Bibliometric analysis of information communication technology for sustainable development: a machine-learning-based approach. (16th September 2022)

• Record Type: Journal Article
• Authors: Oosthuizen, Rudolph; Pretorius, Leon
• Is Part Of: International journal of learning and change. Volume 14:Number 5/6(2022)
• Page Start: 537
• Page End: 558
• Publication Date: 2022-09-16
• Subjects: sustainable development -- information communication technology -- natural language processing -- NLP -- topic modelling -- research -- bibliometric -- literature -- machine-learning -- knowledge -- research trends -- research roadmap -- abstracts -- titles; Organizational learning -- Periodicals; Knowledge management -- Periodicals; Technological innovations -- Management -- Periodicals; 658.406
• Languages: English
• ISSNs: 1740-2875

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.