A Conceptual Space Integrating Artificial Intelligence, Fake News, and Media Education: A Bibliometric Synthesis

The current information ecosystem combines platformized social media with AI-enabled content production, accelerating fake news. Yet research remains siloed: computational detection studies rarely connect to media-education scholarship on critical literacy and democratic resilience, limit-ing human-centered interventions. This paper synthesizes the conceptual structure of artificial intelligence, fake news, and media education via bibliometric science mapping. Scopus and Web of Science records were retrieved, deduplicated in Bibliometrix, and analyzed as two corpora (AI–fake news: 920 documents, 2013–2026; media education–fake news: 231 documents, 2009–2026). Thematic maps identified dominant and emerging clusters, and a merged set of 467 references was modeled as an author-keyword co-occurrence network and visualized as a conceptual space. Results delineate five interlinked regions - fake news, media literacy, social networks, media education, and artificial intelligence - highlighting AI’s ambivalent role in generating and mitigating information disorder. The framework aligns technical models with pedagogy, governance, and evaluation priorities.