Engaging in sports via the metaverse? An examination through analysis of metaverse research trends in sports  

作　　者：Ahyun Kim Sang-Soo Kim 

机构地区：[1]Department of Business Administration,Dongyang Mirae University,Seoul,08221,South Korea [2]Department of Business Administration,Yong in University,Gyeonggi-do,17092,South Korea

出　　处：《Data Science and Management》2024年第3期181-188,共8页数据科学与管理（英文）

摘　　要：In sports, virtual spaces are sometimes utilized to enhance performance or user experience. In this study, we conducted a frequency analysis, semantic network analysis, and topic modeling using 134 abstracts obtained through keyword searches focusing on “sport(s)” in combination with “metaverse”, “augmented reality”, “virtual reality”, “lifelogging”, and “mixed reality”. First, the top 20 words were extracted through frequency analysis, and then each type of extracted word was retained to select seven words. The analysis revealed the emergence of key themes such as “user(s)”, “game(s)”, “technolog(y/ies)”, “experience(d)”, “physical”, “training”, and “video”, with variations in intensity depending on the type of metaverse. Second, the relationships between the words were reconfirmed using semantic networks based on the seven selected words. Finally, topic modeling analysis was conducted to uncover themes specific to each type of metaverse. We also found that “performance/scoring” was a prominent word across all types of metaverses. This suggests that in addition to providing enjoyment through sports, there is a high possibility that all users (both general users and athletes) utilize the metaverse to achieve positive outcomes and success. The importance of “performance/scoring” in sports may seem obvious;however, it also provides significant insights for practitioners when combined with metaverse-related keywords. Ultimately, this study has managerial implications for enhancing the performance of specialized users in the sports industry.

关 键 词：SPORT Metaverse Frequency analysis Topic modeling Semantic network analysis 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]