Evidence map›Paper›PMID 38463039›Full record

ArticlePNAS nexus2024

Containing misinformation: Modeling spatial games of fake news.

Matthew I Jones, Scott D Pauls, Feng Fu

Abstract read
In one paragraph

Article in PNAS nexus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. On the optimal integration of intelligent agents into network systems to steer cooperation.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. 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

3 authors.

Matthew I JonesSociology Department, Yale University, New Haven, CT 06511, USA.ORCID https://orcid.org/0000-0002-9972-6367
Scott D PaulsMathematics Department, Dartmouth College, Hanover, NH 03755, USA.ORCID https://orcid.org/0000-0002-0281-2868
Feng FuMathematics Department, Dartmouth College, Hanover, NH 03755, USA.ORCID https://orcid.org/0000-0001-8252-1990

Funding

Zhao - Proj 2P20GM130454 · NIGMS · DARTMOUTH COLLEGE · PI Chengxiang Qiu · 2019 to 2026
$27.2M
NIGMS NIH HHS P20 GM130454
6 · The paper itself

Abstract

The spread of fake news on social media is a pressing issue. Here, we develop a mathematical model on social networks in which news sharing is modeled as a coordination game. We use this model to study the effect of adding designated individuals who sanction fake news sharers (representing, for example, correction of false claims or public shaming of those who share such claims). By simulating our model on synthetic square lattices and small-world networks, we demonstrate that social network structure allows fake news spreaders to form echo chambers and more than doubles fake news' resistance to distributed sanctioning efforts. We confirm our results are robust to a wide range of coordination and sanctioning payoff parameters as well as initial conditions. Using a Twitter network dataset, we show that sanctioners can help contain fake news when placed strategically. Furthermore, we analytically determine the conditions required for peer sanctioning to be effective, including prevalence and enforcement levels. Our findings have implications for developing mitigation strategies to control misinformation and preserve the integrity of public discourse.

Indexed as

echo chambersfact-checkingonline misinformationsocial networksspatial game theory

Identifiers

PMID38463039
PMCPMC10924450

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.