Simple changes to content curation algorithms affect the beliefs people form in a collaborative filtering experiment Article Swipe
Jason W. Burton
,
Stefan M. Herzog
,
Philipp Lorenz-Spreen
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.31234/osf.io/5yfbt_v2
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.31234/osf.io/5yfbt_v2
Content-curating algorithms provide a crucial service for social media users by surfacing relevant content, but they can also bring about harms when their objectives are misaligned with user values and welfare. Yet, potential behavioral consequences of this alignment problem remain understudied in controlled experiments. In a preregistered, two-wave, collaborative filtering experiment, we demonstrate that small changes to the metrics used for sampling and ranking posts affect the beliefs people form. Our results show observable differences in two types of outcomes within statisticized groups: belief accuracy and consensus. We find partial support for hypotheses that the recently proposed approaches of "bridging-based ranking" and "intelligence-based ranking" promote consensus and belief accuracy, respectively. We also find that while personalized, engagement-based ranking promotes posts that participants perceive favorably, it simultaneously leads those participants to form more polarized and less accurate beliefs than any of the other algorithms considered.
Related Topics
Concepts
Ranking (information retrieval)
Affect (linguistics)
Computer science
Bridging (networking)
Collaborative filtering
Simple (philosophy)
Content (measure theory)
Information retrieval
Psychology
Social psychology
Artificial intelligence
Algorithm
Mathematics
Recommender system
Epistemology
Communication
Computer network
Philosophy
Mathematical analysis
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.31234/osf.io/5yfbt_v2
- https://osf.io/5yfbt_v2/download
- OA Status
- gold
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411300193
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4411300193Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.31234/osf.io/5yfbt_v2Digital Object Identifier
- Title
-
Simple changes to content curation algorithms affect the beliefs people form in a collaborative filtering experimentWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2025Year of publication
- Publication date
-
2025-06-13Full publication date if available
- Authors
-
Jason W. Burton, Stefan M. Herzog, Philipp Lorenz-SpreenList of authors in order
- Landing page
-
https://doi.org/10.31234/osf.io/5yfbt_v2Publisher landing page
- PDF URL
-
https://osf.io/5yfbt_v2/downloadDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://osf.io/5yfbt_v2/downloadDirect OA link when available
- Concepts
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Ranking (information retrieval), Affect (linguistics), Computer science, Bridging (networking), Collaborative filtering, Simple (philosophy), Content (measure theory), Information retrieval, Psychology, Social psychology, Artificial intelligence, Algorithm, Mathematics, Recommender system, Epistemology, Communication, Computer network, Philosophy, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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