Climate-denying rumor propagation in a coupled socio-climate model: Impact on average global temperature

Individual attitudes vastly affect the transformations we are experiencing and are vital in mitigating or intensifying climate change. A socio-climate model by coupling a model of rumor dynamics in heterogeneous networks to a simple Earth System model is developed, in order to analyze how rumors about climate change impact individuals' opinions when they may choose to either believe or reject the rumors they come across over time. Our model assumes that when individuals experience an increase in the global temperature, they tend to not believe the rumors they come across. The rumor rejectors limit their CO2 emissions to reduce global temperature. Our numerical analysis indicates that, over time, the temperature anomaly becomes less affected by the variations in rumor propagation parameters, and having larger groups (having more members) is more efficient in reducing temperature (by efficiently propagating rumors) than having numerous small groups. It is observed that decreasing the number of individual connections does not reduce the size of the rejector population when there are large numbers of messages sent through groups. Mitigation strategies considered by the rejectors are highly influential. The absence of mitigative behavior in rejectors can cause an increase in the global average temperature by 0.5°C. Our model indicates that rumor propagation in groups has the upper hand in controlling temperature change, compared to individual climate-denying propagation.

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Publication Details

Journal
PLoS ONE
Published
2025-01-16
DOI
https://doi.org/10.1371/journal.pone.0317338
Citations
1
Primary Topic
Climate Change Communication and Perception
Type
article
Field-Weighted Citation Impact
4.20

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article

Climate-denying rumor propagation in a coupled socio-climate model: Impact on average global temperature

Athira Satheesh Kumar, Madhur Anand, Chris T. Bauch
1 citations
PLoS ONE
Climate Change Communication and Perception
4.20
article

Climate-denying rumor propagation in a coupled socio-climate model: Impact on average global temperature

Athira Satheesh Kumar, Madhur Anand, Chris T. Bauch
article en
1 citations

Abstract

Individual attitudes vastly affect the transformations we are experiencing and are vital in mitigating or intensifying climate change. A socio-climate model by coupling a model of rumor dynamics in heterogeneous networks to a simple Earth System model is developed, in order to analyze how rumors about climate change impact individuals' opinions when they may choose to either believe or reject the rumors they come across over time. Our model assumes that when individuals experience an increase in the global temperature, they tend to not believe the rumors they come across. The rumor rejectors limit their CO2 emissions to reduce global temperature. Our numerical analysis indicates that, over time, the temperature anomaly becomes less affected by the variations in rumor propagation parameters, and having larger groups (having more members) is more efficient in reducing temperature (by efficiently propagating rumors) than having numerous small groups. It is observed that decreasing the number of individual connections does not reduce the size of the rejector population when there are large numbers of messages sent through groups. Mitigation strategies considered by the rejectors are highly influential. The absence of mitigative behavior in rejectors can cause an increase in the global average temperature by 0.5°C. Our model indicates that rumor propagation in groups has the upper hand in controlling temperature change, compared to individual climate-denying propagation.

PLoS ONEVol. 20(1)
University of Waterloo (CA), University of Guelph (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 10%
Climate Change Communication and Perception
4.20
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Climate-denying rumor propagation in a coupled socio-climate model: Impact on average global temperature — Athira Satheesh Kumar, Madhur Anand, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS