Artificial intelligence and digital advertising: persuasive discourses and citizenship in academic research
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Abstract
Introduction: This study presents a bibliometric analysis of the evolution of scientific production related to persuasive discourse in personalized digital advertising targeted at citizens. The aim is to examine how artificial intelligence has reshaped communication segmentation practices, introducing new theoretical, ethical, and social challenges. Methodology: A bibliometric analysis was conducted using the Biblioshiny interface (based on Bibliometrix in R) on a corpus of 141 scientific articles indexed in Scopus and Web of Science, published between 2000 and 2024. The study included productivity indicators, institutional co-authorship networks, keyword co-occurrence analysis, and thematic mapping. Results: The findings identify four consolidated research lines: recommendation algorithms, programmatic advertising, data privacy, and algorithmic segmentation. The field displays a predominantly technological orientation, limited international collaboration, and minimal integration of critical approaches focused on digital citizenship. Discussion: The evidence reveals a gap between the technical advancement of personalized advertising and the academic reflection on its social implications. This disconnect undermines the field’s potential to influence regulatory, educational, and ethical debates related to artificial intelligence. Conclusions: The study proposes a renewed, critical, and interdisciplinary research agenda centered on communication rights, transparency in automated systems, and digital literacy as priorities for future investigations in AI-mediated advertising contexts.
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