aritter on Nostr: Now that #[0] launched nostr-relaypool-ts, and it's working great for retrieval, I ...
Now that
Iris (npub1wnw…95l8) launched nostr-relaypool-ts, and it's working great for retrieval, I started to focus on what I originally was interested in: ranking.
So far it's in the planning stage, but I think it's going well. For now I'm planning on developing a pLike | note model (predicting whether a note is going to be liked by a user). I'm planning to use logistic regression with the following signals as a start:
- time passed since note was created
- note's author is followed by user
- number of likes
- number of comments
- share of likes from the author by the user in the past
- does it contain image?
- does it contain link?
- does it contain video?
- text length
- likes by followers
Some are easier to implement, some are a bit harder, and of course I'll check their impact before launching them.
I think I will order threads by the maximum probability that a note has in a thread. Also pLike can be used as a filter for comments to be shown / hidden. Of course pComment model can be trained on the same signal.
Published at
2023-04-16 09:00:34Event JSON
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"created_at": 1681628434,
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"content": "Now that #[0] launched nostr-relaypool-ts, and it's working great for retrieval, I started to focus on what I originally was interested in: ranking.\n\nSo far it's in the planning stage, but I think it's going well. For now I'm planning on developing a pLike | note model (predicting whether a note is going to be liked by a user). I'm planning to use logistic regression with the following signals as a start:\n\n - time passed since note was created\n - note's author is followed by user \n - number of likes\n - number of comments\n - share of likes from the author by the user in the past\n - does it contain image?\n - does it contain link?\n - does it contain video?\n - text length\n - likes by followers\n\nSome are easier to implement, some are a bit harder, and of course I'll check their impact before launching them.\n\nI think I will order threads by the maximum probability that a note has in a thread. Also pLike can be used as a filter for comments to be shown / hidden. Of course pComment model can be trained on the same signal.",
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}