AI-Driven Climate Change Misinformation on Social Media and Its Impact on Public Beliefs

Abstract

The rising integration of artificial intelligence (AI) into social media platforms has extensively transformed the production and visibility of climate change–related content.

The study examines the role of AI-driven mechanisms in the spread of climate change misinformation on social media, particularly focused on TikTok and X (formally twitter) and investigates their impact on public beliefs. Employing mixed-methods research design, the research combines qualitative content analysis of climate-related social media posts with a survey of users to assess exposure patterns, perceived credibility, and belief formation. The analysis focuses on AI-enabled processes such as algorithmic recommendation, automated amplification, and engagement-driven visibility that contribute to the circulation of deceptive narratives.

The findings reveal that AI-driven augmentation enhances the reach of emotionally framed and deceptive climate content, influencing public understanding, trust in climate science, and perceptions of climate risk. Frequent exposure to such misinformation is found to contribute skepticism, and polarization among audiences.

By situating these research findings within media effects and information disorder frameworks, the study contributes to scholarly debates on AI, misinformation, and climate communication. This exploration offers policy-relevant insights for platform governance, media literacy initiatives, and ethical AI practices aimed at mitigating the societal impact of climate change misinformation.

Keywords:  Artificial intelligence, Climate change misinformation, Social media, Public beliefs, Algorithmic amplification