Social media algorithms shape the beliefs people form
www.mpg.de
The content people see on social media is typically determined by an algorithm. Researchers from the University of Copenhagen, the Max Planck Institute for Human Development, and TU Dresden have now demonstrated in a controlled experiment involving approximately 1,500 participants that simple changes to how posts are sampled and ranked can affect the beliefs people form. The study suggests that alternative approaches to algorithmic content curation along with prosocial platform design may promote consensus and belief accuracy.

cross-posted from: https://piefed.world/c/tech/p/1305963/social-media-algorithms-shape-the-beliefs-people-form-even-small-changes-to-content-cura

Research Paper.

  • Algorithms shape the beliefs people form: Simple changes to content curation algorithms can affect beliefs, consensus, and belief accuracy.
  • Personalized engagement-based ranking can be problematic: Although users perceive these feeds positively, they tend to lead to less consensus and less accurate beliefs.
  • Consensus is possible: Bridging-based ranking can help promote consensus by surfacing content that receives approval across different groups.
  • Belief accuracy can be improved: Intelligence-based ranking can promote more accurate collective and individual judgments.
  • Small algorithmic changes can have large effects: Simple changes to how posts are sampled and ranked can substantially influence the beliefs people form.
  • PierceTheBubble@lemmy.mlEnglish
    2·
    7 hours ago

    lead people to form erroneous beliefs … whether they promote consensus or belief accuracy … more polarized and less accurate beliefs … help users find more mutual understanding on these platforms … content that receives approval across different groups is promoted … bridge divides and encourage positive interactions across diverse audiences … bridging-based ranking can promote consensus … elicit belief updates that benefit collective accuracy … improve both collective accuracy and average individual accuracy … aligning them more closely with socially desirable goals

    I don’t know what’s creepier: a polarized society but with a more diverse view on topics, or a cohesive society with an eerily uniform view instead. Polarization is problematic, but so is thought-policing. I would argue feeds shouldn’t be algorithmically determined, but composed of content by channels the user has explicitly chosen to subscribe to; and a separate explore feature for interest-based suggestions, without creepy “this is what most people agree with, and so should you” course-correction measures.