| Title | New Trends in Smart Cities: The Evolutionary Directions Using Topic Modeling and Network Analysis |
|---|---|
| ID_Doc | 43438 |
| Authors | Oh, M; Ahn, C; Nam, H; Choi, S |
| Title | New Trends in Smart Cities: The Evolutionary Directions Using Topic Modeling and Network Analysis |
| Year | 2023 |
| Published | Systems, 11, 8 |
| Abstract | The COVID-19 pandemic has affected smart city operations and planning. Smart cities, where digital technologies are concentrated and implemented, face new challenges in becoming sustainable from social, ecological, and economic perspectives. Using text mining methodologies of topic modeling and network analysis, this study aims to identify keywords in the field of smart cities after the pandemic and provide a future-oriented perspective on the direction of smart cities. A corpus of 1882 papers was collected from the Web of Science and Scopus databases from December 2019 to November 2022. We identified six categories of potential issues in smart cities using topic modeling: "supply chain", "resilience", "culture and tourism", "population density", "mobility", and "zero carbon emission". This study differs from previous research because it is a quantitative study based on text mining analysis and deals with smart cities, given the prevalence of COVID-19. This study also provides insights into the development of smart city policies and strategies to improve urban resilience during the pandemic by anticipating and addressing related issues. The findings of this study will assist researchers, policymakers, and planners in developing smart city strategies and decision-making in socioeconomic, environmental, and technological areas. |
| https://www.mdpi.com/2079-8954/11/8/410/pdf?version=1691567339 |
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