I made the site in question (81m .org). My inspiration was the work of Zoe Phin (whose name is phzoe on HN), who noticed that YouTube was deleting dislikes and decided to write some scripts and build some charts.
I replicated her approach and automated it further. The result is 81m .org.
If you want to validate my data, it is easy to do:
- Trivial way: For some video, check the official YouTube likes/dislikes/views numbers from time to time, and compare them to the numbers I display. You will see that they line up.
- Harder way: Get a YouTube API key, query `http s:// youtube.googleapis .com/youtube/v3/videos?part=statistics&id=<VIDEO_ID_HERE>&key=<API_KEY_HERE>`, and log the likes/dislikes/views for one or more videos. Compare to my data, and you will see that the two datasets line up.
You can find more info at 81m .org/about
(Sorry for the " .org" and " .com" and other whitespace insertions above. I am worried HN will shadowban me if I post links.)
I made the site in question (81m .org). My inspiration was the work of Zoe Phin (whose name is phzoe on HN), who noticed that YouTube was deleting dislikes and decided to write some scripts and build some charts.
I replicated her approach and automated it further. The result is 81m .org.
If you want to validate my data, it is easy to do:
- Trivial way: For some video, check the official YouTube likes/dislikes/views numbers from time to time, and compare them to the numbers I display. You will see that they line up.
- Harder way: Get a YouTube API key, query `http s:// youtube.googleapis .com/youtube/v3/videos?part=statistics&id=<VIDEO_ID_HERE>&key=<API_KEY_HERE>`, and log the likes/dislikes/views for one or more videos. Compare to my data, and you will see that the two datasets line up.
You can find more info at 81m .org/about
(Sorry for the " .org" and " .com" and other whitespace insertions above. I am worried HN will shadowban me if I post links.)