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Threads would be much better if it had the algorithm of TikTok. Basic things like I scroll through Threads on my iPhone (while logged into my account) and then
by s1mon 3y ago
Threads would be much better if it had the algorithm of TikTok.
Basic things like I scroll through Threads on my iPhone (while logged into my account) and then I do the same on my iPad and it shows me the same posts. WTF?!? Keeping track of what I've read (or at least scrolled past) is really basic and has been part of email, newsgroups, etc. for decades.
TikTok does this pretty well but it is also pathologically good at picking new things based on your viewing habits. It has a huge advantage over Threads (and Facebook, Instagram, X, etc) in that TikTok only presents one thing at a time to the user. If I flick it away in a fraction of a second, it shows that something has triggered me (boredom, disgust, etc) to move to the next thing. If I watch one clip multiple times and/or dig into the comments or other clips from the same creator, or even follow a creator, chances are I want to see more of that and/or more like that. I'm sure it's more complex, but there's a lot of feedback to the algorithm there. Facebook and Instagram try to learn from the "more..." buttons that expand comments, but it's not really the same level of information.
As it stands, the discovery process on Threads is no where near as compelling as it is on TikTok.
- deleted 3y ago[deleted]
- unethical_ban 3y agoThreads hasn't built the better misinformation machine/dopamine generator/rage inducer, you say? Maybe I should sign up.
- disgruntledphd2 3y ago> TikTok does this pretty well but it is also pathologically good at picking new things based on your viewing habits. It has a huge advantage over Threads (and Facebook, Instagram, X, etc) in that TikTok only presents one thing at a time to the user. I'm glad someone else gets this. Fundamentally, TikTok are solving a much, much easier ML problem than FB/IG/Twitter et al. They can classify every post you see much more easily than the others. This is presumably (maybe) because they were built as products with ML in mind, rather than having it tacked on at the end.