CHARTING CONNECTIONS: A SOCIAL NETWORK ANALYSIS OF RESEARCH COLLABORATION IN AI-DRIVEN HUMAN RESOURCE MANAGEMENT

Abstract

The rapid adoption of Artificial Intelligence (AI) in Human Resource Management (HRM) has transformed traditional workforce management by enabling intelligent recruitment, employee performance evaluation, talent analytics, workforce planning, and organizational decision-making. Simultaneously, the growing volume of research publications in AI-driven HRM has created complex collaboration networks among researchers, institutions, and countries. Social Network Analysis (SNA) provides an effective methodology for exploring these collaborative relationships by identifying influential authors, research communities, institutional partnerships, and knowledge diffusion patterns. This paper presents a comprehensive Social Network Analysis framework for examining research collaboration in AI-driven Human Resource Management. The proposed framework integrates bibliometric analysis, network construction, graph analytics, and visualization techniques to investigate co-authorship, institutional collaboration, countrylevel partnerships, keyword co-occurrence, and citation relationships. Graph-based metrics including degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, network density, and modularity are utilized to evaluate collaboration strength and identify influential research communities. Comparative analysis demonstrates that AI-driven HRM research has experienced significant global collaboration growth, interdisciplinary knowledge sharing, and increased institutional connectivity over recent years. The findings provide valuable insights into emerging research trends, collaborative structures, influential contributors, and future research opportunities within AI-enabled Human Resource Management. The proposed framework contributes to strategic research planning, policy formulation, and international scientific collaboration by providing a data-driven understanding of the evolving research ecosystem.