Mapping Human-Computer Interaction Research Themes and Trends from Its Existence to Today: A Topic Modeling-Based Review of past 60 Years

GÜRCAN F., Cagiltay N. E., ÇAĞILTAY K.

INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION, cilt.37, sa.3, ss.267-280, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 37 Sayı: 3
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1080/10447318.2020.1819668
  • Dergi Adı: INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, ABI/INFORM, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Compendex, Computer & Applied Sciences, INSPEC, Library and Information Science Abstracts, Linguistics & Language Behavior Abstracts, Psycinfo, Sociological abstracts
  • Sayfa Sayıları: ss.267-280
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

As it covers a wide spectrum, the research literature of human-computer interaction (HCI) studies has a rich and multi-disciplinary content where there are limited studies demonstrating the big picture of the field. Such an analysis provides researchers with a better understanding of the field, revealing current issues, challenges, and potential research gaps. This study aims to explore the research trends in the developmental stages of the HCI studies over the past 60 years. Automated text mining with probabilistic topic modeling has been used to analyze 41,720 journal articles that are indexed by the SCOPUS database between 1957 and 2018. The results of this study reveal 21 major topics mapping the research landscape of HCI. By extending the discovered topics beyond a snapshot, the topics were analyzed considering their developmental stages, volume, and accelerations to provide a panoramic view that shows the increase and decrease of trends over time. In this context, the transition of HCI studies from machine-oriented systems to human-oriented systems indicates its future direction toward context-aware adaptive systems.