At risk of spamming, I thought it might be good to link to a few of the notebooks, to give a sense of what kinds of analysis are possible:
https://github.com/datactive/bigbang/blob/master/examples/Analyze%20Senders.ipynb https://github.com/datactive/bigbang/blob/master/examples/Cohort%20Visualization.ipynb https://github.com/datactive/bigbang/blob/master/examples/name-and-gender/Analyze%20Senders%20-%20Name%20and%20Gender.ipynb https://github.com/datactive/bigbang/blob/master/examples/Show%20Interaction%20Graph.ipynb The sky is the limit, of course :) On Tue, Mar 6, 2018 at 9:43 PM, Sebastian Benthall <sbenth...@gmail.com> wrote: > Hello list, > > I wanted to mention a project I've been working on with some other folks > that's designed to teach open source in a particulary reflexive way. > > The project is called BigBang: > > https://github.com/datactive/bigbang > > The gist of it is that it has: > - tools for ingesting data from other open source projects (mailing > lists, repository data, one day issue tracker data) > - library methods for scientifically analyzing that data > - examples of scientific analysis in Jupyter notebooks > > I've done some pilot trainings with undergrad research assistants, who > have built their own Jupyter notebooks to study open collaboration, often > examining the very communities who built the software the project depends > on. > > Lately the BigBang community has been led in a different direction: In a > couple weeks they will be at the Internet Engineering Task Force (IETF) > meeting in London and using it at the hackathon there to analyze the IETF > mailing list history. > > This is an open call to participation if anybody is interested in adapting > this project for their own teaching. I'm happy to field any questions about > it. > > Thanks for listening! > > Seb > > > Sebastian Benthall > Research Fellow, Digital Life Initiative, Cornell Tech >
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