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The Study

Comparing the Willingness to Share for Human-generated vs. AI-generated Fake News

In simple terms

This study asked people what they thought about different fake news stories and whether they’d share them. It found patterns—like people sharing both kinds equally—but it didn’t change anything or control who saw what. So it can’t prove one thing causes another, only that things are linked.

44%

Analysis score

44/ 44

Maximum 44 for a cross-sectional study.

Where the score came from

Reporting0
Methodology44
Publication100
Statistical100
Study type (basis of the score)
Cross-Sectional Study
Level 4 - Case series
What’s the bottom line?

People think AI-made fake news is less true than human-made fake news, but they still share both just as much.

Where does this study sit?

Reviews of RCTs (Meta-analyses)

Max 100

Randomized Trials

Max 90

Reviews of Cohort Studies

Max 85

Cohort Studies

Max 72

Reviews of Case-Control Studies

Max 63

Case-Control Studies

Max 58

Cross-Sectional & Case Series

Max 50

Expert Opinion

Max 5
StrongerWeaker
Cross-Sectional & Case Series
Level 4
44

44 / 100

Quality score

Snapshots of a population at a single point in time, or descriptions of small groups. Can identify correlations and prevalence, but cannot determine cause and effect.

Cannot establish causation

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Key takeaways

Summary

Based on the study abstract and findings.

  1. 1Yes — this means people share fake news not because they believe it, but because of emotions, habits, or social pressure.
  2. 2AI fake news was rated less accurate, but 988 adults shared AI and human fake news equally.

Score breakdown, methodology, conflicts of interest, evidence analysis & raw study data

Publication

Journal

Proceedings of the ACM on Human-Computer Interaction

Year

2024

Authors

Amirsiavosh Bashardoust, S. Feuerriegel, Y. Shrestha

Open Access
39 citations
Analysis v5
Fit Body Science verdict — we translate health studies into clear verdicts backed by peer-reviewed research.

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