Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 441

The DOI matches its Crossref record; 112 of the 112 references it cites were found in a registry or an index.

Online misinformation about climate change

Open access
Treen, Kathie M. d'I., Williams, Hywel T. P., O'Neill, Saffron J.·2020·WIREs Climate Change
DOI 10.1002/wcc.665
Open this paper in CoChat — free account

Abstract

Policymakers, scholars, and practitioners have all called attention to the issue of misinformation in the climate change debate. But what is climate change misinformation, who is involved, how does it spread, why does it matter, and what can be done about it? Climate change misinformation is closely linked to climate change skepticism, denial, and contrarianism. A network of actors are involved in financing, producing, and amplifying misinformation. Once in the public domain, characteristics of online social networks, such as homophily, polarization, and echo chambers—characteristics also found in climate change debate—provide fertile ground for misinformation to spread. Underlying belief systems and social norms, as well as psychological heuristics such as confirmation bias, are further factors which contribute to the spread of misinformation. A variety of ways to understand and address misinformation, from a diversity of disciplines, are discussed. These include educational, technological, regulatory, and psychological‐based approaches. No single approach addresses all concerns about misinformation, and all have limitations, necessitating an interdisciplinary approach to tackle this multifaceted issue. Key research gaps include understanding the diffusion of climate change misinformation on social media, and examining whether misinformation extends to climate alarmism, as well as climate denial. This article explores the concepts of misinformation and disinformation and defines disinformation to be a subset of misinformation. A diversity of disciplinary and interdisciplinary literature is reviewed to fully interrogate the concept of misinformation—and within this, disinformation—particularly as it pertains to climate change. This article is categorized under: Perceptions, Behavior, and Communication of Climate Change > Communication

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/wcc.665

Cites

112 of 112 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

1 retracted

Research works printed but not linked: 15

  1. Amoruso M., 2017, Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS '17), May 8–12, Sao Paulo, Brazil, 1323
  2. Cambridge Dictionary. (2019). Misinformation. Retrieved fromhttps://dictionary.cambridge.org/dictionary/english/misinformation.
  3. Constitution Center. (2019). Amendment I: Freedom of Religion Speech Press Assembly and Petition. Retrieved fromhttps://constitutioncenter.org/interactive-constitution/amendments/amendment-i
  4. Epstein Z.Mosleh M. Arechar A. Pennycook G. &Rand D. G..Primed for Accuracy: A Cognitive Approach to Fighting Misinformation on Twitter.In: 5th Annual International Conference on Computational Social Science (IC2S2) July 17–202019. Amsterdam Netherlands: University of Amsterdam.
  5. Guess A., 2018, Does counter‐attitudinal information cause backlash?, Results from Three Large Survey Experiments, British Journal of Political Science, 2018, 1
  6. GuptaA. Lamba H. Kumaraguru P. &Joshi A.(2013a) Analyzing and measuring the spread of fake content on twitter during high impact events. IEEE APWG eCrime Research Summit (eCRS) 2013.
  7. Halliman R., 2017, Restructuring of the global economy: The role of climate alarmism, The Business and Management Review, 9, 321
  8. 10.1038/nclimate1547 · DOI · Paper page
  9. KarlovaN. A. &FisherK. E.. (2012).“Plz RT”: A social diffusion model of misinformation and disinformation for understanding human behaviour. Proceedings of the ISIC2012 Tokyo.
  10. 10.1007/s11191-013-9588-3 · doi:10.1007/s11191-013-9588-3
  11. Oxford Dictionaries. (2019). Misinformation. Retrieved fromhttps://en.oxforddictionaries.com/definition/misinformation.
  12. 10.5408/12-304.1 · doi:10.5408/12-304.1
  13. Tompros L. W., 2017, The Constitutionality of criminalizing false speech made on social networking sites in a post‐Alvarez, social media‐obsessed world, Harvard Journal of Law & Technology, 31, 65
  14. Webb H., 2016, Digital Wildfires: Propagation, Verification, Regulation, and Responsible Innovation, ACM Transactions on Information Systems—Special Issue on Trust and Veracity of Information in Social Media, 34, 15
  15. Wu L., 2016, Mining misinformation in social media, in big data in complex and Social Networks

Cited by

See all 441

Metadata

Authors
Treen, K. M. D., Williams, H. T. P., & O'Neill, S. J.
Venue
WIREs Climate Change
Publisher
Wiley
Published
2020-06-18
Volume
11
Issue
5
ISSN
  • 1757-7780 (ISSN-L)
  • 1757-7799
DOI
10.1002/wcc.665
OpenAlex
W3036619158
Cited by
441
References
112
FWCI
52.55
Type
journal article
Language
en
Open access
hybrid
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
  • Economic and Social Research Council (ES/P011489/1)
  • University of Exeter

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.