We, the Arbiters of Truth, are Working Really Really Hard to Understand Those Stupid Lying Climate Denier Liars
Sigh, another in a long line of “trying to understand” the motivations and reasoning for people who disagree with them, but in reality are likely more informed than them.
I don’t have much to say about this ugliness, but I’ll let their writing speak for itself.
Abstract
Using data from Twitter (now X), this study deploys artificial intelligence (AI) and network analysis to map and profile climate change denialism across the United States. We estimate that 14.8% of Americans do not believe in climate change. This denialism is highest in the central and southern U.S. However, it also persists in clusters within states (e.g., California) where belief in climate change is high. Political affiliation has the strongest correlation, followed by level of education, COVID-19 vaccination rates, carbon intensity of the regional economy, and income. The analysis reveals how a coordinated social media network uses periodic events, such as cold weather and climate conferences, to sow disbelief about climate change and science, in general. Donald Trump was the strongest influencer in this network, followed by conservative media outlets and right-wing activists. As a form of knowledge vulnerability, climate denialism renders communities unprepared to take steps to increase resilience. As with other forms of misinformation, social media companies (e.g., X, Facebook, YouTube, TikTok) should flag accounts that spread falsehoods about climate change and collaborate on targeted educational campaigns.
Introduction
Climate change denialism persists in the United States, with estimates ranging from 12% to 26% of the U.S. population1,2. It is more pronounced in some states and regions3. Reasons for this denialism are multifaceted: Political affiliation and ideology, income, education, and exposure to extreme weather events are all important factors4,5,6. Denialism is more prevalent where local economies are highly dependent on fossil fuels7, in rural communities, and in populations where mistrust in science is pronounced8,9. Social media reaches millions of users, providing a key mechanism for influencers to spread misinformation10. The ability of social media to influence and harden attitudes was apparent in the response to COVID-19 vaccines11.
Understanding how and why climate change opinion varies geographically and documenting it at an actionable scale is crucial for communication campaigns, outreach, and other interventions12,13. Most estimates of the extent and geographic configuration of climate change denialism rely primarily on national surveys, with the Yale Climate Opinion Survey being the only dataset that provides estimates at the state and county levels for the entire U.S.3. These survey efforts, however, are time-intensive and expensive and are therefore destined to cover short time spans and, often, limited geographic extent. The Yale Survey combines data from more than 2500 national surveys and uses multinomial regression modeling to downscale estimates to subnational levels. Independent representative surveys conducted in states and metropolitan areas validate the predictions from the Yale Survey models3.
Mining social media data (e.g., Facebook, YouTube, and X, formerly Twitter) is a tantalizing alternative to survey-based approaches14,15. X is a social media platform with an extensive data repository. By adjusting for the skew toward certain demographic groups in users, data from this platform is useful for estimating public views on an array of topics, such as politics, social issues, and COVID-19 vaccination rates16,17. Data from Twitter has also been used in predictive modeling of election outcomes18. Account holders can misuse it to oppose scientific knowledge and spread misinformation19.
This study used Twitter data (2017–2019) to: (i) estimate the prevalence of climate change denialism at the state and county levels; (ii) identify typical profiles of climate change deniers; (iii) understand how social media promulgates climate change denialism through key influencers; and (iv) determine how world events are leveraged to promulgate attitudes about climate change.
We used a Deep Learning text recognition model to classify 7.4 million geocoded tweets containing keywords related to climate change. Posted by 1.3 million unique users in the U.S., these tweets were collected between September 2017 and May 2019 (see Online Methods S1). We classified these tweets about climate change into ‘for’ (belief) and ‘against’ (denial). Our analysis resulted in a profile of climate change deniers at the county level, provided insight into the networks of social media figures influential in promoting climate change denial, and generated insight into how these influencers use current events to foster this denial.
After confirming the validity of using social media data instead of information collected through surveys to capture public opinion on climate change at policy-relevant geographical scales, we found that denialism clusters in particular regions (and counties) of the country and amongst certain socio-demographic groups. Our analysis reveals how politicians, media figures, and conservative activists promulgated misinformation in the Twittersphere. It maps out how denialists and climate change believers have formed mostly separate Twitter communities, creating echo chambers. Such information provides a basis for developing strategies to counter this knowledge vulnerability and reduce the spread of mis- or disinformation by targeting the communities most at risk of not adopting measaures to increase resilience to the effects of climate change.
Results
Where in the U.S. is climate change denial prevalent?
Our study found that 14.8% of Americans deny that climate change is real (Fig. 1A), a percentage consistent with previous national studies (Fig. S4). Using geolocation information, we determined that denialism is highest in the Central part of the U.S. and in the South, with more than 20% of the populations of OK, MS, AL, and ND consisting of deniers. Along the West and East Coasts and New England, belief in climate change is highest. However, climate change denial varies substantially within states, often clustering in geographic swaths across multiple counties (Fig. 1B). For example, in Shasta County, California climate change denial is as high as 52%; yet overall less than 12% of the population of California does not believe in climate change. Similarly, the average percentage of deniers is 21% in Texas, but at the county-level this ranges from 13% in Travis County to 67% in Hockley County.
https://www.nature.com/articles/s41598-023-50591-6
The full study can be found here.