Exploring Gamification Research Trends Using Topic Modeling

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AYAZ A., ÖZYURT Ö., Al-Rahmi W. M., Salloum S. A., Shutaleva A., Alblehai F., ...Daha Fazla

IEEE ACCESS, cilt.11, ss.119676-119692, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 11
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1109/access.2023.3326444
  • Dergi Adı: IEEE ACCESS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
  • Sayfa Sayıları: ss.119676-119692
  • Anahtar Kelimeler: Gamification, machine learning, text mining, topic modeling, trend analysis
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

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.