While it is relatively easier to verify the results of filtering out "top", "important", "emergent", "important" projects in a graph network by tribal knowledge, news, reports, affiliations etc it is harder to validate the results of core, active and peripheral contributors.
To validate the results of our bucketing of contributors by count based approaches here #188, we can definitely analyze the accuracy of our contributor grouping on a case by case basis, but one way to validate the results could be to
- Try this on CNCF projects and check the overlap of the "core" category contributors displayed by our network analysis methods to the maintainers list https://github.com/cncf/foundation/blob/main/project-maintainers.csv. The intuition here is that there should be some degree of overlap between these and that would validate the results of our analysis.
- Check whether the 2nd and 3rd degree contributors (Active/Peripheral etc) have some overlap with a project's contributors. (Note sure if Augur lets us fetch this list. And although this list technically ranks all of a projects contributors, it could be a good resource for a sanity check that most of the top contributors that we fetch for a project are in fact contributing to that project)
While it is relatively easier to verify the results of filtering out "top", "important", "emergent", "important" projects in a graph network by tribal knowledge, news, reports, affiliations etc it is harder to validate the results of core, active and peripheral contributors.
To validate the results of our bucketing of contributors by count based approaches here #188, we can definitely analyze the accuracy of our contributor grouping on a case by case basis, but one way to validate the results could be to