this post was submitted on 29 Jul 2023
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Meta conducted an experiment where thousands of users were shown chronological feeds on Facebook and Instagram for three months. Users of the chronological feeds engaged less with the platforms and were more likely to use competitors like YouTube and TikTok. This suggests that users prefer algorithmically ranked feeds that show them more relevant content, even though some argue chronological feeds provide more transparency. While the experiment found that chronological feeds exposed users to more political and untrustworthy content, it did not significantly impact their political views or behaviors. The researchers note that a permanent switch to chronological feeds could produce different results, but this study provides only a glimpse into the issue.


I think this is bullshit. I exclusively scroll Lemmy in new mode. I scroll I see a post I already have seen. Then I leave. That doesn't mean I hate it, I'm just done!

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[–] Zeth0s@reddthat.com 4 points 1 year ago* (last edited 1 year ago) (1 children)

It is not at the moment. Models are built on the assumption of stability, i.e. that what they are modelling doesn't change over time, doesn't evolve. This is clearly untrue, and cheating is a way the environment evolves. Only way to consider that, is to create a on-line continous learning algorithm. Currently this exists and is called reinforcement learning. Main issue is that methods to account for an evolving environment are still under active research. In the sense that methods to address this issue are not yet available.

It is an extremely difficult task tbf

[–] OneRedFox@beehaw.org 3 points 1 year ago (1 children)

Ok, then what about algorithms that are reasonably difficult to game?

[–] Zeth0s@reddthat.com 4 points 1 year ago* (last edited 1 year ago)

It requires continuous expansive improvements. It is like real world. Building a system robust to frauds works on the short term, but on the mid and long term is impossibile. That is why laws change, evolve, we have governments and so on. Because system reacts to your rules and algorithms, making them less effective.

And these continous expensive improvements are done daily, but it is a difficult job