"Feed algorithms are widely suspected to influence political attitudes. However, previous evidence from switching off the algorithm on Meta platforms found no political effects1. Here we present results from a 2023 field experiment on Elon Musk’s platform X shedding light on this puzzle. We assigned active US-based users randomly to either an algorithmic or a chronological feed for 7 weeks, measuring political attitudes and online behaviour. Switching from a chronological to an algorithmic feed increased engagement and shifted political opinion towards more conservative positions, particularly regarding policy priorities, perceptions of criminal investigations into Donald Trump and views on the war in Ukraine. In contrast, switching from the algorithmic to the chronological feed had no comparable effects. Neither switching the algorithm on nor switching it off significantly affected affective polarization or self-reported partisanship. To investigate the mechanism, we analysed users’ feed content and behaviour. We found that the algorithm promotes conservative content and demotes posts by traditional media. Exposure to algorithmic content leads users to follow conservative political activist accounts, which they continue to follow even after switching off the algorithm, helping explain the asymmetry in effects. These results suggest that initial exposure to X’s algorithm has persistent effects on users’ current political attitudes and account-following behaviour, even in the absence of a detectable effect on partisanship."

https://www.nature.com/articles/s41586-026-10098-2

#SocialMedia #Algorithms #Twitter #Politics #RecommendationAlgorithms #PublicOpinion #Propaganda

"Feed algorithms are widely suspected to influence political attitudes. However, previous evidence from switching off the algorithm on Meta platforms found no political effects1. Here we present results from a 2023 field experiment on Elon Musk’s platform X shedding light on this puzzle. We assigned active US-based users randomly to either an algorithmic or a chronological feed for 7 weeks, measuring political attitudes and online behaviour. Switching from a chronological to an algorithmic feed increased engagement and shifted political opinion towards more conservative positions, particularly regarding policy priorities, perceptions of criminal investigations into Donald Trump and views on the war in Ukraine. In contrast, switching from the algorithmic to the chronological feed had no comparable effects. Neither switching the algorithm on nor switching it off significantly affected affective polarization or self-reported partisanship. To investigate the mechanism, we analysed users’ feed content and behaviour. We found that the algorithm promotes conservative content and demotes posts by traditional media. Exposure to algorithmic content leads users to follow conservative political activist accounts, which they continue to follow even after switching off the algorithm, helping explain the asymmetry in effects. These results suggest that initial exposure to X’s algorithm has persistent effects on users’ current political attitudes and account-following behaviour, even in the absence of a detectable effect on partisanship."

https://www.nature.com/articles/s41586-026-10098-2

#SocialMedia #Algorithms #Twitter #Politics #RecommendationAlgorithms #PublicOpinion #Propaganda

Let’s decouple the algorithm from the platform
https://josschuurmans.com/nl/blog/laten-we-het-algoritme-loskoppelen-van-het-platform/

Profile-based #recommendationalgorithms should be banned. That is the view of @bitsoffreedom, voiced by policy advisor Lotje Beek in the Bits of Freedom podcast of January 9 (https://www.bitsoffreedom.nl/podcast/nieuwe-europese-wetgeving-de-digital-fairness-act).

Together with a team from the South-Eastern Finland University of Applied Sciences, I am working on an #opensource system for transparent #information_recommendation, based on #collaborative_filtering.

(3/3)

The recommendation engines we habitually call "algorithms" have actually been *models*, not algorithms. So "AI" is just a continuation of the automated disinformation-as-usual that corporate platforms have been engaged in for almost 20 years.

#AI #MOLE #RecommendationAlgorithms