{"type":"rich","version":"1.0","title":"aritter wrote","author_name":"aritter (npub1dc…ux5ey)","author_url":"https://yabu.me/npub1dcl4zejwr8sg9h6jzl75fy4mj6g8gpdqkfczseca6lef0d5gvzxqvux5ey","provider_name":"njump","provider_url":"https://yabu.me","html":"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."}