Bibliometric Analysis Research Project for Artificial Intelligence (AI) Social Robot in Marketing

The marketing landscape is currently experiencing a significant transformation as a result of the advancements in artificial intelligence (AI), particularly with the integration of AI social robots. These independent entities are capable of engaging in complex social interactions with humans, representing a departure from traditional marketing strategies. This study aims to provide a comprehensive understanding of the role of AI social robots in marketing by employing bibliometric analysis and deep learning (DL) techniques to identify key trends, most relevant sources, challenges, and thematic clusters. Utilizing tools such as Bibliometrix R package, and DL models including Mean Sentence-BERT (SBERT) and BERT (Bidirectional Encoder Representations from Transformer) Base, the research analyses scholarly literature to identify emerging trends, most influential sources, and significant challenges such as user acceptance, privacy, safety, and ethical considerations. The findings highlight a substantial increase in research activity, with influential contributions from key sources, and underscore the superior performance of DL models in clustering research data. This study offers valuable insights to guide future research, inform strategic business decisions, and assist policymakers in effectively integrating AI social robots in marketing.