The Current State of Leadership Research: Identifying Key Trends through Natural Language Processing and Machine Learning Analysis

The impact of leadership on organizational performance and success is a well-established theme, leading to a significant expansion in related scientific studies. This has made identifying and understanding the current state of literature challenging. Most studies focus on specific aspects of leadership, offering a fragmented view of the field. This study employs Natural Language Processing (NLP) techniques and a machine learning approach to analyze 19,429 research papers from Web of Science and Scopus. We aimed to identify and interpret current trends in leadership research, providing a comprehensive overview of the leadership domain, highlighting five key research trends: (1) Leadership and Digital Transformation Research (LDTR); (2) Leadership and Organizational Performance Research (LOPR); (3) Educational Leadership Research (ELR); (4) Leadership Practices and Development Research (LPDR); and (5) Gender and Diversity Leadership Research (GDLR). This overview not only delineates current trends but also aids researchers in identifying significant gaps in existing literature, thereby facilitating the development of innovative research projects and initiatives.