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name layout title date author sourceslug tags
get-ecoevo-journal-titles
post
Getting ecology and evolution journal titles from R
2012-08-31
Scott Chamberlain
_drafts/2012-08-31-get-ecoevo-journal-titles.Rmd
R
altmetrics
ecology
evolution
doi

So I want to mine some #altmetrics data for some research I'm thinking about doing. The steps would be:

  • Get journal titles for ecology and evolution journals.
  • Get DOI's for all papers in all the above journal titles.
  • Get altmetrics data on each DOI.
  • Do some fancy analyses.
  • Make som pretty figs.
  • Write up results.

It's early days, so jus working on the first step. However, getting a list of journals in ecology and evolution is frustratingly hard. This turns out to not be that easy if you are (1) trying to avoid Thomson Reuters, and (2) want a machine interface way to do it (read: API).

Unfortunately, Mendeley's API does not have methods for getting a list of journals by field, or at least I don't know how to do it using their API. No worries though - Crossref comes to save the day. Here's my attempt at this using the Crossref OAI-PMH.


I wrote a little while loop to get journal titles from the Crossref OAI-PMH. This takes a while to run, but at least it works on my machine - hopefully yours too!

{% highlight r linenos %} library(XML) library(RCurl)

token <- "characters" # define a iterator, also used for gettingn the resumptionToken nameslist <- list() # define empty list to put joural titles in to while (is.character(token) == TRUE) { baseurl <- "http://oai.crossref.org/OAIHandler?verb=ListSets" if (token == "characters") { tok2 <- NULL } else { tok2 <- paste("&resumptionToken=", token, sep = "") } query <- paste(baseurl, tok2, sep = "") crsets <- xmlToList(xmlParse(getURL(query))) names <- as.character(sapply(crsets[[4]], function(x) x[["setName"]])) nameslist[[token]] <- names if (class(try(crsets[[2]]$.attrs[["resumptionToken"]])) == "try-error") { stop("no more data") } else token <- crsets[[2]]$.attrs[["resumptionToken"]] } {% endhighlight %}


Yay! Hopefully it worked if you tried it. Let's see how long the list of journal titles is.

{% highlight r linenos %} sapply(nameslist, length) # length of each list {% endhighlight %}

{% highlight text %} characters c65ebc3f-b540-4672-9c00-f3135bf849e3 10001 10001 6f61b343-a8f4-48f1-8297-c6f6909ca7f7 6864 {% endhighlight %}

{% highlight r linenos %} allnames <- do.call(c, nameslist) # combine to list length(allnames) {% endhighlight %}

{% highlight text %} [1] 26866 {% endhighlight %}


Now, let's use some regex to pull out the journal titles that are likely ecology and evolutionary biology journals. The ^ symbol says "the string must start here". The \\s means whitespace. The [] lets you specify a set of letters you are looking for, e.g., [Ee] means capital E OR lowercase e. I threw in titles that had the words systematic and natrualist too. Tried to trim any whitespace as well using the stringr package.

{% highlight r linenos %} library(stringr)

ecotitles <- as.character(allnames[str_detect(allnames, "^[Ee]cology|\s[Ee]cology")]) evotitles <- as.character(allnames[str_detect(allnames, "^[Ee]volution|\s[Ee]volution")]) systtitles <- as.character(allnames[str_detect(allnames, "^[Ss]ystematic|\s[Ss]systematic")]) naturalist <- as.character(allnames[str_detect(allnames, "[Nn]aturalist")])

ecoevotitles <- unique(c(ecotitles, evotitles, systtitles, naturalist)) # combine to list ecoevotitles <- str_trim(ecoevotitles, side = "both") # trim whitespace, if any length(ecoevotitles) {% endhighlight %}

{% highlight text %} [1] 188 {% endhighlight %}

{% highlight r linenos %}

Just the first ten titles

ecoevotitles[1:10] {% endhighlight %}

{% highlight text %} [1] "Microbial Ecology in Health and Disease"
[2] "Population Ecology"
[3] "Researches on Population Ecology"
[4] "Behavioral Ecology and Sociobiology"
[5] "Microbial Ecology"
[6] "Biochemical Systematics and Ecology"
[7] "FEMS Microbiology Ecology"
[8] "Journal of Experimental Marine Biology and Ecology" [9] "Applied Soil Ecology"
[10] "Forest Ecology and Management"
{% endhighlight %}


Get the .Rmd file used to create this post at my github account.


Written in Markdown, with help from knitr, and nice knitr highlighting/etc. in in RStudio.