Public Sentiment Toward AI Governance and Global Regulation: An Analysis of YouTube Comments on the International Debate on Artificial Intelligence Ethics

This study investigates public perceptions of artificial intelligence governance and ethics through a mixed-methods analysis of YouTube comments from three highly engaged international videos published between 2021 and 2025. Using YouTube Data API extraction and rigorous preprocessing, a total of 711 cleaned comments were analyzed to capture contemporary discourse surrounding global AI regulation, ethical concerns, and societal implications. The quantitative phase employed a combination of lexicon-based and transformer-based sentiment classification. Results show that public sentiment is predominantly positive, followed by significant negative responses reflecting concerns about safety, existential risks, and institutional trust. Aspect-based sentiment analysis reveals strong positive reactions to themes such as ethics, bias mitigation, and innovation, while safety and regulatory uncertainty generate the most negative sentiment. Topic modeling using LDA and BERTopic consistently identifies clusters related to existential threat narratives, human–machine comparison, governance debates, and skepticism toward industry figures. The qualitative phase deepens these findings by examining rhetorical patterns, discursive framing, and emotional expressions within a stratified sample of comments. Users frequently articulate contrasting frames of technological optimism and pessimism, often invoking metaphors, analogies, and references to current global developments. This interpretive layer complements the computational results, illuminating how societal hopes, fears, and expectations shape public reasoning about AI governance. Integrated analysis demonstrates strong convergence between quantitative and qualitative insights, indicating that public discourse is complex, polarized, and highly sensitive to both technological advances and the communication strategies of influential actors. The study underscores the importance of transparent policy communication, inclusive governance frameworks, and sustained public engagement in shaping responsible AI development.