cff-version: 1.2.0
message: "If you use this dataset or code, please cite the paper."
title: "Two Buttons, One Feed: Aligning YouTube Recommendations Requires Both Controls"
abstract: >-
  Data and analysis code for a 2x2 factorial sock-puppet audit of YouTube's
  explicit feedback controls ('like' and 'not interested') across twelve
  simulated adolescent accounts.
authors:
  - family-names: Cho
    given-names: Desiree
    affiliation: "University of Oxford"
  - family-names: Hale
    given-names: Scott A.
    affiliation: "Oxford Internet Institute, University of Oxford"
  - family-names: Zhao
    given-names: Jun
    affiliation: "Department of Computer Science, University of Oxford"
  - family-names: Shadbolt
    given-names: Nigel
    affiliation: "University of Oxford"
  - family-names: Przybylski
    given-names: Andrew K.
    affiliation: "Oxford Internet Institute, University of Oxford"
license: MIT
date-released: 2025-09-11
keywords:
  - algorithm auditing
  - recommender systems
  - YouTube
  - user agency