  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
