Mitigating crowded transportation terminals nearby mega-sports events

Elkhouly, Reem; Tamaki, Emi; Iwasaki, Kei

doi:10.1080/0144929x.2022.2048890

Cited by 4 publications

(2 citation statements)

References 52 publications

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“…While the responses of national sports leagues varied, international leagues saw a complete suspension of sporting events at all levels ( Sivevska and Popeska, 2020 ). Throughout the pandemic, professional sports leagues had limited or banned spectator attendance; major events like the Olympics and various sports leagues canceled or postponed ( Elkhouly et al, 2022 ), and soccer is no exception.…”

Section: Introductionmentioning

confidence: 99%

Soccer’s AI transformation: deep learning’s analysis of soccer’s pandemic research evolution

Lee,

Song,

Kim

et al. 2023

Front. Psychol.

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

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Section: Introductionmentioning

confidence: 99%

Soccer’s AI transformation: deep learning’s analysis of soccer’s pandemic research evolution

Lee,

Song,

Kim

et al. 2023

Front. Psychol.

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“…The response of national sports leagues varied, but international leagues experienced a complete shutdown of sporting events at all levels ( Bas et al, 2020 ). Throughout the pandemic, professional sports leagues both restricted and completely prohibited spectators, and large events such as the Olympics and various sports leagues were canceled or postponed ( Elkhouly et al, 2022 ). According to Füzéki et al (2020) , the most serious sports-related problem caused by the pandemic is that people have almost no opportunities for exercise and physical activity in their daily life.…”

Section: Introductionmentioning

confidence: 99%

LDA-based topic modeling for COVID-19-related sports research trends

2022

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IntroductionThe COVID-19 pandemic could generate a turning point for introducing a new system for sports participation and business. The purpose of this study is to explore trends and topic structures of COVID-19-related sports research by analyzing the relevant literature.MethodsSports studies related to COVID-19 were collected in searching international academic databases. After the pre-processing step using the refinement and morpheme analysis function of the Net Miner program, topic modeling and social network analysis were used to analyze Journal Citation Reports found using the search term ‘COVID-19 sports’.ResultsAs a result, this study used subject modeling to reveal important potential topics in COVID-19-related sports research articles. ‘Sports participation’, ‘elite players’, and ‘sports industry’ were macroscopically classified, and detailed research topics could be identified from each division.ConclusionThis study revealed important latent topics from COVID-19-related sports research articles using topic modeling. The results of the research elucidate the structure of academic knowledge on this topic and provide guidance for future research.

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Estimating urban rail transit passenger inflow caused by special events occurrences fusing multi-source data

Zhang

et al. 2023

Neural Comput & Applic

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Mitigating crowded transportation terminals nearby mega-sports events

Cited by 4 publications

References 52 publications

Soccer’s AI transformation: deep learning’s analysis of soccer’s pandemic research evolution

Soccer’s AI transformation: deep learning’s analysis of soccer’s pandemic research evolution

LDA-based topic modeling for COVID-19-related sports research trends

Estimating urban rail transit passenger inflow caused by special events occurrences fusing multi-source data

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