AUTHOR=Lee Jea Woog , Song Sangmin , Kim YoungBin , Park Seung-Bo , Han Doug Hyun TITLE=Soccer’s AI transformation: deep learning’s analysis of soccer’s pandemic research evolution JOURNAL=Frontiers in Psychology VOLUME=14 YEAR=2023 URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2023.1244404 DOI=10.3389/fpsyg.2023.1244404 ISSN=1664-1078 ABSTRACT=Introduction

This paper aims to identify and compare changes in trends and research interests in soccer articles from before and during the COVID-19 pandemic.

Methods

We compared research interests and trends in soccer-related journal articles published before COVID-19 (2018–2020) and during the COVID-19 pandemic (2021–2022) using Bidirectional Encoder Representations from Transformers (BERT) topic modeling.

Results

In both periods, we categorized the social sciences into psychology, sociology, business, and technology, with some interdisciplinary research topics identified, and we identified changes during the COVID-19 pandemic period, including a new approach to home advantage. Furthermore, Sports science and sports medicine had a vast array of subject areas and topics, but some similar themes emerged in both periods and found changes before and during COVID-19. These changes can be broadly categorized into (a) Social Sciences and Technology; (b) Performance training approaches; (c) injury part of body. With training topics being more prominent than match performance during the pandemic; and changes within injuries, with the lower limbs becoming more prominent than the head during the pandemic.

Conclusion

Now that the pandemic has ended, soccer environments and routines have returned to pre-pandemic levels, but the environment that have changed during the pandemic provide an opportunity for researchers and practitioners in the field of soccer to detect post-pandemic changes and identify trends and future directions for research.