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arxiv: 2604.24223 · v1 · submitted 2026-04-27 · 💻 cs.SI

Recognition: unknown

Mapping Emerging Climate Misinformation Playbooks in the Global South

Marcelo Sartori Locatelli, Meeyoung Cha, Pedro Dutenhefner, Pedro Loures Alzamora, Virgilio Almeida, Wagner Meira Jr., Wenchao Dong

Pith reviewed 2026-05-07 17:15 UTC · model grok-4.3

classification 💻 cs.SI
keywords climate misinformationGlobal SouthYouTubenew denialBrazilcontent analysisplatform datarenewable energy
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The pith

Climate misinformation in Brazil has shifted from denying the science to attacking proposed solutions.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper studies 226,775 climate-related YouTube videos from Brazil produced between 2019 and 2025. It separates older messages that reject the existence of climate change from newer messages that accept the science but work against renewable energy, climate policies, and environmental groups. The newer messages come from more creators, draw higher viewer engagement, and use subtler arguments. This change is important in the Global South because it can reduce support for climate action in places already facing high vulnerability and development pressures.

Core claim

The paper finds a clear transition toward solution-focused narratives that target renewable energy, climate governance, and environmental advocates, with this new denial produced by a wider array of actors, attracting higher engagement, and using more sophisticated persuasive techniques than earlier outright rejection of climate facts.

What carries the argument

Large-scale collection of YouTube video data combined with qualitative classification of content into traditional denial versus new denial categories.

If this is right

  • New denial reaches wider audiences and is created by more varied producers than traditional denial.
  • The newer content uses more sophisticated persuasive methods focused on solutions.
  • These patterns hit regions with existing structural inequities hardest.
  • Current platform moderation policies often fail to address this adapting form of content.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same shift from denial to solution attacks may be appearing on other platforms or in neighboring countries with similar digital environments.
  • Detection systems for harmful content will need to track narratives that accept climate facts while opposing specific policies.
  • Longer-term monitoring could test whether engagement advantages for new denial continue as platforms change their rules.

Load-bearing premise

The classification of videos into traditional denial versus new denial correctly identifies the main strategies without significant mislabeling or selection bias across the full dataset.

What would settle it

Re-examination of a random sample of videos showing that a large share labeled as new denial actually contain direct rejections of climate science would undermine the reported transition.

Figures

Figures reproduced from arXiv: 2604.24223 by Marcelo Sartori Locatelli, Meeyoung Cha, Pedro Dutenhefner, Pedro Loures Alzamora, Virgilio Almeida, Wagner Meira Jr., Wenchao Dong.

Figure 1
Figure 1. Figure 1: The evolution of denial narratives. Old Denial rejects the existence of climate change, while New Denial accepts climate change but attacks solutions, scientists, and the climate movement. are driving climate change [50], contributing to increased extreme weather events [44], and growing threats to food security [16], denialist narratives continue to proliferate across social media [25]. These movements le… view at source ↗
Figure 2
Figure 2. Figure 2: UMAP visualization of video content embeddings for 2019 and 2024 (A-B), showing the semantic clustering of old view at source ↗
Figure 3
Figure 3. Figure 3: Monthly distribution of YouTube channels producing (A) old denial content and (B) new denial content, by channel view at source ↗
Figure 4
Figure 4. Figure 4: Thematic structure of old (left) and new (right) denial topics, organized into seven major themes. Numbers indicate view at source ↗
Figure 5
Figure 5. Figure 5: Proportion of videos related to old and new denialist narratives over time. Events that received significant coverage view at source ↗
Figure 6
Figure 6. Figure 6: Difference in prevalence (%) of (A) persuasions in video content and (B) ToM mental states in comments between denial view at source ↗
Figure 7
Figure 7. Figure 7: Yearly engagement measured by view count for old denial (blue) and new denial (red) videos across quantile groups. view at source ↗
Figure 8
Figure 8. Figure 8: Information panel for Brazilian YouTube climate change videos. The English translation is shown below. view at source ↗
Figure 9
Figure 9. Figure 9: UMAP visualization of video content embeddings for each year, showing the semantic clustering of old denial (blue), view at source ↗
Figure 10
Figure 10. Figure 10: Yearly engagement as like and comment count for old denial (blue) and new denial (red) videos across quantile view at source ↗
Figure 11
Figure 11. Figure 11: Two-dimensional visualization of topic modeling results using UMAP for dimensionality reduction. view at source ↗
read the original abstract

Climate misinformation continues to erode support for climate action, a challenge that is especially acute in the Global South, where high climate vulnerability intersects with development pressures. In rapidly evolving digital ecosystems, misinformation adapts to platform incentives, shifting from overt rejection of climate science toward more subtle narratives that contest proposed solutions. This study integrates large-scale platform data with qualitative content analysis to examine how information systems shape contemporary climate discourse. Using a dataset of 226,775 climate-related YouTube videos from Brazil (2019-2025), we identify two dominant misinformation strategies: traditional denial that disputes scientific evidence and an emerging "new denial" that accepts climate change while undermining mitigation and adaptation policies. We find a pronounced transition to solution-focused narratives that target renewable energy, climate governance, and environmental advocates. New denial content is produced by a wider array of actors, attracts higher engagement, and employs more sophisticated persuasive techniques. These patterns disproportionately affect regions already facing structural inequities and bring broader concerns about platform accountability in unequal information environments and suggest the need for governance approaches capable of addressing new denial, a rapidly adapting form of harmful content that often evades existing moderation policies.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 1 minor

Summary. The paper analyzes a dataset of 226,775 climate-related YouTube videos from Brazil (2019-2025) using large-scale platform data combined with qualitative content analysis. It identifies two misinformation strategies—traditional denial disputing scientific evidence and an emerging 'new denial' that accepts climate change while targeting solutions such as renewable energy, climate governance, and environmental advocates—and claims a pronounced transition toward the latter, with new denial produced by a wider array of actors, attracting higher engagement, and employing more sophisticated persuasive techniques.

Significance. If the central claims hold after addressing methodological transparency, the work would offer a valuable empirical contribution to understanding adaptive climate misinformation in the Global South, where vulnerability intersects with digital platforms. The scale of the dataset and focus on solution-focused narratives provide a basis for policy discussions on platform accountability, though the current lack of detail on classification and analysis limits its immediate utility for the field.

major comments (3)
  1. [Abstract] Abstract: The description of findings from the 226,775-video dataset provides no details on video selection criteria, how 'climate-related' videos were identified via keywords or other filters, or subsampling for qualitative review, which is load-bearing for the transition claim.
  2. [Methods] Methods section on qualitative analysis: No operational definitions, inter-coder agreement scores, or reliability metrics are reported for classifying videos as traditional denial versus new denial, risking subjective mislabeling that underpins the headline finding of a shift to solution-focused narratives.
  3. [Results] Results on engagement and actors: The claims that new denial attracts higher engagement and involves more actors lack description of statistical tests, controls for platform algorithm effects, video metadata confounders, or temporal trends, making it impossible to evaluate whether differences are genuine or artifacts of selection.
minor comments (1)
  1. [Abstract] Abstract: The time period (2019-2025) and country focus (Brazil) are stated but could be more explicitly tied to the dataset size for immediate context.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their thoughtful and constructive review. Their comments on methodological transparency are well-taken, and we have revised the manuscript to provide greater detail on data collection, coding procedures, and statistical analyses. We believe these changes address the concerns and enhance the paper's rigor while preserving its core findings on the shift toward new denial in Brazilian climate discourse.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The description of findings from the 226,775-video dataset provides no details on video selection criteria, how 'climate-related' videos were identified via keywords or other filters, or subsampling for qualitative review, which is load-bearing for the transition claim.

    Authors: We agree that additional details are necessary for transparency. In the revised abstract, we now include: 'Using keyword-based searches via the YouTube Data API for climate-related terms in Portuguese and English, we assembled a dataset of 226,775 videos uploaded between 2019 and 2025. A stratified random subsample of 500 videos was selected for in-depth qualitative analysis to identify misinformation strategies.' The full dataset supports the quantitative claims on engagement and actor diversity, while the subsample underpins the classification of traditional versus new denial, demonstrating the temporal transition. revision: yes

  2. Referee: [Methods] Methods section on qualitative analysis: No operational definitions, inter-coder agreement scores, or reliability metrics are reported for classifying videos as traditional denial versus new denial, risking subjective mislabeling that underpins the headline finding of a shift to solution-focused narratives.

    Authors: We have substantially expanded the Methods section to include operational definitions and reliability metrics. Traditional denial is operationalized as videos that explicitly reject the scientific consensus on climate change (e.g., claiming it is a hoax or natural variation only). New denial encompasses content that acknowledges climate change but argues against solutions, such as claiming renewables are ineffective or that policies harm the economy. Two independent coders analyzed a training set of 300 videos, achieving an inter-coder reliability of Cohen's κ = 0.85. The full coding was performed by one coder with 10% double-coded for quality control. These details are now reported to allow for replication and to mitigate concerns of subjectivity. revision: yes

  3. Referee: [Results] Results on engagement and actors: The claims that new denial attracts higher engagement and involves more actors lack description of statistical tests, controls for platform algorithm effects, video metadata confounders, or temporal trends, making it impossible to evaluate whether differences are genuine or artifacts of selection.

    Authors: We have added statistical tests and controls to the Results section. Engagement differences were assessed using independent samples t-tests, revealing that new denial videos had significantly higher average views (t = 12.4, p < 0.001) and comments. To control for confounders, we employed multivariate regression models including video duration, channel size, and upload year as covariates; the effect of denial type remained significant. Temporal trends are visualized in a new figure showing the increasing proportion of new denial content over time. Regarding platform algorithm effects, we note that while we cannot directly observe recommendation mechanisms, our analysis of organic search and channel-driven views provides indirect evidence. We have added a limitations paragraph discussing potential selection biases. revision: partial

Circularity Check

0 steps flagged

No circularity: empirical qualitative analysis with no derivations or self-referential loops

full rationale

The paper is a data-driven empirical study that collects 226,775 YouTube videos, applies qualitative content analysis to classify them into traditional denial versus new denial categories, and reports observed patterns in narratives, actors, and engagement. No equations, fitted parameters, predictions derived from inputs, or derivation chains appear in the abstract or described methodology. Classification relies on external platform data and manual review rather than any internal construction that reduces to its own definitions or prior self-citations. The central claims about a transition to solution-focused narratives rest on the dataset and typology application, which are independent of the reported results and do not loop back by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claims rest on the representativeness of the YouTube dataset for Brazilian climate discourse and the validity of the qualitative distinction between denial types; no free parameters, invented entities, or formal axioms are introduced.

axioms (1)
  • domain assumption The 226,775-video dataset and qualitative coding reliably identify dominant misinformation strategies in Brazilian climate discourse
    Stated in the abstract as the basis for identifying traditional and new denial patterns without further justification of sampling or inter-coder agreement.

pith-pipeline@v0.9.0 · 5522 in / 1349 out tokens · 74865 ms · 2026-05-07T17:15:54.642499+00:00 · methodology

discussion (0)

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