Linking a conspiratorial counterpublic to a foundational event.
Climate change is one of the most polarized topics in American public life, and has become deeply entwined with cultural identity and partisan boundaries. Conventional explanations of climate skepticism often portray it as a failure of science communication, but this fails to account for the deeper emotional and social dynamics that fuel the adoption and dissemination of misinformation, and leaves many open questions. Why does climate skepticism persist even as scientific evidence accumulates? Why do online communities of climate denial seem to grow rather than shrink in the age of information abundance?
This research investigates climate skepticism not as a simple failure to understand science, but as a culturally embedded worldview with its own internal logic, emotional dynamics, and networked infrastructure. Drawing on cognitive anthropology and computational social science, it maps how anti-environmentalism evolved from a coherent elite conservative ideological project into a diffuse, conspiratorial digital movement.
This work draws on a large, multi-source corpus spanning over a decade of climate discourse across media contexts that differ in their institutional constraints, audiences, and norms:
The textual corpora include conservative think tank publications (e.g., The Heartland Institute), cable news transcripts (Fox News, CNN, MSNBC), climate skeptical blogs (e.g., Watts Up With That), and millions of climate-related tweets. Four complementary computational methods are applied across these data:
BERTopic models identify thematic clusters in each corpus, revealing how climate change is framed differently across institutional contexts.
Word2Vec models trained per-source capture the semantic neighborhoods of climate change—what concepts are nearby in each discourse.
Co-retweet networks trace how climate skeptic communities form, polarize, and persist on Twitter from 2008 to 2020.
A fine-tuned RoBERTa model automatically detects and categorizes specific types of climate denial in tweets.
The analysis integrates four computational approaches, each capturing a different dimension of the discourse:
BERTopic uses embedding models to cluster documents by semantic similarity, surfacing the thematic structure of each corpus by identifying what topics dominate and how they differ across sources. Word2Vec builds up implicit associations between word or phrase-level concepts from patterns of co-occurrence, mapping the semantic neighborhood of key concepts like “climate change” in each text dataset. This algorithmic approach operationalizes cultural schema theory: a theory in cognitive anthropology that meaning is not only found in overt discussion, but also can be identified through the web of connotations that core concepts automatically activate. Co-retweet network analysis identifies communities of shared attention on Twitter, revealing how climate change discourse on the platform is socially organized and how these discourse communities evolve over time. Fine-tuned RoBERTa classification detects and categorizes specific types of climate denial at scale, sorting hundreds of thousands of tweets into a taxonomy of claims to measure what kinds of skepticism dominate and how their prevalence shifts over time.
No single method tells the full story. Topic models reveal what is being discussed; embeddings reveal how concepts are implicitly related; networks reveal who is connected and how communities form; and classification reveals which specific claims circulate and at what volume. Together, they construct a multi-layered portrait of an ecosystem of shared meanings that no single approach could produce alone.
1. Different media, different skepticisms. Conservative think tanks and Fox News frame climate change policy as an antagonist to free-market flourishing; they focus their effort on opposing regulations, carbon taxes, and international agreements. But climate skeptical blogs represent a discursive shift: their language is more conspiratorial, more emotionally charged, and engages in a view of general hostility towards scientific authority while promoting a wide-ranging skepticism.
2. The semantic world of climate skepticism is distinctive. Word embedding analysis reveals that in climate skeptical sources, "climate change" lives in a semantic neighborhood dominated by terms of deception, alarmism, and institutional corruption—a markedly different conceptual landscape than mainstream or liberal media, where climate change clusters with scientific and policy vocabulary.
3. The "Climategate" pseudo-scandal crystallized a counterpublic. The November 2009 leak of climate scientists' emails catalyzed the formation of a durable, affectively bound online community. Network analysis of Twitter co-retweet patterns shows the climate skeptic network expanding from 17 core accounts before Climategate to 500 during the event, with community structure persisting long afterward.
4. The Twitter counterpublic is stable and polarized. Co-retweet networks from 2010 to 2020 reveal a remarkably consistent bifurcated structure: climate skeptics and climate advocates occupy separate, densely connected clusters with few bridges between them. Network transitivity remains below 0.5, confirming that audiences boosting skeptic content and those boosting scientific content are structurally partitioned.
5. Climate denial is ritualized and event-driven. Discussion in the skeptic counterpublic follows a pattern of stochastic bursts—rapid mobilization in response to climate events, IPCC reports, or political actions—followed by quieter periods. These bursts are powered by anger and disgust (confirmed by emotion classification), and function as collective rituals that reaffirm group identity and reinforce conspiratorial narratives.
The visualization below shows how the climate skeptic co-retweet network on Twitter evolved around the Climategate scandal. Each node is a Twitter account; connections indicate shared audiences (users who retweeted both). Colors represent detected communities. Click "Yearly Evolution" to see the network grow from 2009 to 2019.
Most computational studies of climate skepticism analyze a single platform, apply a single method, or capture a narrow window of time. This study does something structurally different: it traces climate skepticism across four institutional contexts—think tanks, cable news, blogs, and social media—using four complementary computational methods on a unified twelve-year timeline.
This matters because climate skepticism is not a single phenomenon. The policy-focused opposition of a Heritage Foundation white paper, the conspiratorial engagement in the comments section of a Watts Up With That blog post, and the affective one-liners of a viral tweet are all “climate denial,” but they operate through different logics, in different institutional settings, for different audiences. By placing all four contexts on the same analytical timeline, this research can show how ideas originate in elite institutional settings, migrate through media intermediaries, and take on a life of their own as bedrock ideologies for durable grassroots communities online—a pipeline that is invisible from within any single platform.
This research has three implications for understanding and responding to climate misinformation:
Beyond "information deficit." Climate skepticism cannot be resolved simply by providing better scientific information. The movement is sustained by affective bonds, identity performances, and ritualized collective action that operate independently of factual claims. Interventions must reckon with the emotional and communal dimensions of climate denial.
Platform structure matters. Social media platforms provide the infrastructure for rapid counterpublic formation and maintenance. The stability of the skeptic network over a decade—with the same core accounts maintaining centrality—suggests that platform-level interventions, not just content-level fact-checking, are necessary.
The conspiratorial drift. The evolution from structured anti-environmentalist ideology to diffuse online conspiracism represents a broader pattern in American public life. Climate skepticism's trajectory from policy disagreement to wholesale rejection of scientific authority offers a template for understanding similar dynamics in public health, election integrity, and beyond.
This brief draws on ongoing research by J. Connor Balch (Just Horizons Alliance), currently being prepared for peer-reviewed publication. The underlying study was developed with advisory input from Wesley J. Wildman (Computational Social Science), Neha Gondal (Social Network Analysis), and Christopher Wells (Emerging Media Studies) at Boston University. The climate denial claim classification builds on the CARDS framework (Computer-Assisted Recognition of Climate Change Denial and Skepticism) by Travis G. Coan, Constantine Boussalis, John Cook, and Mirjam O. Nanko.