Short-term exposure to filter-bubble recommendation systems has limited polarization effects: Naturalistic experiments on YouTube.

ABSTRACT: An enormous body of literature argues that recommendation algorithms drive political polarization by creating "filter bubbles" and "rabbit holes." Using four experiments with nearly 9,000 participants, we show that manipulating algorithmic recommendations to create these conditions has limited effects on opinions. Our experiments employ a custom-built video platform with a naturalistic, YouTube-like interface presenting real YouTube videos and recommendations. We experimentally manipulate YouTube's actual recommendation algorithm to simulate filter bubbles and rabbit holes by presenting ideologically balanced and slanted choices. Our design allows us to intervene in a feedback loop that has confounded the study of algorithmic polarization-the complex interplay between supply of recommendat

SUBMITTER: Liu N 

PROVIDER: S-EPMC11874454 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature