| 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 |
|
|
