Testing the impact of fallacies and contrarian claims in climate change misinformation
Bibliographic Data
| ID | 21297971 |
|---|---|
| Authors | Renee Lieu (Melbourne School of Psychological Science University of Melbourne Melbourne Victoria Australia), Oliver R Hayes (Melbourne School of Psychological Science University of Melbourne Melbourne Victoria Australia), John Cook (0000-0002-3330-5180, Melbourne Centre for Behaviour Change University of Melbourne Melbourne Victoria Australia, corresponding author) |
| Year | 2025 |
| Publication date | 2025-12-29 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | British Journal of Psychology (JOURNAL) |
| Journal identifiers | ISSN: 0007-1269 • E-ISSN: 2044-8295 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/bjop.70049 |
| PMID | 41462017 |
| OpenAlex | W7117596066 |
| Language | EN |
| Citations received | 1 |
| References cited | 66 |
Climate misinformation reduces public acceptance of climate change and undermines support for mitigation policies. This study explored the impact of different types of climate misinformation, examining through content‐based and logic‐based frameworks. The content‐based framework was based on a taxonomy of contrarian claims consisting of five categories—it's not real, it's not us, it's not bad, climate solutions won't work and scientists are not reliable. The logic‐based framework examined six rhetorical techniques used in science denial arguments—misrepresentation, false equivalence, oversimplification, red herring, cherry picking and slothful induction. We experimentally tested 30 misinformation examples, crossing five content categories with six fallacies. Participants rated the perceived veracity of misinformation as well as the likelihood of interacting with it. We found no main effect of fallacy on perceived veracity or likelihood to interact but did find a main effect of content category, with the fourth category (climate solutions won't work) perceived as most veracious. We also found that content categories interacted with political ideology, replicating past research into the polarizing effect of climate misinformation. Specifically, the most polarizing categories of misinformation were those targeting climate solutions or attacking climate scientists. Our results highlight the need to prioritize combatting misinformation that targets solutions and scientists
Climate change · Contrarian · Credibility · Deception · Denial · Misinformation · Motivated reasoning · Perception · Salience (neuroscience) · Climate Change Communication and Perception · Educational Strategies and Epistemologies · Misinformation and Its Impacts
The Political Divide on Climate Change
The generalizability crisis
Sample Size Justification
The Scientific Consensus on Climate Change
Effect of outdoor temperature, heat primes and anchoring on belief in global warming
Manufactured Scientific Controversy
Paris Agreement climate proposals need a boost to keep warming well below 2 °C
How People Process Different Types of Health Misinformation
Beyond Fact-Checking
Confirmation Bias and the Persistence of Misinformation on Climate Change
Democracy, Public Policy, and Lay Assessments of Scientific Testimony
Support for climate policy and societal action are linked to perceptions about scientific agreement
Analytic thinking reduces belief in conspiracy theories
Quantifying the consensus on anthropogenic global warming in the scientific literature
Does narrative information bias individual's decision making? A systematic review
Polarized climate change beliefs
Online misinformation about climate change
Birds of a Feather Tweet Together
Seepage
Belief in conspiracy theories
Developing a Critical Response to Ad Hominem Attacks Against Climate Science
Conspiracy Theories and the Paranoid Style(s) of Mass Opinion
The entertainment value of conspiracy theories
The social consequences of conspiracism
Challenging Global Warming as a Social Problem
Inducing Resistance to Conspiracy Theory Propaganda
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |