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Название: Exploring Gamification Research Trends Using Topic Modeling
Авторы: Ayaz, A.
Ozyurt, O.
Al-Rahmi, W. M.
Salloum, S. A.
Shutaleva, A.
Alblehai, F.
Habes, M.
Дата публикации: 2023
Издатель: Institute of Electrical and Electronics Engineers Inc.
Библиографическое описание: Ayaz, A, Ozyurt, O, Al-Rahmi, WM, Salloum, SA, Shutaleva, A, Alblehai, F & Habes, M 2023, 'Exploring Gamification Research Trends Using Topic Modeling', IEEE Access, Том. 11, стр. 119676-119692. https://doi.org/10.1109/ACCESS.2023.3326444
Ayaz, A., Ozyurt, O., Al-Rahmi, W. M., Salloum, S. A., Shutaleva, A., Alblehai, F., & Habes, M. (2023). Exploring Gamification Research Trends Using Topic Modeling. IEEE Access, 11, 119676-119692. https://doi.org/10.1109/ACCESS.2023.3326444
Аннотация: Gamification holds significant importance as an efficacious means to motivate individuals, stimulate their engagement, and foster desired behaviors. There is an increasing interest among researchers in exploring the domain of gamification. Consequently, it becomes crucial to identify specific research trends within this field. This study employs a comprehensive analysis of 4743 articles sourced from the Scopus database, utilizing the topic modeling approach, with the objective of discerning research patterns and trends within the gamification domain. The findings revealed the existence of thirteen distinct topics within the field. Notably, 'Health training,' 'Enhancing learning with technology,' and 'Game design framework' emerged as the most prominent topics, based on their frequency of research publications and popularity. This study serves as a valuable resource for researchers and practitioners seeking to stay abreast of the latest advancements in gamification. The identified issues through topic modeling can be employed to identify gaps in current research and potential directions for future research endeavors. © 2013 IEEE.
Ключевые слова: GAMIFICATION
MACHINE LEARNING
TEXT MINING
TOPIC MODELING
TREND ANALYSIS
DATA MINING
LEARNING SYSTEMS
BIBLIOMETRIC
GAME
GAMIFICATION
MACHINE-LEARNING
MARKET RESEARCHES
RESEARCH TRENDS
SYSTEMATIC
TEXT-MINING
TOPIC MODELING
TREND ANALYSIS
MARKET RESEARCH
URI: http://elar.urfu.ru/handle/10995/130942
Условия доступа: info:eu-repo/semantics/openAccess
cc-by-nc-nd
Текст лицензии: https://creativecommons.org/licenses/by-nc-nd/4.0/
Идентификатор SCOPUS: 85176309086
Идентификатор WOS: 001100934300001
Идентификатор PURE: 48553750
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2023.3326444
Располагается в коллекциях:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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Лицензия на ресурс: Лицензия Creative Commons Creative Commons