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We're experimenting with giving developers the ability to upvote features that they're interested in. In addition to the obvious developer signal of the current # of upvotes, it would also be useful to be able to track this number over time, ideally by day. That data would be especially useful to see how the rate of interest has changed and when particular moments of interest occurred.
Example use cases:
- Sort and filter the features that have gotten the most upvotes in the past X days as a way of seeing "what's hot"
- See how changes in the number of browser implementations affect the rate of developer interest in a feature
- Correlate surges in upvotes with the timing of influential posts, for attribution and measuring impact
If I were to prototype something like this, I'd use Apps Script on a daily trigger to query the GitHub API for all issues, extract the number of upvotes, save the results to Google Sheets, and visualize it in a public Looker Studio dashboard.
foolip
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