Evidence map›Paper›PMID 39532907›Full record

ArticleScientific reports2024

A technocognitive approach to detecting fallacies in climate misinformation.

Francisco Zanartu, John Cook, Markus Wagner, Julian García

Abstract read
In one paragraph

Article in Scientific reports, 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. Testing the impact of fallacies and contrarian claims in climate change misinformation.British journal of psychology (London, England : 1953) · 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

4 authors.

Francisco ZanartuUniversity of Melbourne, Parkville, VIC, Australia.
John CookMelbourne Centre for Behaviour Change, University of Melbourne, Parkville, VIC, Australia. jocook@unimelb.edu.au.
Markus WagnerDepartment of Data Science & AI, Monash University, Clayton, VIC, 3800, Australia.
Julian GarcíaDepartment of Data Science & AI, Monash University, Clayton, VIC, 3800, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Misinformation about climate change is a complex societal issue that requires holistic, interdisciplinary solutions at the intersection between technology and psychology. One proposed solution is a "technocognitive" approach, involving the synthesis of psychological and computer science research. Psychological research has identified that interventions that counter misinformation require both fact-based (e.g., factual explanations) and technique-based (e.g., explanations of misleading techniques and logical fallacies) content. However, little progress has been made on documenting and detecting fallacies in climate misinformation. In this study, we apply a previously developed critical thinking methodology for deconstructing climate misinformation in order to develop a dataset mapping examples of climate misinformation to reasoning fallacies. This dataset is used to train a model to detect fallacies in climate misinformation. We evaluate the model's performance using the

Indexed as

Climate ChangeCommunicationHumansClimate changeFallacy detectionMisinformationTechnocognitive approach

Identifiers

PMID39532907
PMCPMC11557567

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.