Bibliometric Analysis of Information Communication Technology for Sustainable Development: A Machine-Learning-Based Approach

Autor/inn/en	Oosthuizen, Rudolph; Pretorius, Leon
Titel	Bibliometric Analysis of Information Communication Technology for Sustainable Development: A Machine-Learning-Based Approach
Quelle	In: International Journal of Learning and Change, 14 (2022) 5-6, S.537-558 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1740-2875
DOI	10.1504/IJLC.2022.126421
Schlagwörter	Bibliometrics; Information Technology; Sustainable Development; Natural Language Processing; Artificial Intelligence; Knowledge Management; Quality of Life; Models + Suchen Sie Ihr Suchwort? Bibliometrie; Informationstechnologie; Nachhaltige Entwicklung; Natürliche Sprache; Künstliche Intelligenz; Wissensmanagement; Lebensqualität; Analogiemodell
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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01