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[There's a decent book](https://www.morganclaypool.com/doi/abs/10.2200/S00624ED1V01Y201501ICR039) on this (and it's FREE!)
# The data
I get most of my data from Web of Science, which I'm able to access [here](http://resolver.library.cornell.edu/misc/4283377) when on the Cornell internet.
I use a nice scraper, which methodically downloads records 500 at a time.
There are other sources of bibliographic data, but I can't speak to most of them. WoS has proved to be clean and reliable, and others have just presented me with issues.
+ [Academic tree](https://academictree.org/) - ancestry of academics, who mentors who, seems really useful
+ [Open Syllabus project](https://opensyllabus.org/) - have wanted to use this data for a while. millions of syllabi in the last couple decades
+ [Dimensions](https://twitter.com/DSDimensions) - dynamic linked research data platform that re-imagines the way research can be discovered, accessed and analyzed
+ [Microsoft Academic](https://twitter.com/MSFTAcademic) - to help the academic community find academic content, researchers, institutions, and activities
+ [Semantic Scholar](https://twitter.com/SemanticScholar) - AI-powered research tool for scientific literature
# The software
+ [VOSviewer](https://www.vosviewer.com/) and (much less so) [CitNetExplorer](https://www.citnetexplorer.nl/).
+ In R, use [bibliometrix](https://cran.r-project.org/web/packages/bibliometrix/vignettes/bibliometrix-vignette.html) (also there is [wosr](https://cran.r-project.org/web/packages/wosr/wosr.pdf) but I don't know what it does)
+ I don't know any tools in python, but once you extract the WOS bibliographic data (most easily using VOSviewer) you can export to a network and analyze using typical social network analysis tools, some of which are OK in Python