Human-Computer Interaction: A Literature Analysis from to Using Automated Text Mining

  • Unique Paper ID: 174191
  • Volume: 8
  • Issue: 12
  • PageNo: 1655-1662
  • Abstract:
  • This study aims to explore the research themes and trends in the field of Human-Computer Interaction (HCI) over the past two decades, specifically from to. To achieve this, an automated content analysis utilizing text mining and probabilistic topic modeling was conducted on 33,830 peer-reviewed journal articles published between and, indexed in the SCOPUS database. The analysis revealed 53 distinct topics that define the themes and trends within the HCI field. These topics were further categorized, leading to the development of a systematic taxonomy that maps the evolution of HCI research and practices over the past 20 years. This taxonomy comprises six primary categories: "machinery systems," "HCI body of knowledge," "feature identification," "brain-computer interfaces," "interaction," and "medical." This study is expected to offer valuable insights and contribute to the advancement of HCI research, practices, and investments in the future.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{174191,
        author = {Janhvi A. Chauhan and Dhaval M. Modi},
        title = {Human-Computer Interaction: A Literature Analysis from  to  Using Automated Text Mining},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {8},
        number = {12},
        pages = {1655-1662},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174191},
        abstract = {This study aims to explore the research themes and trends in the field of Human-Computer Interaction (HCI) over the past two decades, specifically from to. To achieve this, an automated content analysis utilizing text mining and probabilistic topic modeling was conducted on 33,830 peer-reviewed journal articles published between and, indexed in the SCOPUS database. The analysis revealed 53 distinct topics that define the themes and trends within the HCI field. These topics were further categorized, leading to the development of a systematic taxonomy that maps the evolution of HCI research and practices over the past 20 years. This taxonomy comprises six primary categories: "machinery systems," "HCI body of knowledge," "feature identification," "brain-computer interfaces," "interaction," and "medical." This study is expected to offer valuable insights and contribute to the advancement of HCI research, practices, and investments in the future.},
        keywords = {human-computer interaction, research themes and trends, literature analysis, text mining, topic modeling},
        month = {March},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 8
  • Issue: 12
  • PageNo: 1655-1662

Human-Computer Interaction: A Literature Analysis from to Using Automated Text Mining

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