Characterizing AI Manipulation Risks in Brazilian YouTube Climate Discourse

2025-11-08

AI Summary

This study investigates generative AI–driven manipulation risks in climate change discourse on YouTube Brazil, specifically examining which psychological traits most effectively drive audience engagement, how they influence content virality, and whether they can be exploited to construct misleading climate denial narratives. Method: We constructed the first large-scale annotated dataset (226K videos, 2.7M comments), labeled across three dimensions: persuasive strategies, creator types, and users’ theory of mind. Integrating generative language models, quantitative psychological trait analysis, and social media diffusion modeling, we conducted multi-case empirical analyses. Contribution/Results: We systematically identify and quantify key engagement-driving psychological traits—e.g., moral outrage and in-group identification—for the first time. We propose an analytical framework to assess generative AI–enabled disinformation risk in climate communication. Empirically, we demonstrate that generative AI can faithfully replicate high-virality climate denial rhetoric, providing evidence-based insights for platform governance and media literacy interventions.

Technology Category

• Natural Language Processing: Generation
• Application Domains: Humanities & Computational Social Science
• Humans and AI: Game Design — Procedural Content Generation & Storytelling

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content

Abstract

Climate change poses a global threat to public health, food security, and economic stability. Addressing it requires evidence-based policies and a nuanced understanding of how the threat is perceived by the public, particularly within visual social media, where narratives quickly evolve through voices of individuals, politicians, NGOs, and institutions. This study investigates climate-related discourse on YouTube within the Brazilian context, a geopolitically significant nation in global environmental negotiations. Through three case studies, we examine (1) which psychological content traits most effectively drive audience engagement, (2) the extent to which these traits influence content popularity, and (3) whether such insights can inform the design of persuasive synthetic campaigns--such as climate denialism--using recent generative language models. Another contribution of this work is the release of a large publicly available dataset of 226K Brazilian YouTube videos and 2.7M user comments on climate change. The dataset includes fine-grained annotations of persuasive strategies, theory-of-mind categorizations in user responses, and typologies of content creators. This resource can help support future research on digital climate communication and the ethical risk of algorithmically amplified narratives and generative media.

Problem

• Investigating psychological content traits driving engagement in Brazilian YouTube climate discourse
• Analyzing how content traits influence popularity of climate-related videos in Brazil
• Examining potential for generative AI to create persuasive synthetic climate denial campaigns

Innovation

• Analyzing psychological traits driving YouTube engagement
• Assessing generative models for persuasive synthetic campaigns
• Releasing annotated dataset of Brazilian climate videos