Wang, S.; Zhang, M.; Hu, T.; Fu, X.; Gao, Z.; Halloran, B.; Liu, Y. A Bibliometric Analysis and Network Visualisation of Human Mobility Studies from 1990 to 2020: Emerging Trends and Future Research Directions. Sustainability2021, 13, 5372.
Wang, S.; Zhang, M.; Hu, T.; Fu, X.; Gao, Z.; Halloran, B.; Liu, Y. A Bibliometric Analysis and Network Visualisation of Human Mobility Studies from 1990 to 2020: Emerging Trends and Future Research Directions. Sustainability 2021, 13, 5372.
Wang, S.; Zhang, M.; Hu, T.; Fu, X.; Gao, Z.; Halloran, B.; Liu, Y. A Bibliometric Analysis and Network Visualisation of Human Mobility Studies from 1990 to 2020: Emerging Trends and Future Research Directions. Sustainability2021, 13, 5372.
Wang, S.; Zhang, M.; Hu, T.; Fu, X.; Gao, Z.; Halloran, B.; Liu, Y. A Bibliometric Analysis and Network Visualisation of Human Mobility Studies from 1990 to 2020: Emerging Trends and Future Research Directions. Sustainability 2021, 13, 5372.
Abstract
Studies on human mobility have a long history with increasingly strong connections to multi-disciplines across social science, environmental science, information and technology, computer science, engineering, and health science. However, what is lacking in the current research is a summary of studies on human mobility to identify the evolutional pathway and future research directions. To address this gap, we conduct a systematic review of human mobility-related studies published from 1990 to 2020. Drawing on the selected publications retrieved from the Web of Science, we conduct a bibliometric analysis and network visualisation by CiteSpace and VOSviewer on publication years and numbers, authors and their countries and afflictions, citations, topics, abstracts, keyword, and journals. Our findings show that human mobility-related studies have become increasingly interdisciplinary and multi-dimensional, enhanced by the involvement of multi-source big data, the development of technologies, the innovation of modelling approaches, and the novel applications in various areas. We also summarise four future research directions proposed by top cited authors and mobility studies, in terms of data sources, modelling methods, applications, and technologies. We advocate in-depth research on human mobility to address real-world problems and contribute to social good as promising future orientations through integrating multi-source big data and advanced modelling methods facilitated by artificial intelligence, and machine and deep learning.
Keywords
Human mobility; literature review; bibliometric analysis; network visualisation; CiteSpace; VOSviewer
Subject
Business, Economics and Management, Accounting and Taxation
Copyright:
This 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.
