Auditing health-related recommendations in social media: A Case Study of Abortion on YouTube

TL;DR

This paper presents a sock puppet auditing method to analyze how YouTube's recommendation system suggests abortion-related videos to users with different backgrounds, highlighting potential biases and misinformation in healthcare content.

Contribution

It introduces a novel, simple sock puppet framework for auditing social media recommendation algorithms in sensitive healthcare topics.

Findings

Identified biases in abortion-related video recommendations

Demonstrated effectiveness of the sock puppet auditing approach

Highlighted potential misinformation in YouTube's recommendations

Abstract

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