = 1980, citation = 1)
nrow(df)
hist(df$YEAR, xlab = "Year", 
     main = "Frequency of Publications with\n\"METAPOPULATION\" in Title")