étudier is a small Python program that uses Selenium, requests-html and networkx to drive a non-headless browser to collect a citation graph around a particular Google Scholar citation or set of search results. The resulting network is written out as GEXF and GraphML files as well as an HTML file that includes a D3 network visualization (pictured above).

If you are wondering why it uses a non-headless browser it's because Google is quite protective of this data and will routinely ask you to solve a captcha (identifying street signs, cars, etc in photos) to prove you are not a bot. étudier allows you to complete these captcha tasks when they occur and then it continues on its way collecting data. You need to have a browser to interact with in order to do your part.

Install

You'll need to install ChromeDriver before doing anything else. If you use Homebrew on OS X this is as easy as:

brew cask install chromedriver

Then you'll want to install Python 3 and:

pip3 install etudier

Run

To use étudier you first need to navigate to a page on Google Scholar that you are interested in, for example here is the page of citations that reference Sherry Ortner's Theory in Anthropology since the Sixties. Then you start etudier up pointed at that page.

% etudier 'https://scholar.google.com/scholar?start=0&hl=en&as_sdt=20000005&sciodt=0,21&cites=17950649785549691519&scipsc='

If you are interested in starting with keyword search results in Google Scholar you can do that too. For example here is the url for searching for "cscw memory" if I was interested in papers that talk about the CSCW conference and memory:

% etudier 'https://scholar.google.com/scholar?hl=en&as_sdt=0%2C21&q=cscw+memory&btnG='

Note: it's important to quote the URL so that the shell doesn't interpret the ampersands as an attempt to background the process.

--pages

By default étudier will collect the 10 citations on that page and then look at the top 10 citations that reference each one. So you will end up with no more than 100 citations being collected (10 on each page * 10 citations).

If you would like to get more than one page of results use the --pages. For example this would result in no more than 400 (20 * 20) results being collected:

% etudier --pages 2 'https://scholar.google.com/scholar?start=0&hl=en&as_sdt=20000005&sciodt=0,21&cites=17950649785549691519&scipsc=' 

--depth

And finally if you would like to look at the citations of the citations you use the --depth parameter.

% etudier --depth 2 'https://scholar.google.com/scholar?start=0&hl=en&as_sdt=20000005&sciodt=0,21&cites=17950649785549691519&scipsc='

This will collect the initial set of 10 citations, the top 10 citations for each, and then the top 10 citations of each of those, so no more than 1000 citations 1000 citations (10 * 10 * 10). It's no more because there is certain to be some cross-citation duplication.

--output

By default output.gexf, output.graphml and output.html files will be written to the current working directory, but you can change this with the --output option to control the prefix that is used. The output file will contain rudimentary metadata collected from Google Scholar including:

• id - the cluster identifier assigned by Google
• url - the url for the publication
• title - the title of the publication
• authors - a comma separated list of the publication authors
• year - the year of publication
• cited-by - the number of other publications that cite the publication
• cited-by-url - a Google Scholar URL for the list of citing publications

• modularity - the modularity value obtained from community detection

Features of HTML/D3 output

• Node's color shows its citation group
• Node's size shows its times being cited
• Click node to open its source website
• Dragable nodes
• Zoom and pan
• Double-click to center node
• Resizable window
• Text labels
• Hover to highlight 1st-order neighborhood
• Click and press node to fade surroundings