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#algorithmictimelines

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ABC News (Australia): How to find out your TikTok personality – and become a ‘citizen scientist’. “It’s no secret that TikTok collects data about its users, but it can be hard to know exactly how it’s being used. Do you know what your data says about you? Finding the answers to that question — both for individuals and as a society — is one of the goals of the For You Research […]

https://rbfirehose.com/2025/04/17/abc-news-australia-how-to-find-out-your-tiktok-personality-and-become-a-citizen-scientist/

Concordia University: New Concordia research shows social networks are vulnerable to relatively simple AI manipulation and polarization. “It seems that no matter the topic of conversation, online opinion around it will be split into two seemingly irreconcilable camps. That’s largely a result of these platforms’ design, as the algorithms driving them direct users to like-minded peers. This […]

https://rbfirehose.com/2025/04/17/concordia-university-new-concordia-research-shows-social-networks-are-vulnerable-to-relatively-simple-ai-manipulation-and-polarization/

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@schizanon

I'd like a feature (for Tusky) that shows me the fraction of posts (account's posts / all posts in my personal timeline) of each account I follow, for a specified timeframe, say last 1/3/6 months.

And ideally, there'd then be a feature to show a thinned out personal timeline that contains only toots of the more silent accounts (starting with the most silent) so that there's in total only x number of toots per week (say 70 or so).

I doubt that most people defending the "simple reverse chronological timeline" in #Mastodon, opposing #algorithmicTimelines, have any idea of how it currently works.

Because, having debugged that code and the SQL, I can confidently say that hardly anyone can understand the current algorithms.

There's thousands (inc. dependencies) lines of code and logic, generating very complex SQL queries to fill your seemingly simple reverse chronological timeline. Complex algos already fill your timeline.

Looking at the #analytics of the old 🆓🐦 site makes me sad to see the day that in less than two months the sale of #Twitter made the site completely useless and the move to #web3 accelerate beyond the #ToxicSocialMedaOnePointOh of #AlgorithmicTimelines driven by #Meta #Instagram #Snapchat #WhatsApp & #Twitter dying a horrible race to the bottom #ARPU #DAU #DAP driven #decline of #web1 & #web2 technologies. 👎

☠️💀⚰️🥀R.I.P. 💀☠️🥀⚰️⚱️😐
👎☠️ #AlgorithmicTimelines ☠️👎