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Evidence record 5180 · automatically gathered

Gender Bias in YouTube Exposure: Allocative and Structural Inequalities in Political Information Environments

Recommendation algorithms have become the dominant mechanism for information distribution on digital platforms, profoundly shaping personalized information consumption environments. However, gender bias, as a significant form of algorithmic discrimination, may cause users to experience unequal exposure within different political information environments. Taking YouTube as a case, we conduct a controlled social-bot field experiment, where male-coded and female-coded profiles are constructed. We t

Record details

Published: 30 April 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Environment
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (30 April 2026), “Gender Bias in YouTube Exposure: Allocative and Structural Inequalities in Political Information Environments,” evidence record 5180, https://ethics.ai/record/5180 (originally published by arXiv).

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