arbiter
JournalsAccount

Reducing misinformation on social media: an experimental evaluation of two policy interventions

Lucas Rentschler & Zeeshan Samad

Experimental Economics2026https://doi.org/10.1017/eec.2026.10040article
AJG 3ABDC A*
Weight
0.50

Abstract

The prevalence of false and misleading news has become an issue of great concern in recent years. Academic researchers, policymakers, and social media firms all continue to seek effective solutions to reduce the sharing of misinformation. In this paper, we evaluate the effectiveness of two policies in particular: competition among media firms and fact-checking of published news articles by independent organizations. We first develop a theoretical model that predicts the effect of each policy and then conduct a behavioral experiment to test those predictions. Our experimental findings indicate that media competition is most effective at nipping misinformation in the bud because media firms spend significantly more resources on improving the accuracy of their news when readers obtain news from multiple sources. We also find that fact-checking improves the overall quality of news available to viewers; however, it does not incentivize firms to improve the accuracy of their own news articles. Last, our results from an interaction treatment suggest that under competition, fact-checking adversely affects firms’ investment in news accuracy.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1017/eec.2026.10040

Or copy a formatted citation

@article{lucas2026,
  title        = {{Reducing misinformation on social media: an experimental evaluation of two policy interventions}},
  author       = {Lucas Rentschler & Zeeshan Samad},
  journal      = {Experimental Economics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1017/eec.2026.10040},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Reducing misinformation on social media: an experimental evaluation of two policy interventions

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.