Community Data: What to Measure and Why?
Talkat Open Source Summit North America 2022 · on Friday, 2022-06-24· at 11:10· Room 301/302 (Level 3), JW Marriott Austin, 110 E 2nd Street Austin, TX 78701·
summary
Argues that useful community metrics come from concrete questions, not vanity counts, and shows a repeatable workflow: pick a magic 8-ball question, map available sources (e.g. GitHub API or chat logs), then convert subquestions into metrics. Gives specific measures — 150 contributors, months with 100 vs 40 commits, distinguish active vs drifting contributors and repeat vs flyby (<4 contributions) — and demonstrates a dashboard that aggregates repos, lets thresholds be tuned, and drives hypothesis-led community experiments (examples used successfully with Fedora and internal dashboards).
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chapters (20)
- 0:00Start
- 0:51What Can Strong Community Metrics Enable
- 2:41Expose Areas of Improvement or Highlighting Strengths
- 3:30Community Impact or Business Impact
- 5:06Codifying Problems and Metrics
- 5:32Analysis Angles
- 5:58Number of Contributors
- 6:23Active versus Drifting Contributors
- 6:52Repeat versus Flyby Contributors of the Time
- 7:21Commits Overtime
- 7:36The Depth of Commit over Time
- 8:08Commits by a Subset of Contributors
- 8:35Community Campaign Impact Measurement
- 10:24Scenario Three
- 10:59Breaking Down Your Focus Area
- 13:17Select the Specific Data Points Needed
- 14:56Analysis in Action
- 23:45Data Analysis
- 25:14Closing Thoughts
- 34:05What Are the Things That We Should Keep an Eye on Initially To Build Out a Healthy Community Measuring Program
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