This looks really excellent – it scrapes Google Scholar, starting with a search that reveals work you already know about and that you think is significant. From those search results it generates an exportable Gephi map of authors, subject/disciplinary areas and links between them. Basically, it automatically (well – a little effort and a bit of Google Scholar/Gephi competence needed) maps out connected research areas and authors, mined from Google Scholar, including their relative significance and centrality, shaped to fit your research interests. Doing this manually, as most researchers do, takes a really long time, and it is incredibly easy to miss significant authors and connections. This looks like a fantastic way to help build a literature review, and great scaffolding to help with exploring a research area. I see endless possibilities and uses. Of course, it is only as good as the original query, and only as good as Google Scholar’s citation trail, but that’s an extremely good start, and it could be iterated many times to refine the results further. The code for the tool, Bibnet, is available through Github.
Address of the bookmark: https://mystudentvoices.com/scraping-google-scholar-to-write-your-phd-literature-chapter-2ea35f8f4fa1#.y43s1qg4l
