16 Comments

i wonder if SubStack also has a similar recommendation algorithm. anyhow, commenting here to boost the algorithm 😈😈🥶

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It’s like we’re stuck in this infinite game where creators and platforms keep optimizing each other.

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Comment for engagement!

Anyway, I want off Mr. Bones wild ride. I'm sick of my attention being gamified by everyone and everything online, but is this reversible?

I'm hopeful there will one day be algorithms that optimize well being and provide entertainment that's satisfying rather than addicting, but I have no idea how to get there.

I try to do this on my own by consciously interacting with things that are more deeply 'engaging' but I think anyone who spends time online can attest that it's an uphill battle.

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I like your idea of algorithms that could optimize well being and satisfying entertainment; I think this would have to be developed by the nonprofit or public sector because social media companies make so much profit off our addiction they would resist a healthy algorithm.

It is an uphill battle on multiple fronts

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Hopefully this comment can assist you Mr. Nerd

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Would be interesting, as you’re an “influencer” now, to see if you can get your horde of followers to make a new (or not) word trend to show the treadmill in action.

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It really ain't no joke to say someone is "riding the trend."

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I think the way music gets caught in the algorithm is just as interesting. Unlike words, songs do not have the same property to change and evolve since they are a product of a specific time when they were recorded and mixed. They might be interpreted differently or remixed (sped up/slowed down + reverb) and so on. When you put on a song and listen hear it too many times, you still have the power to stop listening to the song. But when songs then begin to trend and be played in almost every single video they eventually become so overplayed that it is exhausting when you hear it. Listeners will have a feeling of the song itself being forever "branded" as a "TikTok song". I saw a reel on instagram with Crowded House - Don't Dream it's Over playing and people in the comments who already liked the song lamented that it would now be ruined by the algorithm.

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I really love learning about how language can develop and how often nonsensical words can become embedded in normal life. Hopefully I can write an essay about this in the future.

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Cromulent

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The idea that a post will do better because it received more likes/engagement within a certain time period is a common misconception.

Post do not get “pushed” because of the overall engagement. It’s from the content consumer POV that an algorithm will rank the posts based on the ML predictions that use signals to make them.

There is no algorithm at play when posting, only when opening up the app & consuming recommendations are made, which rarely use likes or comments as a signal to base any prediction on.

I recommend checking out https://transparency.meta.com/features/explaining-ranking/

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You're incorrect. Please read my citation from the Knight First Amendment Institute at Columbia University for a thorough explanation.

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I did before writing my reply. Although the citation has a broad range of assumptions & inaccuracies, I did indeed make a mistake: I had Instagram recommendation systems in mind while reading your article, while TikTok was the main focus here. My knowledge on TikTok’s, mostly interest graph based, recommendation systems is fairly limited.

My apologies!

Nonetheless, I do want to add that your writings are very interesting & I enjoy reading them!! full support!!

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like with "shrek is love, shrek is life" or pepe mutations.

original vision is gone.

like when "gay" was slur. and then gay community took it and made into their powerword. there sure are other examples of this but i currently forgot any others.

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Also gay meant just happy before

Forgot that

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I wonder at what point will I stop learning new internet words myself and start learning them from you

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