Evidence map›Paper›PMID 37433974›Full record

ArticleBehavior research methods2024

The (Mis)Information Game: A social media simulator.

Lucy H Butler, Padraig Lamont, Dean Law Yim Wan, Toby Prike, Mehwish Nasim, Bradley Walker, Nicolas Fay, Ullrich K H Ecker

Abstract read
In one paragraph

Article in Behavior research methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Susceptibility to online misinformation: A systematic meta-analysis of demographic and psychological factors.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Pooled it
  3. Psychological inoculation against climate doom.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  4. Article
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  6. Review
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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

8 authors.

Lucy H ButlerSchool of Psychological Science, University of Western Australia, Crawley, WA, Australia.
Padraig LamontSchool of Engineering, University of Western Australia, Crawley, WA, Australia.
Dean Law Yim WanSchool of Physics, Mathematics and Computing, University of Western Australia, Crawley, WA, Australia.
Toby PrikeSchool of Psychological Science, University of Western Australia, Crawley, WA, Australia.
Mehwish NasimSchool of Physics, Mathematics and Computing, University of Western Australia, Crawley, WA, Australia.
Bradley WalkerSchool of Psychological Science, University of Western Australia, Crawley, WA, Australia.
Nicolas FaySchool of Psychological Science, University of Western Australia, Crawley, WA, Australia.
Ullrich K H EckerSchool of Psychological Science, University of Western Australia, Crawley, WA, Australia. ullrich.ecker@uwa.edu.au.ORCID 0000-0003-4743-313X

Funding

Australian Research Council FT190100708Office of National Intelligence and Australian Research Council NI210100224
6 · The paper itself

Abstract

Given the potential negative impact reliance on misinformation can have, substantial effort has gone into understanding the factors that influence misinformation belief and propagation. However, despite the rise of social media often being cited as a fundamental driver of misinformation exposure and false beliefs, how people process misinformation on social media platforms has been under-investigated. This is partially due to a lack of adaptable and ecologically valid social media testing paradigms, resulting in an over-reliance on survey software and questionnaire-based measures. To provide researchers with a flexible tool to investigate the processing and sharing of misinformation on social media, this paper presents The Misinformation Game-an easily adaptable, open-source online testing platform that simulates key characteristics of social media. Researchers can customize posts (e.g., headlines, images), source information (e.g., handles, avatars, credibility), and engagement information (e.g., a post's number of likes and dislikes). The platform allows a range of response options for participants (like, share, dislike, flag) and supports comments. The simulator can also present posts on individual pages or in a scrollable feed, and can provide customized dynamic feedback to participants via changes to their follower count and credibility score, based on how they interact with each post. Notably, no specific programming skills are required to create studies using the simulator. Here, we outline the key features of the simulator and provide a non-technical guide for use by researchers. We also present results from two validation studies. All the source code and instructions are freely available online at https://misinfogame.com .

Indexed as

Social MediaAvatarCommunicationEmotionsHumansResearch PersonnelSoftwareExperimental control softwareMisinformationSocial media

Identifiers

PMID37433974
PMCPMC10991066

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.