Title: Bibliometric analysis of information communication technology for sustainable development: a machine-learning-based approach

Authors: Rudolph Oosthuizen; Leon Pretorius

Addresses: Department of Engineering and Technology Management, University of Pretoria and Defence Peace Safety and Security, CSIR, Pretoria, South Africa ' Department of Engineering and Technology Management, University of Pretoria, Pretoria, South Africa

Abstract: Publication of research outputs is a method of researchers to capture their knowledge generated. Analysing the publication topics and trends in a research field can provide insight into the main research trends. A bibliometric analysis, based on the topics from published literature, provides insight into the focus areas and trends of a research field. The objective of this paper is to extract the main research topics from papers on 'sustainable development' and 'information communication technology'. The research topics are extracted from the abstracts and titles of papers using machine-learning for topic modelling. This paper identified the topics of knowledge management, design process, social change, and smart systems, as the primary focus of research into information communication technology for sustainable development. A deeper analysis into smart systems identified quality of citizen life, solutions for the urban setting, energy, and the environment as key research concerns.

Keywords: sustainable development; information communication technology; natural language processing; NLP; topic modelling; research; bibliometric; literature; machine-learning; knowledge; research trends; research roadmap; abstracts; titles.

DOI: 10.1504/IJLC.2022.126421

International Journal of Learning and Change, 2022 Vol.14 No.5/6, pp.537 - 558

Received: 02 Jun 2020
Accepted: 28 Oct 2020
Published online: 26 Oct 2022 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article