<![CDATA[Over the past four decades, the application of Neuro-Linguistic Programming (NLP) has expanded significantly, attracting considerable interest from researchers worldwide. Despite the proliferation of research across various disciplines, comprehensive reviews that map global trends in NLP research remain limited. Consequently, this study aims to evaluate the evolution and contributions of NLP research over time, and to identify the key topics, leading researchers, prominent institutions, and influential countries involved in its development. This study employs a literature review methodology using the Scopus database as of September 27, 2024, with the keywords “neuro-linguistic” and “programming.” Bibliographic data from 280 publications were exported in CSV format, processed using Excel, and analyzed with VOSviewer software to map networks and visualize findings. The results of the study are as follows: (1) NLP research output peaked in 2018, with over 20 documents published that year; (2) the most cited article is titled “Machine Learning Approach to Personality Type Prediction Based on the Myers–Briggs Type Indicator”; (3) the researcher contributing the most to this field is Tosey, with nine publications; (4) the United Kingdom and Europe exhibit a high concentration of NLP research and robust collaboration networks; (5) in the Scopus database, articles constitute the majority of documents, comprising 62.9% of the total publications; (6) NLP research is predominantly concentrated in the social sciences and computer science domains, where NLP techniques are utilized for developing technologies such as chatbots, text analysis, and linguistic data processing. The findings indicate that NLP holds substantial potential for application in psychology and the social sciences. However, its application in the domain of sports remains underexplored. This represents a significant opportunity to implement NLP in sports, particularly for mental training and enhancing athletic performance.]]>
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