Evidence map›Paper›PMID 40532004›Full record

ArticleScience advances2025

How media competition fuels the spread of misinformation.

Arash Amini, Yigit Ege Bayiz, Eun-Ju Lee, Zeynep Somer-Topcu, Radu Marculescu, Ufuk Topcu

Abstract read
In one paragraph

Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Arash AminiOden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, USA.ORCID 0000-0002-3713-8674
Yigit Ege BayizDepartment of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA.ORCID 0000-0002-0700-2768
Eun-Ju LeeDepartment of Communication, Seoul National University, Seoul, South Korea.ORCID 0000-0002-8752-248X
Zeynep Somer-TopcuDepartment of Government, The University of Texas at Austin, Austin, TX, USA.ORCID 0000-0001-7499-5571
Radu MarculescuDepartment of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA.ORCID 0000-0003-1826-7646
Ufuk TopcuOden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Competition among news sources over public opinion can incentivize them to resort to misinformation. Sharing misinformation may lead to a short-term gain in audience engagement but ultimately damages the credibility of the source, resulting in a loss of audience. To understand the rationale behind news sources sharing misinformation, we model the competition between sources as a zero-sum sequential game, where news sources decide whether to share factual information or misinformation. Each source influences individuals based on their credibility, the veracity of the article, and the individual's characteristics. We analyze this game through the concept of quantal response equilibrium, which accounts for the bounded rationality of human decision-making. The analysis shows that the resulting equilibria reproduce the credibility-opinion distribution of real-world news sources, with hyperpartisan sources spreading the majority of misinformation. Our findings provide insights for policymakers to mitigate the spread of misinformation and promote a more factual information landscape.

Indexed as

CommunicationCommunications MediaInformation DisseminationMass MediaDecision MakingHumansPublic Opinion

Identifiers

PMID40532004
PMCPMC12175900

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.