Finding climate misinformation
Now, an international team of researchers has delved into a related phenomenon – climate misinformation – and found that attacks on the reliability of climate science is the most common form of misinformation, and that misinformation targeting climate solutions is on the rise.
Monash University research fellow Dr John Cook and colleagues from the University of Exeter, UK, and Trinity College Dublin, Ireland, trained a machine-learning model to automatically detect and categorise climate misinformation.
Then they reviewed 255,449 documents from 20 prominent conservative think-tank (CTT) websites and 33 climate change denial blogs to build a two-decade history of climate misinformation and find common topics, themes, peaks, and changes over time.
It’s the largest content analysis to date on climate misinformation, with findings published today in in the Nature journal Scientific Reports.
“Our study found claims used by such think-tanks and blogs focus on attacking the integrity of climate science and scientists, and, increasingly, challenged climate policy and renewable energy,” Cook says.
“Organised climate change contrarianism has played a significant role in the spread of misinformation and the delay to meaningful action to mitigate climate change.”
As a result of their analysis, the researchers developed a taxonomy to categorise claims about climate science and policy used by opponents of climate action.
They found the five major claims about climate change used by CTTs and blogs were:
- It’s not happening
- It’s not us
- It’s not bad
- Solutions won’t work
- Climate science/scientists are unreliable
The researchers say climate misinformation leads to a number of negative outcomes, including reduced climate literacy, public polarisation, cancelling out accurate information and influencing how scientists engage with the public.
“The problem of misinformation is so widespread, practical solutions need to be scalable to match the size of the problem,” Cook says.
“Misinformation spreads so quickly across social networks, we need to be able to identify misinformation claims instantly in order to respond quickly. Our research provides a tool to achieve this.”
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