Auditing health-related recommendations in social media: A Case Study of Abortion on YouTube
Fuente:
arXiv
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866910406354665472 |
|---|---|
| author | Lahsaini, Mohammed Lechiakh, Mohamed Maurer, Alexandre |
| author_facet | Lahsaini, Mohammed Lechiakh, Mohamed Maurer, Alexandre |
| contents | Recommendation algorithms (RS) used by social media, like YouTube, significantly shape our information consumption across various domains, especially in healthcare. Hence, algorithmic auditing becomes crucial to uncover their potential bias and misinformation, particularly in the context of controversial topics like abortion. We introduce a simple yet effective sock puppet auditing approach to investigate how YouTube recommends abortion-related videos to individuals with different backgrounds. Our framework allows for efficient auditing of RS, regardless of the complexity of the underlying algorithms |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_07896 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Auditing health-related recommendations in social media: A Case Study of Abortion on YouTube Lahsaini, Mohammed Lechiakh, Mohamed Maurer, Alexandre Social and Information Networks Information Retrieval Recommendation algorithms (RS) used by social media, like YouTube, significantly shape our information consumption across various domains, especially in healthcare. Hence, algorithmic auditing becomes crucial to uncover their potential bias and misinformation, particularly in the context of controversial topics like abortion. We introduce a simple yet effective sock puppet auditing approach to investigate how YouTube recommends abortion-related videos to individuals with different backgrounds. Our framework allows for efficient auditing of RS, regardless of the complexity of the underlying algorithms |
| title | Auditing health-related recommendations in social media: A Case Study of Abortion on YouTube |
| topic | Social and Information Networks Information Retrieval |
| url | https://arxiv.org/abs/2404.07896 |