Short Note: Climate Misinformation and Trump
Methods Used By Climate Deniers are Tailored to Algorithms
If you have noticed how some climate deniers like Trump and his ilk have framed the climate debate, there is a disparagement of anyone who claims climate change is real. According to Anton and Petter Törnberg, there is a methodology these deniers utilize that is meant to make climate realists appear weak and feminized. There is an actual algorithm that promotes the toxic masculinity behind Trump’s methods. These algorithms are utilized throughout the internet. Törnberg and Törnberg realized through the use of sophisticated artificial intelligence modeling tools that all information is increasingly visual. Moreover, the portrayals of climate change by both sides are becoming more visual by reducing the issues to sound- and visual-bytes. Trump’s disdain for windmills and his calling climate change a hoax is meant to evoke a toxic masculinity in his base and beyond. The notions behind — DRILL- BABY- DRILL are also meant to evoke a time when men made women walk several steps behind them. All in the name of toxic masculinity!
However, Törnberg and Törnberg further showed that the visual nature behind climate denial is an insidious lie. By disparaging climate change as a hoax, climate deniers have gained some ground through non-factual methods. They have utilized aesthetics as a means to their end. How many times have we heard Trump use the word ‘Beautiful’ regarding what he favors? Everything for this toxic asshole has to be Big and Beautiful; it paints an evil aesthetic to all he promotes.
Törnberg and Törnberg conclude their study with warnings to the world community. If we are to win the climate war, the battlefield has shifted. Moreover, it is more than using the facts against the lies. It will be a war of propaganda. The lies of Trump and his ilk demand that we go into the trenches and battle his propaganda with an equal and effective strategy. However, that has as yet to take real shape. It will be a multi-pronged attack on lies and their ability to affect emotions.
Egger, Roman, and Joanne Yu. “A topic modeling comparison between lda, nmf, top2vec, and bertopic to demystify twitter posts.” Frontiers in sociology 7 (2022): 886498.
Grootendorst, Maarten. “BERTopic: Neural topic modeling with a class-based TF-IDF procedure.” arXiv preprint arXiv:2203.05794 (2022).
Törnberg, Anton, and Petter Törnberg. “The aesthetics of climate misinformation: computational multimodal framing analysis with BERTopic and CLIP.” Environmental Politics (2025): 1-24.
Great post, John.