A Bibliometric Analysis of Virtual Influencers: Performance Indicators and Conceptual Structure

Abstract

Artificial intelligence-powered virtual influencers, as digital characters emulating human characteristics, are transforming the way brands interact with consumers and are rapidly becoming a growing field of research in marketing literature. However, despite this burgeoning interest, bibliometric studies that holistically evaluate the accumulated knowledge in the field remain limited. This study aims to examine 258 publications indexed in the Web of Science (WoS) Core Collection within the disciplines of Business and Management, comprising peer-reviewed English articles, through a comprehensive bibliometric analysis. Data were evaluated using performance analysis and science mapping techniques via the bibliometrix package and Biblioshiny interface in the R programming language. The findings demonstrate that research on virtual influencers expanded rapidly during the 2021–2026 period, particularly from 2024–2025 onwards, with an annual growth rate of 111.68%. Furthermore, journals such as the Journal of Retailing and Consumer Services and the Journal of Business Research, as well as China-based authors and institutions, stand out in the field. Keyword and co-occurrence network analyses reveal that the literature has matured around the concepts of credibility, authenticity, and trustworthiness.