Algorithmic Pathways to Mental Health Content: How YouTube's Recommendation System Shapes Adolescent Exposure Patterns

This project investigates how YouTube's recommendation algorithm shapes what adolescents encounter when searching for mental health content. Using a mixed-methods approach combining algorithmic walkthroughs (qualitative) with YouTube Data API analysis (quantitative), we identify systematic patterns in how the platform routes users toward or away from professional mental health resources.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-19
DOI
https://doi.org/10.5281/zenodo.20278934
Primary Topic
Mental Health via Writing
Type
preprint
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preprint

Algorithmic Pathways to Mental Health Content: How YouTube's Recommendation System Shapes Adolescent Exposure Patterns

Bikash Khadka
Zenodo (CERN European Organization for Nuclear Research)
Mental Health via Writing
preprint

Algorithmic Pathways to Mental Health Content: How YouTube's Recommendation System Shapes Adolescent Exposure Patterns

Bikash Khadka
preprint en

Abstract

This project investigates how YouTube's recommendation algorithm shapes what adolescents encounter when searching for mental health content. Using a mixed-methods approach combining algorithmic walkthroughs (qualitative) with YouTube Data API analysis (quantitative), we identify systematic patterns in how the platform routes users toward or away from professional mental health resources.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Mental Health via Writing
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Algorithmic Pathways to Mental Health Content: How YouTube's Recommendation System Shapes Adolescent Exposure Patterns — Bikash Khadka · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS