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Examining the consumption of radical content on YouTube
Open accessAbstract
Significance: Daily share of news consumption on YouTube, a social media platform with more than 2 billion monthly users, has increased in the last few years. Constructing a large dataset of users’ trajectories across the full political spectrum during 2016–2019, we identify several distinct communities of news consumers, including “far-right” and “anti-woke.” Far right is small and not increasing in size over the observation period, while anti-woke is growing, and both grow in consumption per user. We find little evidence that the YouTube recommendation algorithm is driving attention to this content. Our results indicate that trends in video-based political news consumption are determined by a complicated combination of user preferences, platform features, and the supply-and-demand dynamics of the broader web.
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“Most movement to far-right videos comes from outside the platform”
From Social Drivers and Algorithmic Mechanisms on Digital Media. (2024) · cites this paper as Hosseinmardi et al., 2021
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“far-right videos are not more likely toward the end of sessions, where algorithmic recommendations matter most (Hosseinmardi et al., 2021).”
From Social Drivers and Algorithmic Mechanisms on Digital Media. (2024) · cites this paper as Hosseinmardi et al., 2021
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Metadata
- Authors
- Hosseinmardi, H., Ghasemian, A., Clauset, A., Mobius, M., Rothschild, D. M., & Watts, D. J.
- Affiliations
- University of Pennsylvania (US)
- Harvard University (US)
- Santa Fe Institute (US)
- Microsoft Research New England, Cambridge, MA 02142;
- Microsoft Research New York City (United States) (US)
- Corresponding author
- Hosseinmardi, Homa
- Watts, Duncan J.
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2021-08-02
- Volume
- 118
- Issue
- 32
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC8364190
- OpenAlex
- W3189072387
- Cited by
- 171
- References
- 34
- Citations by year
- 2026: 24 · 2025: 20 · 2024: 39 · 2023: 55 · 2022: 28 · 2021: 5
- FWCI
- 42.30
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- OSF Preprints (OSF Preprints) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Social Sciences › Communication › Social Media and Politics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Political Science and International Relations › Populism, Right-Wing Movements
- Keywords
- YouTube, radicalization, algorithmic recommendation, political news consumption, user engagement, gateway effect, political ideology, online media consumption
- MeSH terms
- Humans, Politics, Video Recording, Social Media
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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