KB Full Text Search (Beta)
You are here:

Project Popularity

Question: How popular is an open source project?

Description

Project popularity can be measured by how much activity is visible around a project. Popularity has a positive feedback loop in which more popular projects get more attention, attract more users or developers, and see increases in popularity, spinning the popularity wheel.

Project popularity may be used as a proxy for understanding project value because open source project economic value is hard to measure, due to a lack of available usage or sales information for open source projects.

Objectives

In a quest to earn a living wage, and to maximize future employment opportunities, workers may be interested in knowing which projects are growing and are underserved. Similarly, from an organizational perspective, knowing which projects are highly used can be helpful in knowing which projects might be worth investing in. The Project Popularity metric can be used to identify the trajectory of a project’s development.

Implementation

The project popularity metric is often considered with changes over time. There are numerous example vectors to consider when measuring project popularity based on the number of:

  1. Social media mentions
  2. Forks
  3. Change requests
  4. New Issues
  5. Stars, badges, likes
  6. New contributors
  7. Organizational Diversity
  8. Job postings requesting skills in project
  9. Conversations within and outside of project
  10. Clones
  11. Followers
  12. Downstream dependencies
  13. People attending events that focus on a project

Visualizations

Issues and reviews (change requests) visualization from Cauldron (GrimoireLab):

Issues and reviews

Kubernetes project popularity statistics from DevStats:

Kubernetes_project_popularity

Tools Providing the Metric

References

To edit this metric please submit a Change Request here: https://github.com/chaoss/wg-value/blob/main/focus-areas/communal-value/project-popularity.md

To reference this metric in software or publications please use this stable URL: https://chaoss.community/?p=3573

The usage and dissemination of health metrics may lead to privacy violations. Organizations may be exposed to risks. These risks may flow from compliance with the GDPR in the EU, with state law in the US, or with other laws. There may also be contractual risks flowing from terms of service for data providers such as GitHub and GitLab. The usage of metrics must be examined for risk and potential data ethics problems. Please see CHAOSS Data Ethics document for additional guidance.

Was this article helpful?
Dislike 0