Duolingo vs LinkedIn
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
Duolingo and LinkedIn both appear on the Smoower Developer Ecosystem Index.
Duolingo and LinkedIn sit at essentially the same overall ecosystem score (43), which is unusual and worth reading through the pillars below.
On code quality (the state of repositories, tests, releases and polish), LinkedIn is ahead of Duolingo. On education (docs, guides and learning material for developers), LinkedIn is slightly ahead of Duolingo. On community (issue response, PR reviews and discussion health), LinkedIn is ahead of Duolingo. On reach (how visible the ecosystem is beyond its own repos), LinkedIn is ahead of Duolingo. On momentum (release cadence and how fast the ecosystem moves), Duolingo is slightly ahead of LinkedIn.
Duolingo carries 1,721 GitHub stars across 12 public repos, with 8 repositories active in the last 90 days and 11 external contributors on record. LinkedIn shows 77,785 stars across 137 public repos, 28 active in the last 90 days and 52 external contributors. The star gap on its own does not decide the comparison, but LinkedIn's footprint is roughly 45.2x larger, which usually shows up in downstream signals like inbound issues and third party integrations.
Duolingo is the stronger read for anyone weighting momentum. LinkedIn looks better where code quality is the deciding factor. The table below breaks the scores down pillar by pillar; the linked profiles cover the underlying repos, docs and community signals in full.
Side-by-side metrics
| Metric | Duolingo | |
|---|---|---|
| Ranking | ||
| Overall rank | #338 | #338 |
| Pillars | ||
| Overall | 43 | 43 |
| Code | 44 | 63 |
| Education | 47 | 54 |
| Community | 37 | 49 |
| Reach | 49 | 61 |
| Momentum | 38 | 37 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 1,721 | 77,785 |
| Forks | 267 | 12,231 |
| Public repos | 12 | 137 |
| Active repos (90d) | 8 | 28 |
| External contributors | 11 | 52 |
| Avg polish | 51 | 64 |
| Avg AI-readiness | 30 | 43 |