About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
Emerging Technologies for Developing Countries. 5th EAI International Conference, AFRICATEK 2022, Bloemfontein, South Africa, December 5-7, 2022, Proceedings

Research Article

Application of Latent Dirichlet Allocation Topic Model in Identifying 4IR Research Trends

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-35883-8_6,
        author={Muthoni Masinde},
        title={Application of Latent Dirichlet Allocation Topic Model in Identifying 4IR Research Trends},
        proceedings={Emerging Technologies for Developing Countries. 5th EAI International Conference, AFRICATEK 2022, Bloemfontein, South Africa, December 5-7, 2022, Proceedings},
        proceedings_a={AFRICATEK},
        year={2023},
        month={7},
        keywords={Latent Dirichlet Allocation (LDA) Fourth Industrial Revolution (4IR) Technology Trends Bibliometric Analysis and Topic Models},
        doi={10.1007/978-3-031-35883-8_6}
    }
    
  • Muthoni Masinde
    Year: 2023
    Application of Latent Dirichlet Allocation Topic Model in Identifying 4IR Research Trends
    AFRICATEK
    Springer
    DOI: 10.1007/978-3-031-35883-8_6
Muthoni Masinde1,*
  • 1: Central University of Technology
*Contact email: muthonimasinde@gmail.com

Abstract

The dynamic nature of the technologies associated with the fourth Industrial Revolution (4IR) presents complex scenarios for researchers, practitioners and policymakers alike. To this end, reaching decisions such as what technology to invest/train in could be made easier through a 4IR technology trend predictive tool. In this paper, we apply Latent Dirichlet Allocation (LDA) topic model to identify and predict trends in 4IR technologies. The LDA models were developed and trained using text composed of abstracts, titles and keywords retrieved from 11,7314-IR related to the 2012 to 2022 publications in the Web of Science database. The effectiveness of the resulting tool was then evaluated using text from email message distributed to subscribers of the IEEE’s Tccc-announce mailing list. From the results, our model correctly identifies trends in the following 4IR technologies and applications domains: Internet of Things, Artificial Intelligence/Machine Learning, Big Data/Data Analytics, Augmented Reality, Smart Manufacturing, Supply Chains, Sustainability and Circular Economy. By plotting and visualizing these trends over time (2019 to 2022), the validation text confirms our tool’s ability to identify the trajectory developments as identified by other similar tools such as Bibliometric Analysis.

Keywords
Latent Dirichlet Allocation (LDA) Fourth Industrial Revolution (4IR) Technology Trends Bibliometric Analysis and Topic Models
Published
2023-07-06
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-35883-8_6
Copyright © 2022–2025 ICST
EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL