Exploration of Interdisciplinary Fusion and Interorganizational Collaboration With the Advancement of AI Research: A Case Study on Natural Language Processing

Network analysis is increasingly being used as a decision-making support tool for science and technology policy and technology management through the understanding of the trends and structure of innovation activities and the prediction of their changes. Since convergence and diversity are generally regarded as opportunities for groundbreaking innovation, analysis of interdisciplinary fusion and interorganizational collaboration using network analysis is expected to provide useful suggestions for policy formation and technology management. Nevertheless, little quantitative analysis has been conducted to date, especially for interorganizational collaboration. Meanwhile, regarding artificial intelligence research, its effectiveness has accelerated its application in various fields, and in the process, interdisciplinary fusion and interorganizational collaboration are developing. In this study, we focused on “natural language processing (NLP),” which is said to have recently surpassed human performance, and conducted a microanalysis by visualizing community formation, topic transition including technology integration with other fields and organizations, and their collaboration engaged in research front. Specifically, using the Scopus dataset, we extracted NLP papers and conducted a network analysis. As a result, we visualized these developments in the fast-changing field, and second, we showed that our method is applicable to many other fields. These results will help researchers interested in the application of NLP.