Evidence map›Paper›PMID 37647396›Full record

ArticleScience advances2023

Subscriptions and external links help drive resentful users to alternative and extremist YouTube channels.

Annie Y Chen, Brendan Nyhan, Jason Reifler, Ronald E Robertson, Christo Wilson

Abstract read
In one paragraph

Article in Science advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Short-term exposure to filter-bubble recommendation systems has limited polarization effects: Naturalistic experiments on YouTube.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  4. Article
  5. Article
  6. Challenges in Understanding Human-Algorithm Entanglement During Online Information Consumption.Perspectives on psychological science : a journal of the Association for Psychological Science · 2024
    Article
  7. Article
  8. Review
  9. Causally estimating the effect of YouTube's recommender system using counterfactual bots.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  10. Review
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Annie Y ChenCUNY Institute for State & Local Governance, 10 East 34th St., New York, NY 10016, USA.ORCID 0000-0002-3730-162X
Brendan NyhanDartmouth College, 6108 Hinman, Hanover, NH 03755, USA.ORCID 0000-0001-7497-1799
Jason ReiflerUniversity of Exeter, Stocker Road, Exeter EX4 4PY, UK.ORCID 0000-0002-1116-7346
Ronald E RobertsonStanford Internet Observatory, Stanford University, 616 Jane Stanford Way, Stanford, CA 94305, USA.ORCID 0000-0003-4525-5050
Christo WilsonNortheastern University, 360 Huntington Ave, Boston, MA 02115, USA.ORCID 0000-0002-5268-004X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Do online platforms facilitate the consumption of potentially harmful content? Using paired behavioral and survey data provided by participants recruited from a representative sample in 2020 (

Indexed as

Social MediaAlgorithms

Identifiers

PMID37647396
PMCPMC10468121

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.