Data that goes with "Understanding user support systems in open source", an analysis of user support systems in open source.
I used BigQuery’s GitHub data set to pull a list of top open source projects (public + OSS license detected) on GitHub, by most issues opened in the most recent year (8/29/17-8/29/18). Of these, I removed a bunch of noisy data to end up with a “top 100” list.
Some criteria for how I cleaned up the data:
- Only looked at projects with >2 contributors
- Only looked at software projects (not content)
- Only looked at English-speaking projects, so I could understand them for the analysis
- Archived repositories were removed
- Mirrors of other issue trackers were removed
- Junk repositories and personal projects were removed
After getting a top 100 list, I went through each project and collected data about their support systems. This information was collected and recorded between September 5th-10th, 2018.
Some information on criteria and caveats:
- I only included a channel if the project officially named it as a support channel. Ex. A project might have a mailing list, but if it's used for general chatter, I didn't count it.
- Dedicated security channels (like HackerOne, or an email address) weren't included, as they're a specialized form of support
- An absolute count of support channels doesn't reflect the relative use and popularity of those channels. Ex. A project might list Stack Overflow and Gitter as channels, but hardly ever use the latter. I still counted both.
async_count
includesgh_issues
mailing_list
includes mailing list groups (like Google Groups and groups.io)
Special thanks to Raúl Kripalani for the BigQuery help.
Feedback or questions can be directed to @nayafia
I don't plan to update or change this data set. If you'd like to add more data however, or if you spot any errors, feel free to open a pull request.
This data is available under the Creative Commons CC0 1.0 License, meaning you are free to use it for any purpose, commercial or non-commercial, without any attribution back to me (public domain). If you do use it, I'd love to hear about it! (Find me here: @nayafia) But you are in no way required to do so.