Mapping the Intellectual Structure and Emerging Frontiers of AI-Driven Social Media Marketing: A Bibliometric Analysis of Recent Research - Adelia, Winalda; Nuralam, Inggang Perwangsa (PINISI Discretion Review, 2025)
The rapid integration of artificial intelligence (AI) into social media marketing has generated a growing and fragmented body of scholarly research, creating a need for systematic knowledge consolidation. Despite the increasing volume of publications, a comprehensive understanding of the intellectual structure, thematic evolution, and emerging research directions in AI-driven social media marketing remains limited. Addressing this gap, this study aims to map the development, dominant themes, and future trajectories of AI-driven social media marketing research through a bibliometric analysis.Using data retrieved from the Scopus database on 7 January 2026, a total of 161 journal articles were analyzed. Bibliographic coupling, co-occurrence (co-word) analysis, and citation analysis were conducted using VOSviewer to examine publication growth, scientific influence, intellectual structures, and conceptual themes. The results reveal a significant upward trend in research output over the past five years, accompanied by increasing citation impact. The analysis identifies four core intellectual clusters and five dominant thematic clusters, highlighting key research streams such as AI-enabled marketing analytics, consumer engagement and personalization, automation and conversational AI, performance measurement, and ethical governance.This study contributes by providing a structured and data-driven overview of AI-driven social media marketing research, offering valuable insights for scholars and practitioners. The findings also highlight emerging themes, including generative AI and responsible AI practices, which offer promising directions for future research.